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Author: codelion

_posts/2023-12-12-AutoFix-Automated-Vulnerability-Remediation-using-Static-Analysis-and-LLMs.md

@@ -7,7 +7,7 @@ In the rapidly evolving world of software development, security remains a paramo
 
 ![an illustration showing clean design representing static code analysis](../images/An-illustration-depicting-a-modern-clean-design-with-symbols-representing-static-code-analysis-and-artificial-intelligence.jpeg)
 
-![AutoFix](https://github.com/lambdasec/autofix) is not just another vulnerability scanner; it's a sophisticated blend of static analysis and Large Language Models (LLMs) designed to automatically detect and remediate software vulnerabilities. By leveraging the capabilities of existing static analyzers, like Semgrep, and code LLMs, such as Starcoder, AutoFix offers a unique approach to securing software applications.
+[AutoFix](https://github.com/lambdasec/autofix) is not just another vulnerability scanner; it's a sophisticated blend of static analysis and Large Language Models (LLMs) designed to automatically detect and remediate software vulnerabilities. By leveraging the capabilities of existing static analyzers, like Semgrep, and code LLMs, such as Starcoder, AutoFix offers a unique approach to securing software applications.
 
 The key to AutoFix's effectiveness lies in its methodology. Unlike traditional tools that solely identify issues, AutoFix goes a step further. It uses the insights from static analysis as a guide to craft specific prompts for the LLM, leading to tailored fixes for identified vulnerabilities. This synergy between static analysis and AI not only enhances accuracy but also speeds up the remediation process, a critical factor in today's fast-paced development cycles.