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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
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
#!/usr/bin/env python3
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"""
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Validating Training Data Authenticity
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Source: Chapter_13_Data_Provenance_and_Supply_Chain_Security
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Category: supply_chain
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"""
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import argparse
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import sys
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def verify_data_sources(data_manifest):
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"""Check that training data comes from expected sources"""
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issues = []
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for data_item in data_manifest:
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# Check source URL is legitimate
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if not is_trusted_source(data_item['source_url']):
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issues.append(f"Untrusted source: {data_item['source_url']}")
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# Verify data checksum
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actual_hash = compute_hash(data_item['file_path'])
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if actual_hash != data_item['expected_hash']:
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issues.append(f"Data integrity violation: {data_item['file_path']}")
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# Check license compliance
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if not is_license_compatible(data_item['license']):
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issues.append(f"License issue: {data_item['license']}")
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return issues
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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() |