Skip to content

Security: silver2dream/ai-workflow-kit

Security

SECURITY.md

Security Policy

Supported Versions

The following versions of AWK (AI Workflow Kit) are currently supported with security updates:

Version Supported
1.x.x ✅ Yes
< 1.0 ❌ No

Only supported versions will receive security patches. Users are strongly encouraged to upgrade to a supported release.


Reporting a Vulnerability

We take security vulnerabilities seriously and appreciate responsible disclosure.

How to Report

If you believe you have found a security vulnerability, please follow one of the options below:

  1. DO NOT open a public GitHub issue.

  2. Use GitHub's Private Vulnerability Reporting feature:

    • Go to the repository's Security tab
    • Click Report a vulnerability
  3. (Optional) Email security concerns to:
    security@YOURDOMAIN.COM
    (Replace with a real address if available. If not, GitHub reporting is preferred.)

What to Include

Please include as much information as possible:

  • A clear description of the vulnerability
  • Steps to reproduce
  • Affected versions
  • Potential impact and severity
  • Suggested mitigation or fix (if known)

Response SLA

We aim to respond and remediate according to the following targets:

Severity Initial Response Resolution Target
Critical Within 24 hours 7 days
High Within 48 hours 14 days
Medium Within 7 days 30 days
Low Within 14 days 90 days

What to Expect

  1. Acknowledgment – Confirmation that we received your report
  2. Investigation – Validation and impact assessment
  3. Fix Development – Patch development and testing
  4. Coordinated Disclosure – Disclosure timing agreed with the reporter
  5. Credit – Public acknowledgment unless anonymity is requested

Security Assurance & Verification

This project follows commonly accepted open source security best practices.
Security-related signals are publicly verifiable in this repository, including:

  • Automated dependency vulnerability scanning (Dependabot)
  • Static application security testing (GitHub CodeQL)
  • OpenSSF Scorecard monitoring
  • GitHub branch protection and required pull request reviews
  • Secret scanning for known credential patterns

Users and reviewers are encouraged to inspect the repository's Security tab for up-to-date results.


Threat Model & Scope

AWK is designed to mitigate risks related to:

  • Accidental exposure of secrets in AI-generated code
  • Unauthorized access between isolated AI worker sessions
  • Unreviewed automated code changes
  • Incomplete auditability of AI-driven workflows

AWK does not protect against:

  • Malicious actions by trusted contributors
  • Compromised GitHub accounts or access tokens
  • Vulnerabilities in third-party dependencies or AI model providers
  • Misconfiguration of repository permissions or branch protection

Security is a shared responsibility between the tool and its users.


Supply Chain Security

  • Source code and installation scripts are hosted in this repository
  • Releases are distributed via GitHub Releases
  • Installation scripts are versioned and subject to code review
  • Users are strongly encouraged to pin exact versions instead of using latest
  • No binaries or scripts are fetched from untrusted third-party sources at install time

Security Best Practices for Users

When using AWK (AI Workflow Kit), users are responsible for:

  • Reviewing all AI-generated code before merging
  • Managing GitHub tokens using least-privilege scopes
  • Enabling branch protection and required reviews
  • Keeping dependencies up to date
  • Monitoring audit logs and workflow outputs
  • Ensuring compliance with their organization's security policies

Built-in Security Features

AWK includes the following security-oriented design features:

  • Path isolation: Worker sessions cannot access Principal session data
  • Audit logging: All workflow operations are logged with session identifiers
  • Explicit workflow states: Issue/PR labels act as a visible state machine
  • GitHub-native controls: Integrates with branch protection and review rules
  • Secret detection: Detects common sensitive patterns in generated changes

Acknowledgments

We thank the following individuals for responsibly disclosing security issues:

  • (No disclosures yet — be the first!)

There aren’t any published security advisories