Unlocking the Future of Autonomous AI Pentesting with Strix: Key Insights from My Extensive Testing
In a recent deep dive, I spent nearly 100 hours testing Strix, an AI pentesting tool, with 18 different LLM models. My goal? To determine which model performs best and what that means for autonomous AI pentesting.
Key Findings:
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Testing Methodology:
- Utilized a controlled test server with two web applications.
- Strix was deployed with specific parameters to ensure rigorous evaluation.
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Results Overview:
- GLM 5.1 emerged as the surprising top performer, outperforming others despite its cost.
- Budget models showed that spending less often resulted in subpar performance.
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Insights on Specific Models:
- Anthropic models underperformed, raising questions about their value.
- Notable mentions include step-3.5-flash and kimi-k2.5 for smaller setups.
The landscape of autonomous AI pentesting is evolving quickly. Stay ahead by exploring my full findings and insights!
🔗 Read the complete results and download the CSV file for deeper analysis! Share your thoughts below on which models intrigue you most! #AI #Pentesting #AutonomousAI #Cybersecurity
