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docs: Add Secret Detection Benchmarks section with performance metrics
- Added dedicated section showcasing secret detection benchmark results - Includes comparison table with recall rates and speeds - Links to detailed benchmark analysis - Highlights LLM detector's 84.4% recall on obfuscated secrets
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README.md
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README.md
@@ -67,6 +67,23 @@ If you find FuzzForge useful, please star the repo to support development 🚀
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---
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## 🔍 Secret Detection Benchmarks
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FuzzForge includes three secret detection workflows benchmarked on a controlled dataset of **32 documented secrets** (12 Easy, 10 Medium, 10 Hard):
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| Tool | Recall | Secrets Found | Speed |
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|------|--------|---------------|-------|
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| **LLM (gpt-5-mini)** | **84.4%** | 41 | 618s |
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| **LLM (gpt-4o-mini)** | 56.2% | 30 | 297s |
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| **Gitleaks** | 37.5% | 12 | 5s |
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| **TruffleHog** | 0.0% | 1 | 5s |
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📊 [Full benchmark results and analysis](backend/benchmarks/by_category/secret_detection/results/comparison_report.md)
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The LLM-based detector excels at finding obfuscated and hidden secrets through semantic analysis, while pattern-based tools (Gitleaks) offer speed for standard secret formats.
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---
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## 📦 Installation
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### Requirements
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