by alexdevassy · Agent Tool · ★ 64
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AI-Powered Vulnerability Impact Analyzer 🔍 🤖 Where AI meets Security to tell you if you really need to panic about that CVE 🌟 Introduction Traditional Software Composition Analysis (SCA) tools often generate excessive false positives by solely relying on Software Bill of Materials (SBOM) for vulnerability detection. This tool supercharges the SCA process by performing intelligent impact analysis on reported vulnerabilities. Using agentic AI powered by the open-source Mistral model, it: 📚 Analyzes CVE descriptions of vulnerable packages to pinpoint the components that cause vulnerability. 👮 Human-in-the-loop model to ensure accuracy and control 🔍 Searches your codebase for these components 🎯 Performs deep code analysis to verify actual vulnerability impact 💡 Reduces false positives by understanding context 🔒 Keeps your code secure with a fully on-premises AI solution—no data leaves your premises.
| Stars | 64 |
| Forks | 8 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 61.4610611295663/100 |
| Last Updated | 2025-02-22 |
| Created | 2025-02-18 |
| Platforms | python |
| Est. Tokens | ~51k |
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AI-Powered-Vulnerability-Impact-Analyzer is Vulnerability impact analyzer that reduces false positives in SCA tools by performing intelligent code analysis. Uses agentic AI with open source models to understand CVEs and verify actual vulnerabil. It is categorized as a Agent Tool with 64 GitHub stars.
AI-Powered-Vulnerability-Impact-Analyzer is primarily written in Python.
You can find installation instructions and usage details in the AI-Powered-Vulnerability-Impact-Analyzer GitHub repository at github.com/alexdevassy/AI-Powered-Vulnerability-Impact-Analyzer. The project has 64 stars and 8 forks, indicating an active community.
AI-Powered-Vulnerability-Impact-Analyzer is released under the MIT license, making it free to use and modify according to the license terms.