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https://github.com/Shiva108/ai-llm-red-team-handbook.git
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shiva108
b3d3bac51f
- Extracted all code examples from handbook chapters - Organized into 15 attack categories - Created shared utilities (api_client, validators, logging, constants) - Added workflow orchestration scripts - Implemented install.sh for easy setup - Renamed all scripts to descriptive functional names - Added comprehensive README and documentation - Included pytest test suite and configuration
55 lines
1.3 KiB
Python
55 lines
1.3 KiB
Python
#!/usr/bin/env python3
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"""
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Continuous Compliance Monitoring
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Source: Chapter_40_Compliance_and_Standards
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Category: compliance
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"""
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import argparse
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import sys
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# Integration with CI/CD pipeline (GitHub Actions example)
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# .github/workflows/ai_compliance.yml
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name: AI Compliance Check
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on: [push, pull_request]
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jobs:
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compliance:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Run Compliance Validator
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run: |
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python scripts/compliance_validator.py \
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--check-logs \
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--check-model-card \
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--check-audit-trail
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- name: Upload Compliance Report
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uses: actions/upload-artifact@v3
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with:
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name: compliance-report
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path: compliance_report.md
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- name: Fail on Non-Compliance
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run: |
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if grep -q "NON-COMPLIANT" compliance_report.md; then
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echo "::error::Compliance violations detected"
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exit 1
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fi
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def main():
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"""Command-line interface."""
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")
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args = parser.parse_args()
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# TODO: Add main execution logic
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pass
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if __name__ == "__main__":
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main() |