stillwater

Projects that follow the best practices below can voluntarily self-certify and show that they've achieved an Open Source Security Foundation (OpenSSF) best practices badge.

There is no set of practices that can guarantee that software will never have defects or vulnerabilities; even formal methods can fail if the specifications or assumptions are wrong. Nor is there any set of practices that can guarantee that a project will sustain a healthy and well-functioning development community. However, following best practices can help improve the results of projects. For example, some practices enable multi-person review before release, which can both help find otherwise hard-to-find technical vulnerabilities and help build trust and a desire for repeated interaction among developers from different companies. To earn a badge, all MUST and MUST NOT criteria must be met, all SHOULD criteria must be met OR be unmet with justification, and all SUGGESTED criteria must be met OR unmet (we want them considered at least). If you want to enter justification text as a generic comment, instead of being a rationale that the situation is acceptable, start the text block with '//' followed by a space. Feedback is welcome via the GitHub site as issues or pull requests There is also a mailing list for general discussion.

We gladly provide the information in several locales, however, if there is any conflict or inconsistency between the translations, the English version is the authoritative version.
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These are the Passing level criteria. You can also view the Silver or Gold level criteria.

Baseline Series: Baseline Level 1 Baseline Level 2 Baseline Level 3

        

 Basics 13/13 ●

  • General

    Note that other projects may use the same name.

    Self-hosted artist/composer metadata and image manager for Emby, Jellyfin, and Kodi

    Please use SPDX license expression format; examples include "Apache-2.0", "BSD-2-Clause", "BSD-3-Clause", "GPL-2.0+", "LGPL-3.0+", "MIT", and "(BSD-2-Clause OR Ruby)". Do not include single quotes or double quotes.
    If there is more than one language, list them as comma-separated values (spaces optional) and sort them from most to least used. If there is a long list, please list at least the first three most common ones. If there is no language (e.g., this is a documentation-only or test-only project), use the single character "-". Please use a conventional capitalization for each language, e.g., "JavaScript".
    The Common Platform Enumeration (CPE) is a structured naming scheme for information technology systems, software, and packages. It is used in a number of systems and databases when reporting vulnerabilities.
  • Basic project website content


    The project website MUST succinctly describe what the software does (what problem does it solve?). [description_good]
    This MUST be in language that potential users can understand (e.g., it uses minimal jargon).

    The README's opening paragraph states what Stillwater does and the problem it solves, in language aimed at self-hosted media-server users rather than developers: https://github.com/sydlexius/stillwater#readme

    It names the software (a self-hosted web app), what it operates on (artist and composer metadata for a music library), where the results go (artist.nfo files, or pushed to Emby/Jellyfin over their APIs), and the two problems it exists to solve: artists that other tools leave blank, and manual edits being overwritten the next time a server refreshes. The same description appears on the documentation site at https://sydlexius.github.io/stillwater/ and as the repository's one-line summary.



    The project website MUST provide information on how to: obtain, provide feedback (as bug reports or enhancements), and contribute to the software. [interact]

    All three are covered, reachable from the README:

    OBTAIN -- the README's "Quick start" section gives a working docker-compose file, and the documentation site carries full install guides for Docker, prebuilt binaries, Unraid Community Applications, and reverse-proxy setups: https://github.com/sydlexius/stillwater#quick-start and https://sydlexius.github.io/stillwater/

    FEEDBACK -- bug reports and enhancement requests go through GitHub Issues, with three templates (bug, feature, task) offered at https://github.com/sydlexius/stillwater/issues/new/choose . CONTRIBUTING.md documents which template to use and asks that larger ideas start with a short scope sketch in the issue body; questions are directed to the question label.

    CONTRIBUTE -- the README's "Contributing" section links CONTRIBUTING.md, which covers development environment setup, code style, and the pull-request workflow: https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md . Participants are asked to follow the Code of Conduct: https://github.com/sydlexius/stillwater/blob/main/CODE_OF_CONDUCT.md

    Security vulnerabilities are deliberately routed away from public issues to a private disclosure process documented in SECURITY.md.



    The information on how to contribute MUST explain the contribution process (e.g., are pull requests used?) (URL required) [contribution]
    We presume that projects on GitHub use issues and pull requests unless otherwise noted. This information can be short, e.g., stating that the project uses pull requests, an issue tracker, or posts to a mailing list (which one?)

    Non-trivial contribution file in repository: https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md.



    The information on how to contribute SHOULD include the requirements for acceptable contributions (e.g., a reference to any required coding standard). (URL required) [contribution_requirements]

    https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md#code-style

    CONTRIBUTING.md's "Code style" section states the requirements for an acceptable contribution and links the enforcing configuration:

    The "Pull request workflow" section adds the process requirements a contribution must satisfy: branch from main (direct commits are refused by branch protection), a conventional-commit prefix on the squash commit, and a passing local pre-push gate before pushing. These are enforced rather than advisory -- every PR must pass required CI checks including tests, a patch-coverage floor, CodeQL, and code review before it can merge.


  • FLOSS license


    The software produced by the project MUST be released as FLOSS. [floss_license]
    FLOSS is software released in a way that meets the Open Source Definition or Free Software Definition. Examples of such licenses include the CC0, MIT, BSD 2-clause, BSD 3-clause revised, Apache 2.0, Lesser GNU General Public License (LGPL), and the GNU General Public License (GPL). For our purposes, this means that the license MUST be: The software MAY also be licensed other ways (e.g., "GPLv2 or proprietary" is acceptable).

    The GPL-3.0 license is approved by the Open Source Initiative (OSI).



    It is SUGGESTED that any required license(s) for the software produced by the project be approved by the Open Source Initiative (OSI). [floss_license_osi]
    The OSI uses a rigorous approval process to determine which licenses are OSS.

    The GPL-3.0 license is approved by the Open Source Initiative (OSI).



    The project MUST post the license(s) of its results in a standard location in their source repository. (URL required) [license_location]
    One convention is posting the license as a top-level file named LICENSE or COPYING, which MAY be followed by an extension such as ".txt" or ".md". An alternative convention is to have a directory named LICENSES containing license file(s); these files are typically named as their SPDX license identifier followed by an appropriate file extension, as described in the REUSE Specification. Note that this criterion is only a requirement on the source repository. You do NOT need to include the license file when generating something from the source code (such as an executable, package, or container). For example, when generating an R package for the Comprehensive R Archive Network (CRAN), follow standard CRAN practice: if the license is a standard license, use the standard short license specification (to avoid installing yet another copy of the text) and list the LICENSE file in an exclusion file such as .Rbuildignore. Similarly, when creating a Debian package, you may put a link in the copyright file to the license text in /usr/share/common-licenses, and exclude the license file from the created package (e.g., by deleting the file after calling dh_auto_install). We encourage including machine-readable license information in generated formats where practical.

    Non-trivial license location file in repository: https://github.com/sydlexius/stillwater/blob/main/LICENSE.


  • Documentation


    The project MUST provide basic documentation for the software produced by the project. [documentation_basics]
    This documentation must be in some media (such as text or video) that includes: how to install it, how to start it, how to use it (possibly with a tutorial using examples), and how to use it securely (e.g., what to do and what not to do) if that is an appropriate topic for the software. The security documentation need not be long. The project MAY use hypertext links to non-project material as documentation. If the project does not produce software, choose "not applicable" (N/A).

    The documentation site at https://sydlexius.github.io/stillwater/ carries 75 pages covering installation through reference, organized by task:

    GETTING STARTED (8 pages) -- first-run setup walkthrough plus install guides for Docker Compose, prebuilt binary, and Unraid Community Applications, and connection guides for Emby, Jellyfin, and Lidarr: https://sydlexius.github.io/stillwater/getting-started/

    CORE CONCEPTS (10 pages) -- how the software actually behaves: metadata providers and per-field fallback, field locking, image handling, NFO write-back: https://sydlexius.github.io/stillwater/core-concepts/

    HOW-TO (27 pages) -- task-oriented guides for the operations a user actually performs.

    REFERENCE (8 pages) -- the CLI, environment variables, every setting by tab, the rules catalogue, providers, preferences, and UI labels: https://sydlexius.github.io/stillwater/reference/

    TROUBLESHOOTING, plus a documented REST API. The API is additionally covered by an OpenAPI specification and an executable Bruno collection in the repository, and make check-openapi gates the spec against the implementation so it cannot drift silently.

    The README gives the short version -- what the software does, a working docker-compose quick start, and the feature summary -- and links the full site: https://github.com/sydlexius/stillwater#readme

    Several reference pages are GENERATED from the source of truth rather than hand-maintained (the rules catalogue, the settings reference, and the doc anchors), so they cannot drift from the implementation.



    The project MUST provide reference documentation that describes the external interface (both input and output) of the software produced by the project. [documentation_interface]
    The documentation of an external interface explains to an end-user or developer how to use it. This would include its application program interface (API) if the software has one. If it is a library, document the major classes/types and methods/functions that can be called. If it is a web application, define its URL interface (often its REST interface). If it is a command-line interface, document the parameters and options it supports. In many cases it's best if most of this documentation is automatically generated, so that this documentation stays synchronized with the software as it changes, but this isn't required. The project MAY use hypertext links to non-project material as documentation. Documentation MAY be automatically generated (where practical this is often the best way to do so). Documentation of a REST interface may be generated using Swagger/OpenAPI. Code interface documentation MAY be generated using tools such as JSDoc (JavaScript), ESDoc (JavaScript), pydoc (Python), devtools (R), pkgdown (R), and Doxygen (many). Merely having comments in implementation code is not sufficient to satisfy this criterion; there needs to be an easy way to see the information without reading through all the source code. If the project does not produce software, choose "not applicable" (N/A).

    Every external interface the software exposes is documented, and most of the reference material is generated from the source of truth rather than maintained by hand.

    REST API. The project ships an OpenAPI specification covering 234 paths and 274 operations, describing request and response shapes for the whole /api/v1/ surface: https://github.com/sydlexius/stillwater/blob/main/internal/api/openapi.yaml . The API is documented on the documentation site at https://sydlexius.github.io/stillwater/api/

    The specification is verified against the implementation rather than trusted. make check-openapi compares the spec to the actual handlers, and it runs as a gate -- so a change to a request or response shape that is not reflected in the spec fails rather than silently leaving the documentation wrong. An executable Bruno collection additionally exercises the live API end to end in CI, which is a second, behavioural check that the documented interface is the one the server actually serves.

    COMMAND-LINE INTERFACE. Documented at https://sydlexius.github.io/stillwater/reference/cli/ , covering the flags and subcommands, including the operational one-shot passes (for example the pre-guard lock-damage dry-run and repair, with their approval-digest arguments).

    CONFIGURATION INTERFACE. Environment variables are documented at https://sydlexius.github.io/stillwater/reference/environment-variables/ , and every user-facing setting is catalogued by tab at https://sydlexius.github.io/stillwater/reference/settings-by-tab/ . The settings reference and the rules catalogue are GENERATED from the code that defines them, so they cannot drift from the implementation; a documentation-drift check runs in CI and fails when a shipped page no longer matches the code it describes.

    OTHER SURFACES. The provider set and their per-field behaviour are documented at https://sydlexius.github.io/stillwater/reference/providers/ , user preferences at .../reference/preferences/ , and UI labels at .../reference/ui-labels/ . The reference section runs to 8 pages, within a documentation site of 75 pages total.

    Interface documentation is therefore readable without opening the source, which is what this criterion asks: a consumer can learn the REST API, the CLI, and the configuration surface entirely from published pages.


  • Other


    The project sites (website, repository, and download URLs) MUST support HTTPS using TLS. [sites_https]
    This requires that the project home page URL and the version control repository URL begin with "https:", not "http:". You can get free certificates from Let's Encrypt. Projects MAY implement this criterion using (for example) GitHub pages, GitLab pages, or SourceForge project pages. If you support HTTP, we urge you to redirect the HTTP traffic to HTTPS.

    All three project URLs are HTTPS, verified live.

    Repository: https://github.com/sydlexius/stillwater -- 200 over TLS.

    Documentation site: https://sydlexius.github.io/stillwater/ -- 200 over TLS, served by GitHub Pages with its GitHub-managed certificate. Plain HTTP is not merely supported, it redirects: http://sydlexius.github.io/stillwater/ returns 301 to the HTTPS URL.

    Downloads: releases are served from GitHub over HTTPS at https://github.com/sydlexius/stillwater/releases , and container images from GitHub Container Registry (ghcr.io) over HTTPS. Release artifacts are additionally signed with Sigstore, so their provenance is verifiable independently of the transport.



    The project MUST have one or more mechanisms for discussion (including proposed changes and issues) that are searchable, allow messages and topics to be addressed by URL, enable new people to participate in some of the discussions, and do not require client-side installation of proprietary software. [discussion]
    Examples of acceptable mechanisms include archived mailing list(s), GitHub issue and pull request discussions, Bugzilla, Mantis, and Trac. Asynchronous discussion mechanisms (like IRC) are acceptable if they meet these criteria; make sure there is a URL-addressable archiving mechanism. Proprietary JavaScript, while discouraged, is permitted.

    GitHub supports discussions on issues and pull requests.



    The project SHOULD provide documentation in English and be able to accept bug reports and comments about code in English. [english]
    English is currently the lingua franca of computer technology; supporting English increases the number of different potential developers and reviewers worldwide. A project can meet this criterion even if its core developers' primary language is not English.

    The project is developed and documented entirely in English. The README, CONTRIBUTING.md, CODE_OF_CONDUCT.md, SECURITY.md, the full documentation site at https://sydlexius.github.io/stillwater/ , all in-repo design and reference docs, the three GitHub issue templates, code comments, and commit messages are all written in English. Issues, pull request discussion, and code review are conducted in English: https://github.com/sydlexius/stillwater/issues and https://github.com/sydlexius/stillwater/pulls. The application's own user interface is written in US English.



    The project MUST be maintained. [maintained]
    As a minimum, the project should attempt to respond to significant problem and vulnerability reports. A project that is actively pursuing a badge is probably maintained. All projects and people have limited resources, and typical projects must reject some proposed changes, so limited resources and proposal rejections do not by themselves indicate an unmaintained project.

    When a project knows that it will no longer be maintained, it should set this criterion to "Unmet" and use the appropriate mechanism(s) to indicate to others that it is not being maintained. For example, use “DEPRECATED” as the first heading of its README, add “DEPRECATED” near the beginning of its home page, add “DEPRECATED” to the beginning of its code repository project description, add a no-maintenance-intended badge in its README and/or home page, mark it as deprecated in any package repositories (e.g., npm deprecate), and/or use the code repository's marking system to archive it (e.g., GitHub's "archive" setting, GitLab’s "archived" marking, Gerrit's "readonly" status, or SourceForge’s "abandoned" project status). Additional discussion can be found here.

    The project is under active development, with the most recent commit today.

    COMMITS: 648 in the last 90 days, the latest on 2026-09-02.

    RELEASES: four stable releases in the past month -- v1.6.1 (2026-08-04), v1.6.2 (08-19), v1.6.3 (08-22), v1.6.4 (08-27) -- plus automated nightly pre-releases, the most recent on 2026-09-02. Release artifacts are signed with Sigstore.

    ISSUE ACTIVITY: 94 issues closed in the last 30 days, against 295 open. The open count reflects a tracked and milestoned backlog rather than neglect: issues are filed with a milestone and labels at creation, work is scheduled through release milestones, and defects found during review are captured as tracked issues rather than dropped.

    REVIEW AND CI: every change lands through a pull request with required CI checks (tests, a patch-coverage floor, CodeQL, lint, and a generated-file drift check) and required code review; direct commits to the default branch are refused by branch protection. Dependabot is configured for dependency updates.

    Repository activity is visible at https://github.com/sydlexius/stillwater/commits/main and https://github.com/sydlexius/stillwater/releases


 Change Control 9/9 ●

  • Public version-controlled source repository


    The project MUST have a version-controlled source repository that is publicly readable and has a URL. [repo_public]
    The URL MAY be the same as the project URL. The project MAY use private (non-public) branches in specific cases while the change is not publicly released (e.g., for fixing a vulnerability before it is revealed to the public).

    Repository on GitHub, which provides public git repositories with URLs.



    The project's source repository MUST track what changes were made, who made the changes, and when the changes were made. [repo_track]

    Repository on GitHub, which uses git. git can track the changes, who made them, and when they were made.



    To enable collaborative review, the project's source repository MUST include interim versions for review between releases; it MUST NOT include only final releases. [repo_interim]
    Projects MAY choose to omit specific interim versions from their public source repositories (e.g., ones that fix specific non-public security vulnerabilities, may never be publicly released, or include material that cannot be legally posted and are not in the final release).

    Met. The repository is the live development history, not a release drop.

    https://github.com/sydlexius/stillwater/commits/main -- 648 commits in the last 90 days, 160 merges to the default branch in the last 30 days alone, against four stable releases in that period. Every intermediate state between releases is public.

    Development happens in the open through pull requests, each reviewable before it lands: https://github.com/sydlexius/stillwater/pulls . Direct commits to the default branch are refused by branch protection, so no change reaches main without an interim reviewable state existing first. Review comments and their resolutions stay attached to the PR after merge.

    Automated nightly pre-releases are additionally published from the current development head, so an interim build is available to testers between stable releases: https://github.com/sydlexius/stillwater/releases

    Work in progress is also visible before any code exists, as milestoned and labelled issues: https://github.com/sydlexius/stillwater/issues



    It is SUGGESTED that common distributed version control software be used (e.g., git) for the project's source repository. [repo_distributed]
    Git is not specifically required and projects can use centralized version control software (such as subversion) with justification.

    Repository on GitHub, which uses git. git is distributed.


  • Unique version numbering


    The project results MUST have a unique version identifier for each release intended to be used by users. [version_unique]
    This MAY be met in a variety of ways including a commit IDs (such as git commit id or mercurial changeset id) or a version number (including version numbers that use semantic versioning or date-based schemes like YYYYMMDD).

    Met. Every release carries a unique semantic-version identifier.

    Stable releases are tagged vMAJOR.MINOR.PATCH -- v1.6.4 (2026-08-27), v1.6.3 (08-22), v1.6.2 (08-19), v1.6.1 (08-04): https://github.com/sydlexius/stillwater/releases

    Automated nightly builds are separately and unambiguously identified as nightly-YYYYMMDD and are marked as pre-releases, so they cannot be confused with a stable version.

    The identifier is not only a tag. It is compiled into the binary at build time via linker flags -- internal/version.Version, alongside the exact commit SHA and build date -- so a user can determine precisely which build they are running rather than inferring it from a filename. A CI guard in the release workflow specifically checks that the ldflags symbol path has not silently drifted, since a renamed package would otherwise leave the version unset without failing the build.

    Container images are tagged with the same version identifiers on GitHub Container Registry, and release artifacts are signed with Sigstore, so a given version is verifiable as well as identifiable.



    It is SUGGESTED that the Semantic Versioning (SemVer) or Calendar Versioning (CalVer) version numbering format be used for releases. It is SUGGESTED that those who use CalVer include a micro level value. [version_semver]
    Projects should generally prefer whatever format is expected by their users, e.g., because it is the normal format used by their ecosystem. Many ecosystems prefer SemVer, and SemVer is generally preferred for application programmer interfaces (APIs) and software development kits (SDKs). CalVer tends to be used by projects that are large, have an unusually large number of independently-developed dependencies, have a constantly-changing scope, or are time-sensitive. It is SUGGESTED that those who use CalVer include a micro level value, because including a micro level supports simultaneously-maintained branches whenever that becomes necessary. Other version numbering formats may be used as version numbers, including git commit IDs or mercurial changeset IDs, as long as they uniquely identify versions. However, some alternatives (such as git commit IDs) can cause problems as release identifiers, because users may not be able to easily determine if they are up-to-date. The version ID format may be unimportant for identifying software releases if all recipients only run the latest version (e.g., it is the code for a single website or internet service that is constantly updated via continuous delivery).


    It is SUGGESTED that projects identify each release within their version control system. For example, it is SUGGESTED that those using git identify each release using git tags. [version_tags]

    Met. Every release is identified by a git tag in the repository: https://github.com/sydlexius/stillwater/tags

    62 version tags are present, following vMAJOR.MINOR.PATCH -- for example v1.6.4, v1.6.3, v1.6.2, v1.6.1 -- with release-candidate tags (v1.6.0-rc0, v1.6.0-rc1) where a release was staged. The tags are ANNOTATED rather than lightweight, so each carries its own tagger and date.

    Nightly pre-release builds are tagged separately as nightly-YYYYMMDD, keeping them distinguishable from stable releases in the tag list as well as on the releases page.

    Each tag is what drives the release: the release workflow builds from the tag and stamps that same identifier into the binary via linker flags, so a tag, a GitHub release, and the version a running binary reports all refer to the same commit.


  • Release notes


    The project MUST provide, in each release, release notes that are a human-readable summary of major changes in that release to help users determine if they should upgrade and what the upgrade impact will be. The release notes MUST NOT be the raw output of a version control log (e.g., the "git log" command results are not release notes). Projects whose results are not intended for reuse in multiple locations (such as the software for a single website or service) AND employ continuous delivery MAY select "N/A". (URL required) [release_notes]
    The release notes MAY be implemented in a variety of ways. Many projects provide them in a file named "NEWS", "CHANGELOG", or "ChangeLog", optionally with extensions such as ".txt", ".md", or ".html". Historically the term "change log" meant a log of every change, but to meet these criteria what is needed is a human-readable summary. The release notes MAY instead be provided by version control system mechanisms such as the GitHub Releases workflow.

    https://github.com/sydlexius/stillwater/releases

    Every release ships hand-written release notes, structured as a plain-language summary of what changed and what it means for the user -- not a git log dump.

    The most recent, v1.6.4 (https://github.com/sydlexius/stillwater/releases/tag/v1.6.4), is representative. It opens with a one-sentence statement of what the release delivers, then a Highlights section explaining each significant change in terms of the user-visible symptom rather than the code: what went wrong, what it caused, and what now happens instead. Issue numbers are cited so a reader can follow any item to its full history.

    Upgrade impact is addressed directly where it exists. v1.6.4 shipped a repair for damage caused before an earlier guard existed, so the notes carry a dedicated section explaining that the repair is a deliberate one-time pass rather than something that runs at startup, instructing the user to stop the server and back up the database first, giving the exact commands for the dry-run preview and the approved repair, and explaining why the preview requires human judgment that no automatic test can substitute for.

    Earlier releases follow the same structure: v1.6.3, v1.6.2, v1.6.1. The project ships small, frequent, semver-correct releases, which keeps each set of notes specific enough to be read rather than skimmed.



    The release notes MUST identify every publicly known run-time vulnerability fixed in this release that already had a CVE assignment or similar when the release was created. This criterion may be marked as not applicable (N/A) if users typically cannot practically update the software themselves (e.g., as is often true for kernel updates). This criterion applies only to the project results, not to its dependencies. If there are no release notes or there have been no publicly known vulnerabilities, choose N/A. [release_notes_vulns]
    This criterion helps users determine if a given update will fix a vulnerability that is publicly known, to help users make an informed decision about updating. If users typically cannot practically update the software themselves on their computers, but must instead depend on one or more intermediaries to perform the update (as is often the case for a kernel and low-level software that is intertwined with a kernel), the project may choose "not applicable" (N/A) instead, since this additional information will not be helpful to those users. Similarly, a project may choose N/A if all recipients only run the latest version (e.g., it is the code for a single website or internet service that is constantly updated via continuous delivery). This criterion only applies to the project results, not its dependencies. Listing the vulnerabilities of all transitive dependencies of a project becomes unwieldy as dependencies increase and vary, and is unnecessary since tools that examine and track dependencies can do this in a more scalable way.

    N/A -- there have been no publicly known vulnerabilities in Stillwater itself.

    No CVE has been assigned against this project. Verified against NIST's CPE dictionary: neither the product nor the vendor name returns any entry, which is expected for a project with no published CVE. The repository has published zero GitHub security advisories: https://github.com/sydlexius/stillwater/security/advisories

    The criterion applies to the project's own results rather than its dependencies. Dependency advisories are handled separately and continuously -- Dependabot is configured, govulncheck runs in CI, and CodeQL scans every pull request -- but none of those are vulnerabilities in Stillwater's own code.

    A private disclosure process is in place for when one does arise, documented in SECURITY.md: https://github.com/sydlexius/stillwater/blob/main/SECURITY.md . Release notes are hand-written per release and would carry such a fix.


 Reporting 8/8 ●

  • Bug-reporting process


    The project MUST provide a process for users to submit bug reports (e.g., using an issue tracker or a mailing list). (URL required) [report_process]

    Non-trivial SECURITY[.md] file found file in repository: https://github.com/sydlexius/stillwater/blob/main/SECURITY.md. [osps_do_02_01]



    The project SHOULD use an issue tracker for tracking individual issues. [report_tracker]

    Met. The project uses GitHub Issues: https://github.com/sydlexius/stillwater/issues

    It is used as a working tracker rather than an inbox. Three issue templates route reports to the right shape (bug, feature, task): https://github.com/sydlexius/stillwater/issues/new/choose

    Issues are triaged at creation: every issue is assigned a milestone and labels when it is filed, drawn from 24 milestones and a 45-label taxonomy covering type (bug, enhancement, chore, technical-debt), scope, and affected area (images, rules, ui, providers, database, and so on). An unmilestoned issue does not appear in any release view, so the convention exists to keep work schedulable rather than invisible.

    Recent throughput: 94 issues closed in the last 30 days. Defects surfaced during code review are captured as tracked issues with the milestone of the work that surfaced them, rather than dropped or left in a comment thread.

    Security vulnerabilities are deliberately routed away from the public tracker to a private disclosure process: https://github.com/sydlexius/stillwater/blob/main/SECURITY.md



    The project MUST acknowledge a majority of bug reports submitted in the last 2-12 months (inclusive); the response need not include a fix. [report_responses]

    Met. Every bug report is triaged, and the great majority are resolved.

    Of the 400 issues labelled bug filed in the last 12 months, 394 carry a milestone -- 98.5%. Assigning a milestone and labels at filing time is the project's convention, and it is the acknowledgement: it places the report in a release view where it can be scheduled, rather than leaving it unrouted. The 6 without one are a rounding error, not a backlog of ignored reports.

    Resolution rate is high as well: two thirds of the bug reports in that window are already closed, and 94 issues of all types were closed in the last 30 days alone.

    Reports are also acted on rather than merely filed. Defects surfaced during code review are captured as tracked issues carrying the milestone of the work that surfaced them, and issues frequently accumulate investigation comments -- measurement results, refuted hypotheses, design decisions -- before any code is written.

    The tracker is public: https://github.com/sydlexius/stillwater/issues



    The project SHOULD respond to a majority (>50%) of enhancement requests in the last 2-12 months (inclusive). [enhancement_responses]
    The response MAY be 'no' or a discussion about its merits. The goal is simply that there be some response to some requests, which indicates that the project is still alive. For purposes of this criterion, projects need not count fake requests (e.g., from spammers or automated systems). If a project is no longer making enhancements, please select "unmet" and include the URL that makes this situation clear to users. If a project tends to be overwhelmed by the number of enhancement requests, please select "unmet" and explain.

    Met. Of the 400 issues labelled enhancement filed in the last 12 months, 391 carry a milestone -- 97.75% -- and 231 are already closed, so well over half have been both responded to and resolved.

    Enhancement requests are triaged at filing: a milestone and labels are assigned when the issue is created, which places the request in a release view where it can be scheduled or explicitly deferred, rather than left unrouted. An unmilestoned issue appears in no release view, so the convention exists precisely to keep proposals from going silently unanswered.

    The feature template asks that larger ideas open with a short scope sketch in the issue body so the design can be discussed before any code is written, and CONTRIBUTING.md directs contributors to raise a feature that way rather than starting with a pull request: https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md#suggesting-a-feature

    Proposals that are declined or reshaped are answered in the issue with the reasoning, and larger ones are decomposed into epics with tracked children rather than closed as too big.

    Tracker: https://github.com/sydlexius/stillwater/issues?q=is%3Aissue+label%3Aenhancement



    The project MUST have a publicly available archive for reports and responses for later searching. (URL required) [report_archive]

    https://github.com/sydlexius/stillwater/issues?q=is%%3Aissue

    All bug reports, enhancement requests, and their responses are permanently archived in the public GitHub issue tracker, open and closed alike, and are full-text searchable without an account. Closed issues are never deleted, so the reasoning behind a decision remains readable long after the work ships.

    Pull request discussion is archived alongside it and is equally searchable: https://github.com/sydlexius/stillwater/pulls?q=is%%3Apr . Review comments and their resolutions stay attached to the pull request after merge, so the argument that produced a change is recoverable from the change itself.

    The two are cross-linked in both directions -- pull requests reference the issues they address, and merged work appears in the issue's timeline -- so a search that lands on either finds the other.

    Releases carry hand-written notes citing the issue numbers they resolve, giving a third searchable path from a shipped version back to the discussion behind it: https://github.com/sydlexius/stillwater/releases


  • Vulnerability report process


    The project MUST publish the process for reporting vulnerabilities on the project site. (URL required) [vulnerability_report_process]
    Projects hosted on GitHub SHOULD consider enabling privately reporting a security vulnerability. Projects on GitLab SHOULD consider using its ability for privately reporting a vulnerability. Projects MAY identify a mailing address on https://PROJECTSITE/security, often in the form security@example.org. This vulnerability reporting process MAY be the same as its bug reporting process. Vulnerability reports MAY always be public, but many projects have a private vulnerability reporting mechanism.

    https://github.com/sydlexius/stillwater/blob/main/SECURITY.md

    SECURITY.md publishes the full reporting process, and GitHub surfaces it automatically in the repository's Security tab and on the "Report a vulnerability" flow.

    The policy states plainly that vulnerabilities must NOT be reported through public GitHub issues, and directs reporters to a private channel -- GitHub Security Advisories: https://github.com/sydlexius/stillwater/security/advisories/new -- so an issue can be triaged and a fix prepared before public disclosure.

    It specifies what a report should contain: a description of the vulnerability and its impact, steps to reproduce or a proof of concept, the affected versions, and a suggested fix if the reporter has one.

    It sets expectations both ways. An initial acknowledgement is promised within 72 hours of receipt; once confirmed, a fix is developed and released as soon as practical, typically within 14 days for critical issues.

    It also defines scope explicitly, which keeps a reporter from spending effort on something that will be declined. In scope: the application binary and Docker image, the REST API, authentication and session management, encryption of stored secrets, and file system operations. Out of scope: upstream dependency vulnerabilities (directed to the upstream project), issues requiring physical host access, and denial of service through expected resource usage.

    Supported versions are stated as well -- only the latest release receives security updates.



    If private vulnerability reports are supported, the project MUST include how to send the information in a way that is kept private. (URL required) [vulnerability_report_private]
    Examples include a private defect report submitted on the web using HTTPS (TLS) or an email encrypted using OpenPGP. If vulnerability reports are always public (so there are never private vulnerability reports), choose "not applicable" (N/A).

    https://github.com/sydlexius/stillwater/security/advisories/new

    Yes, private reporting is supported and is the required channel. SECURITY.md (https://github.com/sydlexius/stillwater/blob/main/SECURITY.md) states that vulnerabilities must NOT be reported through public GitHub issues, and directs reporters to GitHub Security Advisories at the URL above.

    That channel is private by construction: a draft advisory is visible only to the reporter and the repository maintainers until it is deliberately published, so the report, the discussion, and any proof-of-concept stay confidential while a fix is prepared. It requires no email exchange and no key management by the reporter, and it is reachable from the repository's Security tab as well as from the link in SECURITY.md.

    The policy also tells a reporter what to expect after sending: an initial acknowledgement within 72 hours, and a fix released as soon as practical -- typically within 14 days for critical issues -- before public disclosure.



    The project's initial response time for any vulnerability report received in the last 6 months MUST be less than or equal to 14 days. [vulnerability_report_response]
    If there have been no vulnerabilities reported in the last 6 months, choose "not applicable" (N/A).

    N/A -- no vulnerability reports have been received in the last 6 months, or at any point.

    The repository has published zero security advisories (https://github.com/sydlexius/stillwater/security/advisories) and no CVE has been assigned against the project, so there is no response time to measure.

    The commitment is published in advance for when one does arrive: SECURITY.md promises an initial acknowledgement within 72 hours of receipt -- well inside the 14-day bar -- with a fix released as soon as practical, typically within 14 days for critical issues. https://github.com/sydlexius/stillwater/blob/main/SECURITY.md

    Reports arrive through GitHub Security Advisories, which notifies maintainers directly rather than relying on a monitored mailbox: https://github.com/sydlexius/stillwater/security/advisories/new


 Quality 13/13 ●

  • Working build system


    If the software produced by the project requires building for use, the project MUST provide a working build system that can automatically rebuild the software from source code. [build]
    A build system determines what actions need to occur to rebuild the software (and in what order), and then performs those steps. For example, it can invoke a compiler to compile the source code. If an executable is created from source code, it must be possible to modify the project's source code and then generate an updated executable with those modifications. If the software produced by the project depends on external libraries, the build system does not need to build those external libraries. If there is no need to build anything to use the software after its source code is modified, select "not applicable" (N/A).

    The project builds from source with a single command.

    make build compiles the binary, and it is not a bare go build -- it depends on the templ and tailwind targets, so generated Go template code and the compiled stylesheet are regenerated first and cannot silently fall out of date with their sources. The Makefile documents 37 targets, discoverable via make help: https://github.com/sydlexius/stillwater/blob/main/Makefile

    Version information is injected at build time through linker flags (version, commit SHA, build date), so a binary reports exactly which source it came from.

    Container builds are equally reproducible from source: https://github.com/sydlexius/stillwater/tree/main/build/docker

    The build is verified continuously rather than assumed to work. Every pull request runs the full build in CI on a clean runner, and a required generated-file drift check fails the build if committed generated output does not match what regenerating from source produces -- so "it builds on the maintainer's machine" is not sufficient to merge. The release workflow builds the shipped artifacts from the tagged source in CI, and it carries its own guard against the version-injection symbol path drifting silently.

    Build prerequisites and the local development workflow are documented at https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md#development-environment



    It is SUGGESTED that common tools be used for building the software. [build_common_tools]
    For example, Maven, Ant, cmake, the autotools, make, rake (Ruby), or devtools (R).

    Non-trivial build file in repository: https://github.com/sydlexius/stillwater/blob/main/Makefile.



    The project SHOULD be buildable using only FLOSS tools. [build_floss_tools]

    Every tool required to build Stillwater from source is FLOSS.

    • Go toolchain (Go 1.27) -- BSD-3-Clause
    • templ (github.com/a-h/templ), the HTML templating generator -- MIT. Invoked as go tool templ, so it is pinned as a module dependency rather than an ambient install.
    • Tailwind CSS, for the stylesheet build -- MIT
    • Node.js, which Tailwind runs under -- MIT
    • GNU Make, driving the build -- GPL
    • git -- GPL-2.0
    • Docker or any OCI-compatible builder for container images; the Dockerfiles are plain and buildable with Podman or Buildah as well: https://github.com/sydlexius/stillwater/tree/main/build/docker

    No proprietary compiler, SDK, IDE, or paid service is needed at any point. A contributor on Linux, macOS, or Windows can clone the repository and run make build with nothing but the above.

    Development and CI tooling is FLOSS as well -- golangci-lint (GPL-3.0), govulncheck (BSD-3-Clause), and Go's built-in test and fuzz tooling. The CI workflows run on GitHub-hosted runners, but nothing in the build depends on GitHub specifically: the same Makefile targets CI invokes are the ones a contributor runs locally.

    Build prerequisites are documented at https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md#development-environment


  • Automated test suite


    The project MUST use at least one automated test suite that is publicly released as FLOSS (this test suite may be maintained as a separate FLOSS project). The project MUST clearly show or document how to run the test suite(s) (e.g., via a continuous integration (CI) script or via documentation in files such as BUILD.md, README.md, or CONTRIBUTING.md). [test]
    The project MAY use multiple automated test suites (e.g., one that runs quickly, vs. another that is more thorough but requires special equipment). There are many test frameworks and test support systems available, including Selenium (web browser automation), Junit (JVM, Java), RUnit (R), testthat (R).

    The project has multiple automated test suites, all built on FLOSS tooling, and how to run them is documented.

    HOW TO RUN -- CONTRIBUTING.md's "Running tests" section: https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md#running-tests

    go test -race ./...
    # or, equivalent
    make test
    

    THE SUITES:

    • Go unit and integration tests -- 754 test files across the module, using Go's standard testing package (BSD-3-Clause). Integration tests run against a real SQLite database via modernc.org/sqlite, not a mock.
    • Native Go fuzzing across roughly 15 packages, with a CI-enforced matrix so a new fuzz target cannot be added without being exercised.
    • Accessibility tests -- Playwright (Apache-2.0) driving axe-core (MPL-2.0) against both Chromium and Firefox.
    • API tests -- an executable Bruno collection (MIT), exercised end to end by make bruno-ci, which builds the binary, starts an ephemeral server, and runs the collection against it.
    • Responsive-layout and load test suites under the same tests/ tree.

    Every suite is FLOSS and none requires a paid service.

    The suites are RUN, not merely present. Every pull request runs them in CI as required status checks, so a change cannot land while they fail: https://github.com/sydlexius/stillwater/blob/main/.github/workflows/ci.yml -- and a patch-coverage floor is itself a required check, so new code arriving without tests fails the build rather than slipping through quietly.



    A test suite SHOULD be invocable in a standard way for that language. [test_invocation]
    For example, "make check", "mvn test", or "rake test" (Ruby).

    The test suite is invoked the standard way for Go:

    go test ./...
    

    with the race detector, which is how this project runs it:

    go test -race ./...
    

    No wrapper, no bespoke runner, no environment fixture required -- a contributor who knows Go needs no project-specific knowledge to run the tests. make test is provided as a convenience alias for exactly that command, not as a substitute for it, and CONTRIBUTING.md presents the two as equivalent: https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md#running-tests

    The auxiliary suites follow their own ecosystems' conventions in the same way -- Go's built-in fuzzing via go test -fuzz, Playwright through its standard runner, and the Bruno API collection through the Bruno CLI. Each is wrapped in a named Makefile target for discoverability (make help lists them), but every one remains runnable directly with its native command.



    It is SUGGESTED that the test suite cover most (or ideally all) the code branches, input fields, and functionality. [test_most]

    Coverage is enforced rather than aspirational, at two levels.

    PER-PACKAGE FLOORS. 54 packages carry an individual coverage floor, checked as a required CI status. Floors range from 58% to 100%, with 31 packages at 80% or above; the exact figures are committed at https://github.com/sydlexius/stillwater/blob/main/testdata/coverage-floor.json and mirrored in https://github.com/sydlexius/stillwater/blob/main/codecov.yml so each package is an independent check. A package that regresses below its own floor fails, so coverage cannot quietly erode in one corner while the overall number holds steady.

    PATCH COVERAGE. New and changed code must reach 78%, as a required check. This is the load-bearing one: it means a change arriving without tests fails the build rather than merging and diluting the average later.

    BEYOND LINE COVERAGE. The project treats line coverage as necessary but not sufficient, and tests for behaviour rather than for the metric:

    • Native Go fuzzing across roughly 15 packages exercises input fields with generated input, and a CI-enforced matrix means a fuzz target cannot be added without being run.
    • New tests guarding a bug fix are required to be shown failing without the fix -- revert it, confirm red, restore, confirm green -- so a test that guards nothing is caught before it lands.
    • Accessibility tests run real axe-core through Playwright against both Chromium and Firefox, against a live page rather than static analysis.
    • An executable Bruno collection exercises the REST API end to end against a real server started for the run.
    • Integration tests use a real SQLite database rather than mocks.

    754 test files across the module: https://github.com/sydlexius/stillwater/blob/main/.github/workflows/ci.yml



    It is SUGGESTED that the project implement continuous integration (where new or changed code is frequently integrated into a central code repository and automated tests are run on the result). [test_continuous_integration]

    The project runs continuous integration on GitHub Actions, across 22 workflows: https://github.com/sydlexius/stillwater/tree/main/.github/workflows

    FREQUENT INTEGRATION. 648 commits in the last 90 days and 160 merges to the default branch in the last 30, against four stable releases in that period. Every change lands through a pull request; direct commits to the default branch are refused by branch protection, so nothing reaches the trunk without passing through CI first.

    TESTS RUN ON EVERY CHANGE, AND BLOCK. The main workflow (ci.yml) runs the full Go suite with the race detector, lint, a whole-module build, and a generated-file drift check that fails if committed generated output does not match a fresh regeneration. These are required status checks, so a red result stops the change rather than merely reporting.

    SPECIALIZED WORKFLOWS beyond the main suite:

    • bruno-ci.yml -- builds the binary, starts an ephemeral server, and runs the REST API collection against it
    • fuzz.yml -- native Go fuzzing, with a matrix check so a new fuzz target cannot be added without being run
    • codeql.yml -- static analysis on every pull request
    • mutation.yml -- mutation testing, to check the tests themselves have teeth
    • gate.yml -- provider-failure smoke tests and gate-invariant enforcement
    • docs-drift.yml -- fails when the documentation no longer matches the code it describes
    • scorecard.yml -- OpenSSF Scorecard on a schedule
    • nightly.yml / release-nightly.yml -- a nightly build published as a pre-release, so an interim artifact exists between stable releases

    A patch-coverage floor is itself a required check, so new code arriving without tests fails rather than landing quietly. All GitHub Actions are pinned to commit SHAs rather than floating tags, and workflow tokens follow least privilege -- both verified independently by OpenSSF Scorecard, which scores this project 10/10 on CI-Tests, Token-Permissions, and Dangerous-Workflow: https://securityscorecards.dev/viewer/?uri=github.com/sydlexius/stillwater


  • New functionality testing


    The project MUST have a general policy (formal or not) that as major new functionality is added to the software produced by the project, tests of that functionality should be added to an automated test suite. [test_policy]
    As long as a policy is in place, even by word of mouth, that says developers should add tests to the automated test suite for major new functionality, select "Met."

    Met, and the policy is mechanically enforced rather than left to discipline.

    THE POLICY. New and changed code must reach 78% patch coverage. This is a REQUIRED status check, so a change that adds functionality without tests fails and cannot land -- the policy is not an intention a reviewer has to remember to raise. Configuration: https://github.com/sydlexius/stillwater/blob/main/codecov.yml

    Per-package floors back it up: 54 packages each carry their own committed minimum, checked independently, so coverage cannot erode in one area while the overall figure holds steady. https://github.com/sydlexius/stillwater/blob/main/testdata/coverage-floor.json

    WHAT THE POLICY ASKS FOR BEYOND A NUMBER. The project treats coverage as necessary but not sufficient, and documents that in its contributor guidance:

    • A test written for a bug fix must be shown to FAIL without the fix -- revert it, confirm red, restore, confirm green -- so a test that guards nothing is caught before it lands rather than providing false assurance.
    • Tests must assert their own preconditions, so a fixture that silently stops exercising the intended path fails instead of passing vacuously.
    • Tests must not depend on the developer's environment; a dependency on an external tool must be stubbed, because a green local run does not prove a test will pass on a bare CI runner.
    • Concurrent code is tested under the race detector.
    • Mutation testing runs in CI against the test suite itself, checking that the tests actually detect changed behaviour.

    Contributor-facing documentation: https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md and the per-package testing guidance in https://github.com/sydlexius/stillwater/tree/main/.github/instructions

    The result is visible in the history: 754 test files across the module, and features routinely ship in the same pull request as the tests that exercise them.



    The project MUST have evidence that the test_policy for adding tests has been adhered to in the most recent major changes to the software produced by the project. [tests_are_added]
    Major functionality would typically be mentioned in the release notes. Perfection is not required, merely evidence that tests are typically being added in practice to the automated test suite when new major functionality is added to the software produced by the project.

    The four most recently merged pull requests each shipped tests with the functionality, and the pattern holds because CI enforces it rather than relying on discipline.

    • #3191 (feat, new enumeration primitive) -- 2 of 3 changed files were tests. Patch coverage 100%.
    • #3192 (fix, delete-intent recorded on an API path, plus a shared test helper) -- 3 of 6 files tests. Patch coverage 100%.
    • #3193 (fix, new operator warning on the push path) -- new dedicated test file alongside the feature. Patch coverage 100%.
    • #3195 (guards for the ordering properties #3193 depends on) -- 3 of 3 files tests, an entire PR of tests deliberately split out to keep it reviewable.

    https://github.com/sydlexius/stillwater/pulls?q=is%3Apr+is%3Amerged

    The evidence goes past file counts. These changes were reviewed adversarially, and the review found and rejected tests that passed for reasons unrelated to what they claimed -- a test whose assertion held whether or not the fix was present, an assertion anchored so that real network latency would mask the defect it existed to catch, a comment claiming a drift check the code could not perform. Each was corrected before the change landed, and each new guard was demonstrated red without its fix and green with it.

    #3195 is the clearest illustration of the policy in practice: it exists solely because the ordering properties a merged fix depends on could still be broken silently. Six mutations reproducing prior defects were applied one at a time and each confirmed to make the right test fail. Nothing in it adds functionality; it exists so the functionality cannot regress unnoticed.

    Enforcement rather than intention: patch coverage at 78% is a required status check, and 54 packages carry individual coverage floors, so a change adding functionality without tests fails the build.



    It is SUGGESTED that this policy on adding tests (see test_policy) be documented in the instructions for change proposals. [tests_documented_added]
    However, even an informal rule is acceptable as long as the tests are being added in practice.

    The expectation is stated in the contributor instructions and in the pull request template, and it is enforced mechanically rather than left to discipline.

    CONTRIBUTING.md states that new or changed functionality is expected to arrive with tests in the same pull request, and that this is enforced: patch coverage at 78% is a required status check, so a change adding functionality without tests fails rather than landing. https://github.com/sydlexius/stillwater/blob/main/CONTRIBUTING.md

    The pull request template's test plan asks the author to confirm that new or changed functionality is covered by tests in that pull request: https://github.com/sydlexius/stillwater/blob/main/.github/pull_request_template.md

    Per-package testing standards live in https://github.com/sydlexius/stillwater/tree/main/.github/instructions and apply automatically to any *_test.go file under review, covering what a good test looks like in this codebase rather than only that one should exist.

    The documented standard goes past a coverage percentage. A test guarding a bug fix is expected to be shown failing without the fix -- revert it, confirm red, restore, confirm green -- so a test that guards nothing is caught before it lands. Tests are expected to assert their own preconditions, so a fixture that stops exercising the intended path fails rather than passing vacuously.

    Enforcement backs the documentation: 54 packages carry individual committed coverage floors (https://github.com/sydlexius/stillwater/blob/main/testdata/coverage-floor.json), each checked independently, and mutation testing runs in CI against the test suite itself.


  • Warning flags


    The project MUST enable one or more compiler warning flags, a "safe" language mode, or use a separate "linter" tool to look for code quality errors or common simple mistakes, if there is at least one FLOSS tool that can implement this criterion in the selected language. [warnings]
    Examples of compiler warning flags include gcc/clang "-Wall". Examples of a "safe" language mode include JavaScript "use strict" and perl5's "use warnings". A separate "linter" tool is simply a tool that examines the source code to look for code quality errors or common simple mistakes. These are typically enabled within the source code or build instructions.

    The project runs golangci-lint (GPL-3.0, FLOSS) with 23 linters enabled, configured at https://github.com/sydlexius/stillwater/blob/main/.golangci.yml

    The enabled set is deliberately broader than the default:

    • Correctness: errcheck, errorlint, nilerr, exhaustive, sqlclosecheck, bodyclose, contextcheck, noctx, musttag
    • Security: gosec
    • Static analysis: govet, staticcheck, unused, unparam, unconvert, wastedassign
    • Quality and idiom: gocritic (with style and performance checks enabled beyond its defaults), revive, gocognit for cognitive complexity, prealloc, usestdlibvars, misspell
    • nolintlint, which polices the suppressions themselves so a //nolint cannot be added without a reason

    Suppressions are specific and carry their rationale inline rather than being blanket disables -- for example gosec G104, G117 and G120 are each excluded with a written reason naming why the rule misfires here.

    Beyond the linter: Go's compiler and go vet run over the whole module on every change, and CodeQL performs static analysis on every pull request. Hadolint lints the Dockerfiles, actionlint the GitHub Actions workflows, and stylelint the CSS.

    These are enforced, not advisory. make lint is documented in CONTRIBUTING.md, the pre-commit hook runs golangci-lint on staged packages so a failing change cannot be committed, and lint is a required CI status check. A cognitive-complexity violation blocked a commit during recent work and had to be resolved by extraction rather than suppressed, which is the enforcement working as intended.

    OpenSSF Scorecard independently scores this project 10/10 on its SAST check: https://securityscorecards.dev/viewer/?uri=github.com/sydlexius/stillwater



    The project MUST address warnings. [warnings_fixed]
    These are the warnings identified by the implementation of the warnings criterion. The project should fix warnings or mark them in the source code as false positives. Ideally there would be no warnings, but a project MAY accept some warnings (typically less than 1 warning per 100 lines or less than 10 warnings).

    The codebase is clean: golangci-lint run ./... across the whole module reports 0 issues, measured against current main.

    Warnings are addressed rather than accumulated, because they cannot accumulate. Lint is a required CI status check, so a change introducing a warning fails and does not land, and a pre-commit hook runs golangci-lint on staged packages so a failing change cannot be committed locally either. The gate is not advisory: during recent work a cognitive-complexity violation blocked a commit and had to be resolved by extracting functions, not by suppressing the check.

    Where a rule genuinely misfires, the suppression is specific and carries its reasoning inline rather than being a blanket disable. Every one of the 443 //nolint directives in the codebase names both the specific linter it suppresses and a written reason, for example:

    defer rows.Close() //nolint:errcheck // Close error not actionable on cleanup
    

    That consistency is itself enforced: nolintlint is among the enabled linters, so a suppression cannot be added without naming its linter and giving an explanation. A directive that suppresses nothing is also flagged, which keeps stale suppressions from surviving the code they were written for.

    The three project-level exclusions in .golangci.yml (gosec G104, G117, G120) each carry a written rationale naming why the rule misfires in this codebase, rather than being disabled silently.

    Configuration: https://github.com/sydlexius/stillwater/blob/main/.golangci.yml



    It is SUGGESTED that projects be maximally strict with warnings in the software produced by the project, where practical. [warnings_strict]
    Some warnings cannot be effectively enabled on some projects. What is needed is evidence that the project is striving to enable warning flags where it can, so that errors are detected early.

    The configuration is deliberately stricter than golangci-lint's defaults, and every relaxation is individually justified in the file rather than applied as a blanket disable.

    STRICTER THAN DEFAULT. 23 linters are enabled, well beyond the default set, including several most projects leave off: contextcheck, exhaustive, musttag, nilerr, noctx, sqlclosecheck, unparam, wastedassign, and gocognit for cognitive complexity. gocritic runs with its style and performance tag bundles enabled on top of its defaults.

    RELAXATIONS ARE ARGUED, NOT ASSUMED. Each disabled gocritic check carries a written rationale in .golangci.yml explaining why it does not fit this codebase -- for example octalLiteral is off because the project uses 0o-prefixed file modes and the check also objects to a literal 0; commentedOutCode is off because it false-positives on Go's semantic // Deprecated: markers. The gocritic diagnostic tag is omitted with its reasoning stated: every check in it overlaps something govet or staticcheck already reports, so enabling it would produce duplicate findings rather than new ones. The three gosec exclusions (G104, G117, G120) each name the specific misfire.

    That is the evidence the criterion asks for: the decisions are visible and defensible, so a future contributor can re-litigate any of them against the reasoning rather than guessing why a check is off.

    SUPPRESSIONS ARE POLICED. nolintlint is enabled, so an inline suppression cannot be added without naming its linter and giving a reason, and a directive that suppresses nothing is flagged. All 443 //nolint directives in the codebase carry both.

    BEYOND THE LINTER. The whole module is built and vetted on every change; CodeQL analyses every pull request; the race detector runs over the suite in CI; mutation testing checks the tests themselves detect changed behaviour; Hadolint, actionlint and stylelint cover the Dockerfiles, workflows and CSS. Lint is a required status check and a pre-commit hook runs it on staged packages, so strictness is enforced at both ends.

    Current result: golangci-lint run ./... reports 0 issues across the module.

    https://github.com/sydlexius/stillwater/blob/main/.golangci.yml


 Security 14/16 ●

  • Secure development knowledge


    The project MUST have at least one primary developer who knows how to design secure software. (See ‘details’ for the exact requirements.) [know_secure_design]
    This requires understanding the following design principles, including the 8 principles from Saltzer and Schroeder:
    • economy of mechanism (keep the design as simple and small as practical, e.g., by adopting sweeping simplifications)
    • fail-safe defaults (access decisions should deny by default, and projects' installation should be secure by default)
    • complete mediation (every access that might be limited must be checked for authority and be non-bypassable)
    • open design (security mechanisms should not depend on attacker ignorance of its design, but instead on more easily protected and changed information like keys and passwords)
    • separation of privilege (ideally, access to important objects should depend on more than one condition, so that defeating one protection system won't enable complete access. E.G., multi-factor authentication, such as requiring both a password and a hardware token, is stronger than single-factor authentication)
    • least privilege (processes should operate with the least privilege necessary)
    • least common mechanism (the design should minimize the mechanisms common to more than one user and depended on by all users, e.g., directories for temporary files)
    • psychological acceptability (the human interface must be designed for ease of use - designing for "least astonishment" can help)
    • limited attack surface (the attack surface - the set of the different points where an attacker can try to enter or extract data - should be limited)
    • input validation with allowlists (inputs should typically be checked to determine if they are valid before they are accepted; this validation should use allowlists (which only accept known-good values), not denylists (which attempt to list known-bad values)).
    A "primary developer" in a project is anyone who is familiar with the project's code base, is comfortable making changes to it, and is acknowledged as such by most other participants in the project. A primary developer would typically make a number of contributions over the past year (via code, documentation, or answering questions). Developers would typically be considered primary developers if they initiated the project (and have not left the project more than three years ago), have the option of receiving information on a private vulnerability reporting channel (if there is one), can accept commits on behalf of the project, or perform final releases of the project software. If there is only one developer, that individual is the primary developer. Many books and courses are available to help you understand how to develop more secure software and discuss design. For example, the Secure Software Development Fundamentals course is a free set of three courses that explain how to develop more secure software (it's free if you audit it; for an extra fee you can earn a certificate to prove you learned the material).

    ...pending completion of the OpenSSF Secure Software Development Fundamentals course.

    The project has a single primary developer, who initiated it, accepts all commits, performs releases, and receives private vulnerability reports. That developer has not completed formal secure-design training and does not claim familiarity with the Saltzer and Schroeder principles by name. Since this criterion asks what a developer understands rather than what the codebase contains, answering Met on the strength of the implementation would be asserting the knowledge rather than evidencing it. It is recorded honestly as unmet.

    The plan to meet it is the course this criterion names -- the OpenSSF Secure Software Development Fundamentals, audited free -- which also addresses know_common_errors.

    For context, several of the principles are applied in the codebase today, though a number of them were arrived at through adversarial review and automated analysis rather than from first principles:

    • Fail-safe defaults: destructive checks are written as positive allowlists rather than negated safe-lists, and an image-repair path that cannot positively identify the slot it means to overwrite adds rather than overwrites, on the reasoning that one extra copy is recoverable and a destroyed image is not.
    • Complete mediation: authentication, CSRF protection and rate limiting are router middleware, so a new endpoint is covered by construction rather than by the author remembering.
    • Open design: provider API keys are encrypted at rest with AES-256-GCM, the key is a 0600 file rather than an environment value, and the whole design is public under GPL-3.0.
    • Least privilege: CI workflow tokens are scoped per job, since job-level permissions replace rather than extend workflow-level ones, and checkouts run with persist-credentials disabled.
    • Input validation with allowlists: path inputs are validated against an allowlist of a single path element rather than a denylist of traversal forms.
    • Limited attack surface: SECURITY.md defines scope explicitly; the application is self-hosted with no outbound telemetry and a minimal vendored JavaScript footprint rather than an npm dependency tree.

    External analysis supports the implementation -- CodeQL on every pull request, gosec among 23 enabled linters, govulncheck in CI, Sigstore-signed releases, and an OpenSSF Scorecard of 9.0/10 -- but external analysis is not the developer knowledge this criterion asks about, so the criterion is answered on its own terms.



    At least one of the project's primary developers MUST know of common kinds of errors that lead to vulnerabilities in this kind of software, as well as at least one method to counter or mitigate each of them. [know_common_errors]
    Examples (depending on the type of software) include SQL injection, OS injection, classic buffer overflow, cross-site scripting, missing authentication, and missing authorization. See the CWE/SANS top 25 or OWASP Top 10 for commonly used lists. Many books and courses are available to help you understand how to develop more secure software and discuss common implementation errors that lead to vulnerabilities. For example, the Secure Software Development Fundamentals course is a free set of three courses that explain how to develop more secure software (it's free if you audit it; for an extra fee you can earn a certificate to prove you learned the material).

    ...pending completion of the OpenSSF Secure Software Development Fundamentals course.

    The project is developed by a single primary developer, who has not completed formal secure-development training, and this criterion asks what a developer knows rather than what the codebase contains. Answering Met on the strength of the implemented mitigations would be asserting knowledge rather than evidencing it, so it is recorded honestly as unmet.

    The plan to meet it is the course this criterion names -- the OpenSSF Secure Software Development Fundamentals, audited free -- which also addresses know_secure_design.

    For context, mitigations for the common classes are implemented and enforced in the project today, several of them structurally rather than per-site: authentication, CSRF protection, and rate limiting applied as router middleware so a new endpoint is covered by construction; provider API keys encrypted at rest with AES-256-GCM under a 0600 key file rather than an environment value; input validated at the API boundary, with path inputs checked against an allowlist of one path element rather than a denylist of traversal forms; parameterized SQL throughout.

    These are backed by automated checks rather than vigilance: CodeQL on every pull request, gosec among 23 enabled linters, govulncheck in CI, and Dependabot for dependency advisories. That is why the codebase scores well on external analysis -- OpenSSF Scorecard rates it 9.0/10 -- but external analysis is not the same as the developer knowledge this criterion asks about, and the criterion is answered on its own terms.


  • Use basic good cryptographic practices

    Note that some software does not need to use cryptographic mechanisms. If your project produces software that (1) includes, activates, or enables encryption functionality, and (2) might be released from the United States (US) to outside the US or to a non-US-citizen, you may be legally required to take a few extra steps. Typically this just involves sending an email. For more information, see the encryption section of Understanding Open Source Technology & US Export Controls.

    The software produced by the project MUST use, by default, only cryptographic protocols and algorithms that are publicly published and reviewed by experts (if cryptographic protocols and algorithms are used). [crypto_published]
    These cryptographic criteria do not always apply because some software has no need to directly use cryptographic capabilities.

    Every cryptographic algorithm the project uses is publicly published, standardised and expert-reviewed, and all of them come from Go's standard library or the Go project's supplementary x/crypto module. Nothing is home-grown.

    • Secrets at rest: AES-256-GCM (FIPS 197 for AES, NIST SP 800-38D for GCM) via crypto/aes and crypto/cipher, used to encrypt provider API keys. Implementation: https://github.com/sydlexius/stillwater/blob/main/internal/encryption/encryption.go
    • Password storage: bcrypt (Provos and Mazieres, USENIX 1999) via golang.org/x/crypto/bcrypt, at the library's default cost. Passwords are pre-hashed before bcrypt to avoid its 72-byte input truncation.
    • Transport: TLS via crypto/tls, with certificate handling through crypto/x509.
    • Signatures and keys: ECDSA (crypto/ecdsa with crypto/elliptic) and RSA (crypto/rsa), as required for OIDC token verification.
    • Hashing and message authentication: SHA-256 (FIPS 180-4) via crypto/sha256, and HMAC (RFC 2104, FIPS 198-1) via crypto/hmac.
    • Randomness: crypto/rand, the cryptographically secure source, rather than math/rand.
    • Constant-time comparison: crypto/subtle, so secret comparisons do not leak by timing.

    No custom cipher, construction, mode, or key-derivation scheme is defined anywhere in the project. Where a cryptographic operation is needed, the standard library primitive is used directly.

    Supporting controls: the encryption key is stored as a file with 0600 permissions rather than an environment variable, so it does not appear in a process listing or in inherited environments. gosec is among the 23 linters enabled in CI, CodeQL analyses every pull request, and govulncheck runs against the dependency graph -- so a weak or deprecated primitive would be flagged rather than lingering unnoticed.



    If the software produced by the project is an application or library, and its primary purpose is not to implement cryptography, then it SHOULD only call on software specifically designed to implement cryptographic functions; it SHOULD NOT re-implement its own. [crypto_call]

    Stillwater is a metadata and image manager for self-hosted media servers; implementing cryptography is not its purpose, and it does not attempt to.

    Every cryptographic operation calls into software written specifically to implement it -- Go's standard library (crypto/aes, crypto/cipher, crypto/tls, crypto/x509, crypto/sha256, crypto/hmac, crypto/rand, crypto/subtle, crypto/ecdsa, crypto/rsa) and the Go project's supplementary golang.org/x/crypto/bcrypt.

    No cipher, mode, hash, MAC, key-derivation function, or random-number generator is implemented in this codebase. The encryption path composes standard primitives in the documented way -- aes.NewCipher into cipher.NewGCM, with the nonce drawn from crypto/rand -- rather than assembling anything bespoke: https://github.com/sydlexius/stillwater/blob/main/internal/encryption/encryption.go

    Where the project had a choice between using a primitive correctly and working around one of its properties, it used the primitive: passwords are pre-hashed before bcrypt to avoid its 72-byte input truncation, rather than substituting a hand-rolled scheme.

    This is enforced as well as intended. gosec is among the 23 linters enabled in CI and flags weak or misused cryptographic primitives, CodeQL analyses every pull request, and govulncheck runs against the dependency graph -- so an advisory affecting x/crypto surfaces as a CI finding rather than going unnoticed. Two such advisories were resolved this way by upgrading the dependency rather than patching around it.



    All functionality in the software produced by the project that depends on cryptography MUST be implementable using FLOSS. [crypto_floss]

    Every cryptographic dependency is FLOSS, and none is optional or substitutable for a proprietary alternative.

    • Go standard library crypto (crypto/aes, crypto/cipher, crypto/tls, crypto/x509, crypto/sha256, crypto/hmac, crypto/rand, crypto/subtle, crypto/ecdsa, crypto/rsa) -- BSD-3-Clause.
    • golang.org/x/crypto/bcrypt, from the Go project -- BSD-3-Clause.

    Both ship with, or are fetched as, ordinary module dependencies. There is no proprietary cryptographic library, no hardware security module requirement, no vendor SDK, and no paid service anywhere in the cryptographic path.

    The algorithms themselves are open standards with multiple independent FLOSS implementations, so nothing here is tied to a single provider: AES (FIPS 197) and GCM (NIST SP 800-38D), bcrypt (published by Provos and Mazieres, USENIX 1999), TLS and X.509 (IETF), SHA-256 (FIPS 180-4), HMAC (RFC 2104), ECDSA and RSA. A reimplementation against any conforming FLOSS crypto library would interoperate with data this project has already written.

    The build reflects that: the whole project builds from source with FLOSS tooling only (Go, templ, Tailwind, Node, Make, git), so a user can compile and run every cryptographic path themselves without acquiring anything proprietary. Encrypted data is readable by any AES-256-GCM implementation given the key, and the key is a plain file rather than something sealed to a proprietary keystore -- so a user is not locked in by the encryption at rest.

    The project is licensed GPL-3.0: https://github.com/sydlexius/stillwater/blob/main/LICENSE



    The security mechanisms within the software produced by the project MUST use default keylengths that at least meet the NIST minimum requirements through the year 2030 (as stated in 2012). It MUST be possible to configure the software so that smaller keylengths are completely disabled. [crypto_keylength]
    These minimum bitlengths are: symmetric key 112, factoring modulus 2048, discrete logarithm key 224, discrete logarithmic group 2048, elliptic curve 224, and hash 224 (password hashing is not covered by this bitlength, more information on password hashing can be found in the crypto_password_storage criterion). See https://www.keylength.com for a comparison of keylength recommendations from various organizations. The software MAY allow smaller keylengths in some configurations (ideally it would not, since this allows downgrade attacks, but shorter keylengths are sometimes necessary for interoperability).

    Every default exceeds the stated 2030 minimums, and shorter lengths are not configurable -- they are rejected outright rather than merely discouraged.

    SYMMETRIC (minimum 112). AES-256, so 256 bits. The key length is not a setting: the encryptor requires exactly 32 bytes and returns an error otherwise, so a shorter key cannot be configured, supplied, or fallen back to. A generated key is drawn from crypto/rand at the full 32 bytes. https://github.com/sydlexius/stillwater/blob/main/internal/encryption/encryption.go

    ELLIPTIC CURVE (minimum 224). P-256, so 256 bits, used for the ACME account and certificate keys. The curve is fixed in code rather than exposed as an option.

    TRANSPORT. The HTTPS listener sets MinVersion: tls.VersionTLS13, which is stronger than this criterion requires: TLS 1.3 removes the weak cipher suites and short-key key-exchange groups entirely, so a downgrade to a smaller keylength is not reachable through negotiation. Older protocol versions are refused rather than deprioritised.

    FACTORING MODULUS AND DISCRETE LOG (minimum 2048). The project does not generate RSA or finite-field Diffie-Hellman keys of its own. crypto/rsa appears only for verifying OIDC provider tokens, where the key is the identity provider's, and crypto/x509 for certificate handling. Where the project chooses, it chooses ECDSA P-256.

    HASH (minimum 224). SHA-256, so 256 bits, via crypto/sha256. No shorter digest is used anywhere; SHA-1 and MD5 do not appear in the cryptographic path.

    CONFIGURABILITY OF SMALLER LENGTHS. There is none, by design. No setting, environment variable, or flag lowers any of the above. The AES key length is enforced with an explicit error, the curve and hash are compile-time choices, and the TLS floor is set at the listener. Since the project has no interoperability requirement that would justify a weaker option, the downgrade path this criterion permits simply does not exist.

    gosec, which flags weak cryptographic parameters, is among the 23 linters enabled in CI, and CodeQL analyses every pull request.



    The default security mechanisms within the software produced by the project MUST NOT depend on broken cryptographic algorithms (e.g., MD4, MD5, single DES, RC4, Dual_EC_DRBG), or use cipher modes that are inappropriate to the context, unless they are necessary to implement an interoperable protocol (where the protocol implemented is the most recent version of that standard broadly supported by the network ecosystem, that ecosystem requires the use of such an algorithm or mode, and that ecosystem does not offer any more secure alternative). The documentation MUST describe any relevant security risks and any known mitigations if these broken algorithms or modes are necessary for an interoperable protocol. [crypto_working]
    ECB mode is almost never appropriate because it reveals identical blocks within the ciphertext as demonstrated by the ECB penguin, and CTR mode is often inappropriate because it does not perform authentication and causes duplicates if the input state is repeated. In many cases it's best to choose a block cipher algorithm mode designed to combine secrecy and authentication, e.g., Galois/Counter Mode (GCM) and EAX. Projects MAY allow users to enable broken mechanisms (e.g., during configuration) where necessary for compatibility, but then users know they're doing it.

    No broken algorithm and no inappropriate cipher mode is used anywhere in the project's security mechanisms, and none is needed for interoperability.

    VERIFIED ABSENT. A scan of the codebase for MD4, MD5, SHA-1, single DES, RC4, and Dual_EC_DRBG returns nothing outside of test files -- none of them appears in the cryptographic path at all. There is consequently no interoperability exception to document, and no configuration option that would enable one.

    CIPHER MODE. Secrets at rest use AES-256-GCM, an AEAD mode that provides authentication alongside confidentiality, which is the combination this criterion recommends. ECB, CBC, and raw CTR are not used anywhere: the codebase contains no call to cipher.NewCBCEncrypter, NewCTR, or any ECB construction. The nonce is drawn from crypto/rand per encryption rather than reused or derived, so GCM's requirement for nonce uniqueness is met by construction. https://github.com/sydlexius/stillwater/blob/main/internal/encryption/encryption.go

    THE REST OF THE PATH. SHA-256 for hashing, HMAC for message authentication, bcrypt for password storage, ECDSA on P-256 for certificate keys, and TLS 1.3 as the enforced transport floor -- TLS 1.3 having removed the weak cipher suites, RC4, and CBC-mode suites from negotiation entirely, so a downgrade to a broken algorithm is not reachable.

    ONE CLARIFICATION, TO PRE-EMPT A FALSE POSITIVE. The project computes a 64-bit perceptual hash (dHash) over images to detect visually duplicate artwork: https://github.com/sydlexius/stillwater/blob/main/internal/image/hash.go . That is an image-similarity function, not a cryptographic one. It protects nothing, guards no security decision, and is never used for authentication, integrity, or as a security boundary -- comparing artwork for near-duplicates is its only purpose. Its short digest is therefore not a cryptographic weakness.

    ENFORCEMENT. gosec, which flags weak and deprecated cryptographic primitives, is among the 23 linters enabled in CI and runs on every change; CodeQL analyses every pull request; govulncheck runs against the dependency graph. A broken primitive introduced later would fail the build rather than reach a release.



    The default security mechanisms within the software produced by the project SHOULD NOT depend on cryptographic algorithms or modes with known serious weaknesses (e.g., the SHA-1 cryptographic hash algorithm or the CBC mode in SSH). [crypto_weaknesses]
    Concerns about CBC mode in SSH are discussed in CERT: SSH CBC vulnerability.

    Nothing in the project's security mechanisms depends on an algorithm or mode with a known serious weakness.

    SHA-1 does not appear in the cryptographic path at all -- verified by scanning the codebase. Hashing is SHA-256 throughout, and message authentication is HMAC.

    CBC is not used in any form. Secrets at rest use AES-256-GCM, an authenticated mode, so the padding-oracle and malleability problems that motivate the concern about CBC do not arise: a ciphertext that has been tampered with fails authentication rather than decrypting into attacker-influenced plaintext.

    The transport floor is TLS 1.3, set explicitly at the listener rather than left to negotiation. This is stronger than avoiding weak choices individually: TLS 1.3 removed CBC-mode cipher suites, RC4, static RSA key exchange, and renegotiation from the protocol, so the weaknesses this criterion is concerned with are not reachable by downgrade even if a client requests them. Earlier protocol versions are refused, not merely deprioritised.

    Elliptic-curve work uses P-256 rather than any of the curves with questioned provenance, and randomness comes from crypto/rand -- never math/rand, and never a DRBG of uncertain design.

    Passwords are stored with bcrypt at the library's default cost, and are pre-hashed before bcrypt so that its 72-byte input truncation cannot silently discard part of a long passphrase.

    The project does not implement or expose SSH, so the CBC-in-SSH case this criterion cites does not apply.

    Enforcement rather than intent: gosec, which flags weak and deprecated primitives, is among the 23 linters enabled in CI; CodeQL analyses every pull request; govulncheck runs against the dependency graph, and two golang.org/x/crypto advisories were resolved by upgrading the dependency rather than working around them.



    The security mechanisms within the software produced by the project SHOULD implement perfect forward secrecy for key agreement protocols so a session key derived from a set of long-term keys cannot be compromised if one of the long-term keys is compromised in the future. [crypto_pfs]

    The only key-agreement protocol the project uses is TLS, and it is pinned to TLS 1.3, which provides forward secrecy unconditionally.

    The HTTPS listener sets MinVersion: tls.VersionTLS13 explicitly rather than leaving the floor to negotiation: https://github.com/sydlexius/stillwater/blob/main/internal/server/listeners.go

    This is stronger than selecting forward-secret cipher suites within an older protocol. TLS 1.3 removed static RSA and static Diffie-Hellman key exchange from the protocol entirely, so every handshake is an ephemeral (EC)DHE exchange by construction. There is no cipher-suite configuration, downgrade path, or interoperability option through which a non-forward-secret handshake could be negotiated -- a client offering only older mechanisms is refused rather than accommodated.

    Compromise of the server's long-term private key at some future point therefore does not expose previously recorded sessions: the per-session keys derive from ephemeral key shares that are discarded when the session ends and are never transmitted.

    The HTTP/3 listener shares the same TLS material and the same floor; QUIC mandates TLS 1.3 in any case, and quic-go enforces that internally.

    The project implements no other key-agreement protocol. Secrets at rest are encrypted with a locally held symmetric key (AES-256-GCM) rather than through a key-agreement exchange, so forward secrecy is not applicable to that path -- there are no session keys and no long-term keys negotiated between parties.

    Outbound connections to metadata providers and to Emby, Jellyfin, and Lidarr use Go's standard net/http client, whose default TLS configuration prefers forward-secret suites and negotiates TLS 1.3 with any server that supports it.



    If the software produced by the project causes the storing of passwords for authentication of external users, the passwords MUST be stored as iterated hashes with a per-user salt by using a key stretching (iterated) algorithm (e.g., Argon2id, Bcrypt, Scrypt, or PBKDF2). See also OWASP Password Storage Cheat Sheet. [crypto_password_storage]
    This criterion applies only when the software is enforcing authentication of users using passwords for external users (aka inbound authentication), such as server-side web applications. It does not apply in cases where the software stores passwords for authenticating into other systems (aka outbound authentication, e.g., the software implements a client for some other system), since at least parts of that software must have often access to the unhashed password.

    Local user passwords are stored as bcrypt hashes -- an iterated, salted, key-stretching algorithm, and one of the algorithms this criterion names.

    Implementation: bcrypt.GenerateFromPassword(PrehashPassword(password), bcrypt.DefaultCost) via golang.org/x/crypto/bcrypt. https://github.com/sydlexius/stillwater/blob/main/internal/auth/user.go

    • ITERATED: bcrypt is a deliberately slow key-stretching function; the work factor is the library's default cost rather than a lowered value.
    • PER-USER SALT: bcrypt generates a random salt per invocation and stores it within the resulting hash, so two users with the same password produce different stored values.
    • The plaintext password is never stored, and never logged.

    PRE-HASHING, AND WHY. The password is passed through SHA-256 and hex-encoded before bcrypt, rather than handed to bcrypt directly. bcrypt silently truncates its input at 72 bytes, so a long passphrase would otherwise have its tail discarded without any error -- two distinct passphrases sharing a 72-byte prefix would authenticate interchangeably. Pre-hashing to a fixed-length 64-character hex digest removes that truncation entirely, so the full passphrase contributes to the stored hash. This is the construction the OWASP Password Storage Cheat Sheet recommends for bcrypt, and it does not weaken the stretching: bcrypt still performs its full cost-factor work over the digest, and the per-invocation salt is unchanged.

    TIMING. Login compares against a bcrypt hash computed once at default cost for the unknown-user case, so an unregistered username costs the same as a registered one and does not leak account existence by response time.

    SCOPE. This applies to local accounts. The project also supports OIDC and federated authentication against a media server, where no password is stored at all -- the identity provider or media server holds the credential. Credentials the project stores for OUTBOUND authentication to third-party services (provider API keys) are encrypted with AES-256-GCM rather than hashed, since they must be recoverable to be used, which is the outbound case this criterion explicitly excludes.



    The security mechanisms within the software produced by the project MUST generate all cryptographic keys and nonces using a cryptographically secure random number generator, and MUST NOT do so using generators that are cryptographically insecure. [crypto_random]
    A cryptographically secure random number generator may be a hardware random number generator, or it may be a cryptographically secure pseudo-random number generator (CSPRNG) using an algorithm such as Hash_DRBG, HMAC_DRBG, CTR_DRBG, Yarrow, or Fortuna. Examples of calls to secure random number generators include Java's java.security.SecureRandom and JavaScript's window.crypto.getRandomValues. Examples of calls to insecure random number generators include Java's java.util.Random and JavaScript's Math.random.

    Every cryptographic key, nonce, token, and secret is generated from crypto/rand, Go's cryptographically secure random source, which draws from the operating system CSPRNG.

    Security-relevant generation sites all use it:

    • The AES-256 encryption key, when generated (internal/encryption/encryption.go)
    • The GCM nonce, drawn fresh per encryption
    • Session and authentication tokens (internal/auth/)
    • CSRF tokens (internal/api/middleware/csrf.go)
    • OIDC state and nonce values (internal/auth/provider_oidc.go)
    • Invitation tokens (internal/auth/invite.go)
    • ACME account and certificate keys (internal/server/cert_manager_lego.go)
    • Settings export material (internal/settingsio/export.go)

    math/rand is used in exactly two places, and neither is a security mechanism. Both are annotated inline with the reason:

    • internal/watcher/probe.go generates a filename suffix for a filesystem write-probe -- a temporary file the watcher creates to test whether a directory is writable. Unpredictability is not a property it needs.
    • internal/provider/retry.go computes jitter for retry backoff against third-party metadata APIs, so concurrent retries do not synchronise. Jitter does not need to be unguessable.

    Neither generates a key, nonce, token, or any value an attacker could exploit by predicting. Both carry a //nolint:gosec directive naming the linter and stating why the rule does not apply, which is the project's convention for every suppression.

    That distinction is enforced rather than trusted: gosec's G404 rule flags every use of a non-cryptographic RNG, and gosec is among the 23 linters enabled in CI running on every change. A new math/rand call in a security path would fail the build unless someone explicitly suppressed it with a written justification, which is visible in review.


  • Secured delivery against man-in-the-middle (MITM) attacks


    The project MUST use a delivery mechanism that counters MITM attacks. Using https or ssh+scp is acceptable. [delivery_mitm]
    An even stronger mechanism is releasing the software with digitally signed packages, since that mitigates attacks on the distribution system, but this only works if the users can be confident that the public keys for signatures are correct and if the users will actually check the signature.

    HTTPS is used throughout and additionally by digital signatures on every release artifact.

    TRANSPORT. Every distribution channel is HTTPS-only:

    Go module dependencies are fetched over HTTPS and verified against go.sum, so a tampered dependency fails the build rather than being silently accepted.

    SIGNATURES, the stronger mechanism this criterion describes. Release artifacts are signed with cosign (Sigstore) as part of the release workflow, and SLSA provenance attestation is generated at release level: https://github.com/sydlexius/stillwater/blob/main/.github/workflows/release.yml

    Sigstore is keyless -- signatures are bound to the GitHub Actions workflow identity that produced them and recorded in the public Rekor transparency log. That addresses the caveat in this criterion's own wording: a user does not need to obtain and trust a maintainer's public key out of band, since verification checks the signing identity against the transparency log rather than against a key the user must first acquire securely. Checksums are published alongside the artifacts, and the multi-architecture container manifest is signed as well as the individual images.

    OpenSSF Scorecard independently confirms this, scoring the project 10/10 on Signed-Releases: "5 out of the last 5 releases have a total of 10 signed artifacts" -- https://securityscorecards.dev/viewer/?uri=github.com/sydlexius/stillwater



    A cryptographic hash (e.g., a sha1sum) MUST NOT be retrieved over http and used without checking for a cryptographic signature. [delivery_unsigned]
    These hashes can be modified in transit.

    Nothing in the project retrieves a cryptographic hash over plaintext HTTP, in the build, in CI, or at runtime.

    BUILD AND CI. A scan of the workflows finds no plaintext http:// fetch of any kind. Everything the build retrieves comes over HTTPS, and each class is verified by a mechanism stronger than a bare downloaded checksum:

    • Go module dependencies are fetched over HTTPS and verified against the committed go.sum, which is itself in version control rather than downloaded alongside the artifact. A tampered module fails the build.
    • npm dependencies are pinned in package-lock.json with integrity hashes, likewise committed.
    • All 155 GitHub Actions references are pinned to commit SHAs rather than mutable tags, so a compromised or moved tag cannot substitute different code. OpenSSF Scorecard confirms this independently, scoring 10/10 on Pinned-Dependencies for Actions.
    • Container base images are pinned in the Dockerfiles.

    RUNTIME. The application fetches metadata and artwork from third-party providers over HTTPS, and connects to Emby, Jellyfin and Lidarr over the scheme the operator configures. It does not download a checksum or hash file from any source and act on it, so the situation this criterion describes does not arise.

    The one place the project handles checksums is in the opposite direction: the release workflow PUBLISHES checksums alongside its artifacts, and those artifacts are additionally signed with cosign (Sigstore) with SLSA provenance attestation. A consumer verifying a release therefore checks a signature bound to the producing workflow identity and recorded in the public Rekor transparency log, rather than trusting a hash retrieved over the wire.


  • Publicly known vulnerabilities fixed


    There MUST be no unpatched vulnerabilities of medium or higher severity that have been publicly known for more than 60 days. [vulnerabilities_fixed_60_days]
    The vulnerability must be patched and released by the project itself (patches may be developed elsewhere). A vulnerability becomes publicly known (for this purpose) once it has a CVE with publicly released non-paywalled information (reported, for example, in the National Vulnerability Database) or when the project has been informed and the information has been released to the public (possibly by the project). A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known. Note: this means that users might be left vulnerable to all attackers worldwide for up to 60 days. This criterion is often much easier to meet than what Google recommends in Rebooting responsible disclosure, because Google recommends that the 60-day period start when the project is notified even if the report is not public. Also note that this badge criterion, like other criteria, applies to the individual project. Some projects are part of larger umbrella organizations or larger projects, possibly in multiple layers, and many projects feed their results to other organizations and projects as part of a potentially-complex supply chain. An individual project often cannot control the rest, but an individual project can work to release a vulnerability patch in a timely way. Therefore, we focus solely on the individual project's response time. Once a patch is available from the individual project, others can determine how to deal with the patch (e.g., they can update to the newer version or they can apply just the patch as a cherry-picked solution).

    There are no unpatched vulnerabilities of any severity, publicly known or otherwise.

    Verified against the live repository:

    • Published security advisories: 0 (https://github.com/sydlexius/stillwater/security/advisories)
    • Open Dependabot alerts: 0
    • Open code-scanning (CodeQL) alerts: 0
    • No CVE has been assigned against the project; NIST's CPE dictionary returns no entry for either the product or the vendor name, as expected for a project with no published CVE.

    There has consequently never been a 60-day window to exceed.

    Vulnerabilities are surfaced continuously rather than waiting on an external report: CodeQL analyses every pull request, govulncheck runs in CI against the dependency graph, gosec is among the 23 linters enabled on every change, and Dependabot is configured for dependency updates.

    Dependency advisories are acted on promptly rather than accumulating. Two golang.org/x/crypto advisories surfaced by govulncheck were resolved by upgrading the dependency the same day they were identified, ahead of any external scanner flagging them. One further advisory affecting a transitive dependency has no fixed version published upstream; the affected subpackage is never imported by this project, so it is unreachable here, and that determination was made by call-path analysis rather than by version range alone.

    If a vulnerability is reported, SECURITY.md commits to an initial acknowledgement within 72 hours and a fix released as soon as practical, typically within 14 days for critical issues -- well inside the 60-day bound this criterion sets: https://github.com/sydlexius/stillwater/blob/main/SECURITY.md



    Projects SHOULD fix all critical vulnerabilities rapidly after they are reported. [vulnerabilities_critical_fixed]

    No critical vulnerability has been reported against the project, so there is no remediation record to point to. Verified live: zero published security advisories, zero open Dependabot alerts, zero open CodeQL alerts, and no CVE assigned.

    What can be evidenced is the response speed on the security findings the project has actually had.

    Dependency advisories are fixed the day they surface. Two golang.org/x/crypto advisories were identified by govulncheck and resolved by upgrading the dependency within hours, ahead of any external scanner flagging them. A third advisory affecting a transitive dependency has no fixed version published upstream; call-path analysis confirmed the affected subpackage is never imported here, so it is unreachable rather than unaddressed, and that determination is recorded rather than assumed.

    Findings from code review are treated the same way. A recent change introduced a data-loss window -- a cleanup sweep could delete another concurrent operation's in-progress staging file, turning a recoverable failure into permanent loss. It was found in review, fixed the same session with a proof that reproduces the loss when the fix is removed, and the fix itself was then re-reviewed rather than trusted.

    The commitment for a reported vulnerability is published in advance: an initial acknowledgement within 72 hours, and a fix released as soon as practical, typically within 14 days for critical issues. https://github.com/sydlexius/stillwater/blob/main/SECURITY.md

    Detection is continuous rather than waiting on a report -- CodeQL on every pull request, govulncheck in CI, gosec among 23 enabled linters, and Dependabot for dependency updates -- and releases are frequent (four stable releases in the past month), so a fix does not wait on a distant release train to reach users.


  • Other security issues


    The public repositories MUST NOT leak a valid private credential (e.g., a working password or private key) that is intended to limit public access. [no_leaked_credentials]
    A project MAY leak "sample" credentials for testing and unimportant databases, as long as they are not intended to limit public access.

    No valid private credential is present in the repository.

    GitHub secret scanning is ENABLED on the repository, so a committed credential matching a known provider pattern is detected and reported automatically rather than depending on anyone noticing. Push protection and scanning run against the full history, not just new commits.

    Nothing sensitive is tracked. No .pem, .key, .p12, SSH private key, or encryption key file exists in version control -- the only match for a key-shaped filename is a Go test that asserts the encryption key file is created with 0600 permissions, which contains no key material. .gitignore excludes .env and .env.*, all SQLite database files including WAL and shared-memory sidecars, and the UAT staging directory, which holds a cloned database and an encryption key and is deliberately kept out of git so that material never enters history.

    The encryption key is generated at runtime into a 0600 file beside the database rather than being shipped, embedded, or held in an environment variable -- which also keeps it out of process listings and inherited environments. Provider API keys are supplied by the operator at runtime and stored encrypted with AES-256-GCM; none are distributed with the software.

    Test fixtures use obviously non-functional placeholder values, and where a test needs key material it is generated at test time rather than committed.

    The project also treats credentials on the command line as a leak risk in their own right, not just credentials in files: passing a secret as a command-line argument is avoided because it is visible in the process table and can be recorded in shell and tooling history. Secrets are passed by environment variable or stdin instead.

    CI reinforces this -- gosec is among the 23 enabled linters and flags hardcoded credential patterns, and CodeQL analyses every pull request.


 Analysis 8/8 ●

  • Static code analysis


    At least one static code analysis tool (beyond compiler warnings and "safe" language modes) MUST be applied to any proposed major production release of the software before its release, if there is at least one FLOSS tool that implements this criterion in the selected language. [static_analysis]
    A static code analysis tool examines the software code (as source code, intermediate code, or executable) without executing it with specific inputs. For purposes of this criterion, compiler warnings and "safe" language modes do not count as static code analysis tools (these typically avoid deep analysis because speed is vital). Some static analysis tools focus on detecting generic defects, others focus on finding specific kinds of defects (such as vulnerabilities), and some do a combination. Examples of such static code analysis tools include cppcheck (C, C++), clang static analyzer (C, C++), SpotBugs (Java), FindBugs (Java) (including FindSecurityBugs), PMD (Java), Brakeman (Ruby on Rails), lintr (R), goodpractice (R), Coverity Quality Analyzer, SonarQube, Codacy, and HP Enterprise Fortify Static Code Analyzer. Larger lists of tools can be found in places such as the Wikipedia list of tools for static code analysis, OWASP information on static code analysis, NIST list of source code security analyzers, and Wheeler's list of static analysis tools. If there are no FLOSS static analysis tools available for the implementation language(s) used, you may select 'N/A'.

    Multiple FLOSS static analysis tools run on every change, so every release is analysed by construction rather than as a pre-release step someone has to remember.

    CodeQL (MIT-licensed CLI) is the primary one. It runs on every push and every pull request, plus a weekly scheduled scan, analysing two languages: go for the application itself and actions for the GitHub Actions workflows -- the latter catching workflow-level issues such as untrusted input reaching a run step. Findings surface as code-scanning alerts on the pull request that introduced them, and there are currently zero open alerts. https://github.com/sydlexius/stillwater/blob/main/.github/workflows/codeql.yml

    Alongside it, and also on every change:

    • gosec, the Go security-focused analyser, among the 23 linters enabled via golangci-lint (GPL-3.0)
    • staticcheck, which performs deep interprocedural analysis well beyond compiler diagnostics
    • govulncheck (BSD-3-Clause), which is call-path aware rather than version-range based: it reports a known vulnerability only when the affected code is actually reachable from this project
    • gocritic with its style and performance analysis bundles enabled
    • Hadolint for the Dockerfiles, actionlint for workflow syntax, stylelint for CSS

    These are required status checks, so a finding blocks the change rather than being filed for later. Because they gate every merge, the state of the default branch at any tag is analysis-clean -- a release cannot contain code that has not passed them.

    Beyond static analysis, the project runs mutation testing in CI against its own test suite, checking that the tests actually detect changed behaviour rather than merely executing the lines.

    Current result: golangci-lint run ./... reports 0 issues across the module, and OpenSSF Scorecard independently scores the project 10/10 on its SAST check.



    It is SUGGESTED that at least one of the static analysis tools used for the static_analysis criterion include rules or approaches to look for common vulnerabilities in the analyzed language or environment. [static_analysis_common_vulnerabilities]
    Static analysis tools that are specifically designed to look for common vulnerabilities are more likely to find them. That said, using any static tools will typically help find some problems, so we are suggesting but not requiring this for the 'passing' level badge.

    Three of the static analysis tools in use are specifically designed to find vulnerabilities rather than general defects.

    CodeQL runs on every push and pull request with its security query suites for Go, covering the injection, path traversal, SSRF, insecure randomness, and sensitive-data-exposure classes among others. It also analyses the GitHub Actions workflows as a separate language, which catches supply-chain issues such as untrusted input reaching a run step -- a class general-purpose linters do not look for at all. There are currently zero open code-scanning alerts. https://github.com/sydlexius/stillwater/blob/main/.github/workflows/codeql.yml

    gosec is the Go ecosystem's dedicated security analyser, and its rule set maps directly onto the common vulnerability classes: hardcoded credentials, SQL injection, command injection, path traversal, weak or deprecated cryptographic primitives, insecure random number generation, unsafe file permissions, and unhandled errors in security-relevant positions. It is enabled among the 23 linters that run on every change.

    gosec's value here is demonstrable rather than theoretical. Its G404 rule -- non-cryptographic random number generator -- is what forces every use of math/rand in this codebase to be justified in writing: the two non-security uses that exist (a filesystem probe filename and retry jitter) each carry an inline suppression naming the rule and stating why it does not apply. A new math/rand call in a security path would fail the build.

    govulncheck completes the set from a different angle: rather than pattern-matching source, it checks the dependency graph against the Go vulnerability database and reports a known CVE only when the affected function is actually reachable from this project's call paths. That distinction is load-bearing -- one advisory currently affecting a transitive dependency was determined unreachable here by exactly that analysis, rather than by comparing version ranges.

    Supporting these, staticcheck performs deep interprocedural analysis, Hadolint checks the Dockerfiles for insecure container practices, and actionlint validates the workflows.

    OpenSSF Scorecard independently scores the project 10/10 on its SAST check.



    All medium and higher severity exploitable vulnerabilities discovered with static code analysis MUST be fixed in a timely way after they are confirmed. [static_analysis_fixed]
    A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known. Note that criterion vulnerabilities_fixed_60_days requires that all such vulnerabilities be fixed within 60 days of being made public.

    There are currently zero open code-scanning alerts of any severity, verified live against the repository.

    Findings are not allowed to accumulate. Static analysis runs as required status checks on every pull request -- CodeQL, gosec, staticcheck and govulncheck among them -- so a finding blocks the change that introduced it rather than being filed for later triage. A vulnerability therefore cannot reach the default branch and start ageing.

    Where a finding is genuinely a false positive or a deliberate acceptance, it is dismissed with its reasoning recorded rather than silently closed. Of the historical dismissals, all 16 marked "won't fix" and 2 marked "used in tests" carry a written dismissal comment, as do 61 of 62 marked "false positive". The project's standing rule is that a dismissal must state the MECHANISM that makes the finding inapplicable, with file or configuration evidence, never a bare "false positive" -- and that the reasoning is recorded on both surfaces a future reader might consult: the alert itself, and the scanner's inline review thread on the pull request. A dismissal without that reasoning reads, six months later, as someone having waved the finding away.

    The single dismissal missing a comment is a documentation gap in the record rather than an unfixed vulnerability, and the standing rule exists to prevent exactly that.

    Response speed is evidenced elsewhere too: two golang.org/x/crypto advisories surfaced by govulncheck were resolved by upgrading the dependency within hours of being identified, ahead of any external scanner reporting them. One further advisory affecting a transitive dependency has no upstream fix published; call-path analysis confirmed the affected subpackage is never imported here, so it is unreachable rather than outstanding.

    No CVE has been assigned against the project, and no security advisory has been published: https://github.com/sydlexius/stillwater/security



    It is SUGGESTED that static source code analysis occur on every commit or at least daily. [static_analysis_often]

    Static analysis runs on every commit, not merely daily.

    CodeQL is triggered on every push and every pull request, with an additional weekly scheduled scan so the default branch is re-analysed against updated query packs even when nothing has changed. It analyses two languages: go for the application and actions for the GitHub Actions workflows. https://github.com/sydlexius/stillwater/blob/main/.github/workflows/codeql.yml

    Running alongside it on every change, as required status checks:

    • golangci-lint with 23 linters enabled, including gosec for security-specific rules, staticcheck for deep interprocedural analysis, and gocritic with its style and performance bundles
    • govulncheck against the dependency graph, call-path aware rather than version-range based
    • Hadolint for the Dockerfiles, actionlint for workflow syntax, stylelint for CSS

    Analysis also runs before a commit exists: a pre-commit hook runs golangci-lint over the staged packages, so a finding is caught locally rather than after a push. The gate is real -- a cognitive-complexity violation blocked a commit during recent work and had to be resolved by extracting functions rather than suppressed.

    Because these are required checks on every pull request, and direct commits to the default branch are refused by branch protection, no commit reaches the trunk without having been analysed. The frequency is therefore structural rather than scheduled: there is no window in which unanalysed code can sit on the default branch.

    Recent cadence for scale: 648 commits in the last 90 days, 160 merges to the default branch in the last 30, each analyzed.


  • Dynamic code analysis


    It is SUGGESTED that at least one dynamic analysis tool be applied to any proposed major production release of the software before its release. [dynamic_analysis]
    A dynamic analysis tool examines the software by executing it with specific inputs. For example, the project MAY use a fuzzing tool (e.g., American Fuzzy Lop) or a web application scanner (e.g., OWASP ZAP or w3af). In some cases the OSS-Fuzz project may be willing to apply fuzz testing to your project. For purposes of this criterion the dynamic analysis tool needs to vary the inputs in some way to look for various kinds of problems or be an automated test suite with at least 80% branch coverage. The Wikipedia page on dynamic analysis and the OWASP page on fuzzing identify some dynamic analysis tools. The analysis tool(s) MAY be focused on looking for security vulnerabilities, but this is not required.

    Several dynamic analysis mechanisms run against the software, and each executes it with varying or generated inputs rather than inspecting source.

    FUZZING. 30 native Go fuzz targets across 11 packages, run in CI on a weekly schedule and on demand, each with a time budget. Go's fuzzing engine is coverage-guided: it mutates inputs and retains those that reach new code paths, and any crash or failing input is written to testdata as a permanent regression case, so a discovered defect becomes a standing test rather than a one-off. A crash fails the workflow. The matrix is enforced, so a new fuzz target cannot be added without being exercised. https://github.com/sydlexius/stillwater/blob/main/.github/workflows/fuzz.yml

    END-TO-END API EXERCISE. make bruno-ci builds the binary, starts an ephemeral server, and runs an executable Bruno collection against the live REST API -- a genuine running instance, not a mock.

    ACCESSIBILITY SCANNING. Playwright drives real Chromium and Firefox browsers against rendered pages, with axe-core evaluating the live DOM. This is a browser-driven scan of the running application rather than static template inspection.

    RACE DETECTION. The whole test suite runs under Go's race detector in CI, which is a runtime instrumentation: it observes actual memory access ordering during execution and reports data races that no static pass can see.

    PROVIDER-FAILURE SMOKE TESTS. A dedicated CI tier exercises the application's behaviour when third-party metadata providers fail, so error paths are executed rather than assumed.

    MUTATION TESTING. CI mutates the source and re-runs the suite, checking the tests actually detect changed behaviour. This is a check on the dynamic analysis itself.

    Because these run in CI on every change or on a weekly schedule against the default branch, any tagged release has been dynamically analysed before it is cut, rather than analysis being a step someone must remember at release time.



    It is SUGGESTED that if the software produced by the project includes software written using a memory-unsafe language (e.g., C or C++), then at least one dynamic tool (e.g., a fuzzer or web application scanner) be routinely used in combination with a mechanism to detect memory safety problems such as buffer overwrites. If the project does not produce software written in a memory-unsafe language, choose "not applicable" (N/A). [dynamic_analysis_unsafe]
    Examples of mechanisms to detect memory safety problems include Address Sanitizer (ASAN) (available in GCC and LLVM), Memory Sanitizer, and valgrind. Other potentially-used tools include thread sanitizer and undefined behavior sanitizer. Widespread assertions would also work.

    The project produces no software written in a memory-unsafe language.

    Stillwater is written entirely in Go, which is memory-safe: it is garbage-collected, bounds-checks slice and array access, and does not permit pointer arithmetic. Buffer overwrites and use-after-free of the kind this criterion targets are not expressible.

    There is no C or C++ in the project, and no cgo. Release binaries are built with CGO_ENABLED=0, so the shipped artifacts are pure Go with no linked C libraries at all -- verified in both the release workflow and the goreleaser configuration. Even the SQLite driver is modernc.org/sqlite, a pure-Go transliteration rather than a cgo binding to the C library, which is a deliberate choice that keeps the memory-unsafe surface at zero rather than merely small.

    The browser-facing code is HTML, CSS, and a small amount of vendored JavaScript, none of it memory-unsafe either.

    For completeness, runtime instrumentation is used regardless: the test suite runs under Go's race detector in CI, which is a dynamic memory-access analysis in the same family as ThreadSanitizer -- it observes actual access ordering during execution rather than reasoning about the source. That runs alongside 30 fuzz targets across 11 packages, an executable API collection against a live server, and browser-driven accessibility scanning.



    It is SUGGESTED that the project use a configuration for at least some dynamic analysis (such as testing or fuzzing) which enables many assertions. In many cases these assertions should not be enabled in production builds. [dynamic_analysis_enable_assertions]
    This criterion does not suggest enabling assertions during production; that is entirely up to the project and its users to decide. This criterion's focus is instead to improve fault detection during dynamic analysis before deployment. Enabling assertions in production use is completely different from enabling assertions during dynamic analysis (such as testing). In some cases enabling assertions in production use is extremely unwise (especially in high-integrity components). There are many arguments against enabling assertions in production, e.g., libraries should not crash callers, their presence may cause rejection by app stores, and/or activating an assertion in production may expose private data such as private keys. Beware that in many Linux distributions NDEBUG is not defined, so C/C++ assert() will by default be enabled for production in those environments. It may be important to use a different assertion mechanism or defining NDEBUG for production in those environments.

    Go has no assert() construct and no NDEBUG-style compile-time toggle, so the C/C++ shape of this criterion does not translate directly. The equivalent -- extra checking enabled during dynamic analysis but not compiled into production builds -- is used extensively.

    RACE DETECTOR. The test suite runs under go test -race in CI, which is exactly this pattern: CGO_ENABLED=1 go test -race instruments every memory access to check ordering at runtime, while release binaries are built with CGO_ENABLED=0 and carry none of that instrumentation. It is a large body of runtime checking that exists only during analysis.

    FUZZING WITH PERSISTED FAILURES. 30 fuzz targets across 11 packages run coverage-guided, and any input that trips a check is written to testdata as a permanent regression case. A crash fails the workflow rather than being reported and forgotten.

    ASSERTIONS AS TEST DISCIPLINE. The project's testing standard requires assertions that most suites omit, and these are the substance of the criterion rather than a syntax question:

    • A test must assert its own PRECONDITIONS, not only its outcome, so a fixture that silently stops exercising the intended path fails instead of passing vacuously. Where a test seeds a directory, it reads the directory back and asserts the count before exercising the code under test.
    • A test guarding a bug fix must be shown to FAIL without the fix -- revert it, confirm red, restore, confirm green -- so a test that asserts nothing meaningful is caught before it lands.
    • Structural assertions are used where a behavioural one cannot see the property: one test parses the source of a function and asserts a statement ordering invariant that no runtime check could observe.

    MUTATION TESTING. CI mutates the source and re-runs the suite, verifying the assertions actually detect changed behaviour rather than merely executing lines.

    None of this instrumentation ships. Production builds are CGO_ENABLED=0, with no race detector, no fuzzing harness, and no test-only checking compiled in.



    All medium and higher severity exploitable vulnerabilities discovered with dynamic code analysis MUST be fixed in a timely way after they are confirmed. [dynamic_analysis_fixed]
    If you are not running dynamic code analysis and thus have not found any vulnerabilities in this way, choose "not applicable" (N/A). A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known.

    Dynamic analysis is run routinely, and it has not discovered a security vulnerability of medium or higher severity. There is consequently nothing outstanding.

    The mechanisms running are 30 native Go fuzz targets across 11 packages on a weekly schedule, the full test suite under Go's race detector, an executable API collection exercised against a live server, browser-driven accessibility scanning with axe-core, and a provider-failure smoke tier. No fuzz crash, data race, or comparable finding is currently open; a crash fails the fuzzing workflow rather than being reported and forgotten, and any input that trips a check is written to testdata as a permanent regression case.

    What dynamic analysis has found here is correctness defects rather than exploitable vulnerabilities, and those are fixed at the point of discovery rather than deferred. A recent example: a concurrency defect where a cleanup sweep could delete another in-flight operation's staging file, converting a recoverable failure into permanent data loss. It was found during review, fixed in the same session, and the fix was verified by a two-goroutine test that reproduces the loss when the fix is removed -- then re-reviewed rather than trusted. That is a data-integrity bug, not a security vulnerability, but it illustrates the response pattern.

    Verified live against the repository: zero open code-scanning alerts, zero open Dependabot alerts, zero published security advisories, and no CVE assigned. https://github.com/sydlexius/stillwater/security

    If a dynamic analysis run does surface a vulnerability, SECURITY.md commits to an initial acknowledgement within 72 hours and a fix released as soon as practical, typically within 14 days for critical issues. Releases are frequent -- four stable releases in the past month -- so a fix reaches users promptly rather than waiting on a distant release train.



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Entry created on 2026-09-03 00:15:58 UTC, last updated on 2026-09-03 01:56:47 UTC.