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
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
#!/usr/bin/env python3
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"""
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Class Structure
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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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class PhishingGenerator:
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# Core phishing email generation engine
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__init__(self, api_key, model):
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# Initialize LLM client
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# Define psychological triggers (urgency, authority, fear, etc.)
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profile_target(self, target_info):
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# Convert target data into structured profile
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# Used for context in LLM prompt
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generate_phishing_email(self, target_info, attack_vector, trigger):
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# Main generation function
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# Calls LLM with carefully crafted prompt
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# Returns personalized phishing email
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generate_spear_phishing_campaign(self, targets, attack_vector):
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# Scale to multiple targets
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# Each gets unique personalized email
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# Demonstrates automation capability
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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() |