AsiBackbone Learning

The project's source repository is publicly readable on GitHub and can be accessed without special repository permissions. The repository provides a stable HTTPS URL for browsing, cloning, and reviewing the project's source, documentation, samples, issues, releases, and development history.

https://github.com/AsiBackbone/Learning

The project uses Git for version control. The public commit history records each change, the author who made it, and the date and time of the change. Individual commits can be reviewed and compared through the GitHub repository history.

https://github.com/AsiBackbone/Learning/commits/main

The repository exposes ongoing development between formal releases rather than publishing only completed release snapshots. Development work is performed through public branches and pull requests, allowing proposed and interim changes to be reviewed before they are merged into the protected main branch.

https://github.com/AsiBackbone/Learning/branches
https://github.com/AsiBackbone/Learning/pulls

The project uses Git, a distributed version control system. Contributors can clone the complete repository and its history locally, create branches, commit changes independently, and submit those changes for collaborative review through GitHub pull requests.

https://github.com/AsiBackbone/Learning

Each public release is assigned a unique version identifier. Releases are published using versioned GitHub release tags such as v0.13.0, allowing users and reviewers to distinguish one release from another unambiguously.

https://github.com/AsiBackbone/Learning/releases

Each release is identified in Git using a version tag. For example, Learning release 0.13.0 is published under the Git tag v0.13.0, providing a stable version-control reference for the exact release contents.

https://github.com/AsiBackbone/Learning/tags
https://github.com/AsiBackbone/Learning/releases

Each public release includes human-readable release notes in the GitHub Releases section. The notes summarize major changes, new material, migrations, roadmap progress, publication updates, and release scope so users can understand what changed between versions.

https://github.com/AsiBackbone/Learning/releases
https://github.com/AsiBackbone/Learning/releases/tag/v0.14.0

Release notes are used to document security-relevant changes. When a release fixes a publicly known vulnerability with an assigned CVE or similar identifier, that vulnerability will be explicitly identified in the release notes. Releases with no such fixes have no CVE entries to report.

https://github.com/AsiBackbone/Learning/releases

The project provides documented reporting paths for both ordinary bugs and sensitive security concerns. General defects, documentation problems, and enhancement requests may be submitted through GitHub Issues, while sensitive vulnerabilities are handled through GitHub private vulnerability reporting when available.

https://github.com/AsiBackbone/Learning/issues
https://github.com/AsiBackbone/Learning/blob/main/SECURITY.md

The project uses GitHub Issues as its public issue tracker for individual defects, documentation problems, maintenance tasks, and enhancement work. Issues remain individually addressable and retain their discussion, labels, status, and resolution history.

https://github.com/AsiBackbone/Learning/issues

The project actively reviews and responds to submitted issues. Recent bug and documentation reports have been acknowledged through maintainer action and resolution, with issues tracked to completion in the public GitHub issue history.

https://github.com/AsiBackbone/Learning/issues

The project actively reviews and responds to enhancement requests submitted through GitHub Issues. Recent enhancement-labeled requests have been triaged and completed, demonstrating that enhancement proposals are regularly acknowledged and acted upon.

https://github.com/AsiBackbone/Learning/issues?q=is%3Aissue+label%3Aenhancement

Private vulnerability reports are supported through GitHub private vulnerability reporting. SECURITY.md instructs reporters to use the private advisory channel for sensitive issues and explicitly warns against posting exploit details, credentials, personal data, or other sensitive material in public project channels.

https://github.com/AsiBackbone/Learning/security/advisories/new
https://github.com/AsiBackbone/Learning/blob/main/SECURITY.md

The project publishes a documented vulnerability-reporting process in SECURITY.md. It explains what security concerns are in scope, what information reporters should provide, how sensitive information should be handled, and what response process maintainers follow.

https://github.com/AsiBackbone/Learning/blob/main/SECURITY.md

Private vulnerability reports are supported through GitHub private vulnerability reporting. SECURITY.md instructs reporters to use the private advisory channel for sensitive issues and explicitly warns against posting exploit details, credentials, personal data, or other sensitive material in public project channels.

https://github.com/AsiBackbone/Learning/security/advisories/new
https://github.com/AsiBackbone/Learning/blob/main/SECURITY.md

N/A — No vulnerability reports have been received during the applicable six-month period, so there is no report-response interval to measure against the 14-day requirement.

Buildable .NET sample projects are included and can be automatically restored, built, and tested from source using the documented dotnet CLI commands. GitHub Actions also performs automated sample validation.

The project uses the standard .NET SDK and dotnet CLI for restore, build, and test operations. CI provisions the same SDK through the commonly used actions/setup-dotnet GitHub Action.

The project can be built and tested entirely with open-source .NET SDK/CLI tooling. No proprietary IDE or proprietary build system is required.

The repository includes publicly available automated .NET tests covering its runnable sample projects. GitHub Actions restores, builds, and executes the complete sample test suite using dotnet test.

Tests use the standard .NET test invocation through the dotnet test CLI. The complete sample suite can be executed with dotnet test samples/Samples.slnx.

The repository contains focused automated tests for the behaviors and invariants demonstrated by its educational sample projects. The complete sample solution is validated as a suite, with individual samples also providing targeted tests for their documented behavior.

GitHub Actions provides continuous integration for the sample software. Pull requests targeting main automatically restore, build, and test the complete sample solution, and relevant pushes to main trigger the same validation.

Contributor guidance requires behavioral tests when executable examples depend on behavioral correctness. CONTRIBUTING.md also identifies missing tests as a defect and instructs contributors to allow the automated sample-validation suite to run on pull requests.

Recent major executable functionality has consistently been introduced with focused automated tests that verify the architectural invariants being taught. Examples include durable decision-ledger/audit-chain, adaptive-risk context, decision explainability, and cross-system capability-exchange samples.

Testing expectations are documented in CONTRIBUTING.md, the repository's contributor instructions. The guidance tells contributors when tests should accompany code changes and requires pull requests to pass automated sample validation.

The .NET sample projects enable nullable reference-type analysis and use TreatWarningsAsErrors=true through the shared samples/Directory.Build.props, causing compiler warnings to be treated as build failures.

Compiler warnings are treated as errors across the sample suite. GitHub Actions automatically builds the complete sample solution on pull requests and relevant pushes, so warning-producing changes fail automated validation and must be corrected before a successful build.

The repository uses a strict practical warning policy for its .NET samples by enabling nullable analysis and treating all compiler warnings as errors across the shared sample build configuration.

The project's primary development work demonstrates practical secure-software-design knowledge through dedicated guidance and implementations covering trust boundaries, least privilege, capability scoping, secure execution boundaries, replay protection, fail-safe behavior, secrets handling, secure logging, threat modeling, and supply-chain security.

The project documents common classes of security errors and their mitigations, including excessive privilege, confused-deputy risks, replay and stale-authority issues, sensitive-data leakage, unsafe trust-boundary crossings, dependency vulnerabilities, insecure workflow configuration, and execution without proper validation.

Executable project samples use standard, publicly reviewed cryptographic algorithms such as SHA-256 through the .NET cryptography APIs. The project does not define proprietary cryptographic algorithms.

Cryptographic operations use the platform-provided System.Security.Cryptography implementation, such as SHA256.HashData, rather than reimplementing cryptographic primitives within the project.

Cryptographic functionality used by the project is available through the open-source .NET SDK/runtime and can be built and executed entirely with FLOSS tooling.

The executable cryptographic functionality currently identified uses SHA-256 hashing and does not use configurable cryptographic keys. Therefore minimum/default key-length requirements do not apply.

Project-produced cryptographic examples use standard SHA-256 through System.Security.Cryptography and do not rely on known-weak algorithms such as SHA-1 or deprecated cipher modes.

The project does not implement key-agreement protocols, transport encryption, or session-key negotiation. Perfect forward secrecy is therefore outside the scope of the software produced by this repository.

The project does not implement an external-user authentication system and does not store user passwords, so password-hashing requirements do not apply.

The cryptographic functionality currently used by the project is hashing/fingerprinting and does not generate cryptographic keys or nonces. Secure random-number generation requirements are therefore not applicable.

Distribution channels use HTTPS exclusively. [osps_br_03_02]

Project distribution uses HTTPS, and the repository does not retrieve cryptographic hashes over unsecured HTTP and then rely on those hashes without an authenticated signature or secure transport.

The project has no known unresolved medium-or-higher vulnerability older than 60 days. Security issues are surfaced through automated tooling including Dependabot, CodeQL, OWASP Dependency-Check, and OpenSSF Scorecard, with current main and executable samples treated as the primary security-review targets.

The project has a documented vulnerability-reporting and remediation process. Confirmed security concerns are triaged and addressed through code, dependency, workflow, configuration, documentation, or advisory changes as appropriate, with private vulnerability reporting preferred for sensitive issues.

The repository contains no known valid private credentials intended to restrict public access. Repository policy prohibits real credentials, secrets, tokens, private keys, certificates, connection strings, and personal data in samples or reports. Secret scanning and push protection are part of the repository security posture, and executable samples are expected to use fictional or placeholder data.

The project uses GitHub CodeQL for static analysis of C# source code. CodeQL analysis is defined in https://github.com/AsiBackbone/Learning/blob/main/.github/workflows/codeql.yml and runs independently of ordinary compiler-warning checks.

CodeQL provides security-focused static-analysis queries for common vulnerability classes in C#/.NET code, including data-flow and trust-boundary issues that go beyond ordinary compiler diagnostics.

Confirmed medium-or-higher exploitable static-analysis findings are treated as security defects and remediated through code, dependency, workflow, or configuration changes as appropriate. The repository currently has no known outstanding confirmed medium-or-higher CodeQL vulnerability requiring remediation.

CodeQL analysis runs automatically on every pull request targeting main, on relevant source-code pushes to main, and weekly on a scheduled basis.

The project uses property-based fuzz testing with FsCheck as part of its automated .NET test suite. The fuzz tests execute the software with generated inputs and verify security-relevant invariants such as fail-closed identity validation and bounded capability use.

The executable software produced by this repository is written in C#/.NET, a memory-managed language. The project does not produce C or C++ software requiring memory-safety fuzzing tools such as AddressSanitizer.

Dynamic testing uses xUnit assertions and FsCheck property-based assertions to validate behavioral and security invariants during execution. Test failures cause the automated validation suite to fail.

Confirmed defects exposed by automated tests or property-based fuzzing are treated as repository defects and must be corrected for the validation suite to pass. Security-relevant findings are handled through the repository's documented security-remediation process.