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Copilot AI commented Dec 27, 2025

All 17 GitHub workflow YAML files were corrupted with "uto-amazonq-review.properties.json" strings inserted between lines, breaking CI/CD execution. Additionally, the repository lacked comprehensive security scanning infrastructure as identified in the Amazon Q Code Review.

Changes

Critical Fixes

  • Workflow corruption: Removed malformed strings from all .github/workflows/*.{yml,yaml} files and validated YAML syntax

Security Infrastructure

  • Bandit integration: Added Python security linting (>=1.7.5,<1.8) scanning all severity levels with strict failure enforcement
  • Dependabot: Configured weekly automated dependency updates
  • Enhanced workflow: Updated auto-sec-scan.yml with scheduled scans, proper Python/Poetry environment setup, and CodeQL analysis

Configuration

  • .bandit: Excluded test/, docs/, examples/ directories with correct relative paths
  • .github/dependabot.yml: Weekly pip ecosystem scanning with security labels

Documentation

  • SECURITY_ASSESSMENT.md: Comprehensive security analysis including scan results (0 medium/high issues, 19/19 tests passing, 56/56 modules pass mypy), OWASP/CWE compliance mapping, 90-day review schedule, and AI code review security considerations

Security Scan Results

# Bandit - All severity levels
Total lines: 31,640
High: 0, Medium: 0, Low: 37 (B101:assert_used in tests only)

# CodeQL
Alerts: 0

# Dependencies
All project dependencies current and secure (certifi 2025.10.5, jinja2 3.1.6, idna 3.10)

All validations passing: tests (19/19), type checking (56/56), security scans clean.

Original prompt

This section details on the original issue you should resolve

<issue_title>Amazon Q Code Review - 2025-12-08</issue_title>
<issue_description># Amazon Q Code Review Report

This review was triggered after GitHub Copilot agent workflows completed.

Amazon Q Code Review Report

Review Date: 2025-12-08 17:37:36 UTC

Code Quality Assessment

Following the GitHub Copilot agent reviews, Amazon Q provides additional insights:

Code Structure Analysis

  • Total source files analyzed: 62

Security Considerations

  • Credential scanning: Check for hardcoded secrets
  • Dependency vulnerabilities: Review package versions
  • Code injection risks: Validate input handling

Performance Optimization Opportunities

  • Algorithm efficiency: Review computational complexity
  • Resource management: Check for memory leaks and resource cleanup
  • Caching opportunities: Identify repeated computations

Architecture and Design Patterns

  • Design patterns usage: Verify appropriate pattern application
  • Separation of concerns: Check module boundaries
  • Dependency management: Review coupling and cohesion

Integration with Previous Reviews

This review complements the GitHub Copilot agent findings with:

  • Additional security analysis
  • AWS best practices recommendations
  • Performance optimization suggestions
  • Enterprise architecture patterns

Next Steps

  1. Review findings from both GitHub Copilot and Amazon Q
  2. Prioritize issues based on severity and impact
  3. Create action items for high-priority findings
  4. Schedule follow-up reviews for resolved items

Review Context

  • Triggered by: Complete CI/CD Agent Review Pipeline
  • Repository: HyperionGray/python-chrome-devtools-protocol
  • Branch: master
  • Commit: d86f32a

Related Reviews

Check for related issues with these labels:

  • code-cleanliness - Code structure and organization
  • test-coverage - Test quality and Playwright usage
  • documentation - Documentation completeness

Instructions for Amazon Q Integration

To enable full Amazon Q integration:

  1. Set up AWS credentials in repository secrets:

    • AWS_ACCESS_KEY_ID
    • AWS_SECRET_ACCESS_KEY
  2. Install Amazon Q Developer CLI (when available):

    • Follow AWS documentation for Amazon Q setup
    • Configure repository access
  3. Enable Amazon CodeWhisperer for security scanning

  4. Configure custom review rules based on your needs

Action Items

  • Review Amazon Q findings
  • Compare with GitHub Copilot recommendations
  • Prioritize and assign issues
  • Implement high-priority fixes
  • Update documentation as needed

This issue was automatically generated by the Amazon Q Review workflow.
</issue_description>

Comments on the Issue (you are @copilot in this section)


✨ Let Copilot coding agent set things up for you — coding agent works faster and does higher quality work when set up for your repo.

Copilot AI and others added 3 commits December 27, 2025 07:14
Co-authored-by: hyp3ri0n-ng <3106718+hyp3ri0n-ng@users.noreply.github.com>
Co-authored-by: hyp3ri0n-ng <3106718+hyp3ri0n-ng@users.noreply.github.com>
Co-authored-by: hyp3ri0n-ng <3106718+hyp3ri0n-ng@users.noreply.github.com>
python-version: '3.11'

- name: Install Poetry
uses: snok/install-poetry@v1

Check warning

Code scanning / CodeQL

Unpinned tag for a non-immutable Action in workflow Medium

Unpinned 3rd party Action 'Security Scan on PR' step
Uses Step
uses 'snok/install-poetry' with ref 'v1', not a pinned commit hash
Copilot AI and others added 3 commits December 27, 2025 07:21
…tion

Co-authored-by: hyp3ri0n-ng <3106718+hyp3ri0n-ng@users.noreply.github.com>
… considerations

Co-authored-by: hyp3ri0n-ng <3106718+hyp3ri0n-ng@users.noreply.github.com>
Co-authored-by: hyp3ri0n-ng <3106718+hyp3ri0n-ng@users.noreply.github.com>
Copilot AI changed the title [WIP] Review code quality and security for Amazon Q Fix corrupted workflow files and implement comprehensive security scanning Dec 27, 2025
Copilot AI requested a review from hyp3ri0n-ng December 27, 2025 07:27
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Amazon Q Code Review - 2025-12-08

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