mirror of
https://github.com/Shiva108/ai-llm-red-team-handbook.git
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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
33 lines
867 B
Python
33 lines
867 B
Python
#!/usr/bin/env python3
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"""
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generate_impersonation_message() Function
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Source: Chapter_24_Social_Engineering_LLMs
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Category: social_engineering
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"""
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import argparse
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import sys
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# Purpose: Create message matching target's style
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# Input: Target name, role, style profile, objective
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# Process
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# 1. Build style description from profile
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# 2. Construct LLM prompt with style requirements
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# 3. Include attack objective naturally
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# 4. Generate message matching all patterns
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# Output: Convincing impersonation message
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# Success rate: 80-90% fool recipients
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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() |