Update 2025-2-24-AutoGrep-Automated-Generation-and-Filtering-of-Semgrep-Rules-from-Vulnerability-Patches.md

Author: codelion

_posts/2025-2-24-AutoGrep-Automated-Generation-and-Filtering-of-Semgrep-Rules-from-Vulnerability-Patches.md

@@ -1,8 +1,8 @@
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-title: "AutoGrep: Automated Generation and Filtering of Semgrep Rules from Vulnerability Patches"
+title: "Autogrep: Automated Generation and Filtering of Semgrep Rules from Vulnerability Patches"
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-This article presents [AutoGrep](https://github.com/lambdasec/autogrep), an automated system for generating and filtering high-quality security rules for static analysis tools. Motivated by recent licensing changes in the Semgrep ecosystem, AutoGrep addresses the critical need for maintaining and expanding permissively licensed security rules. By leveraging Large Language Models (LLMs) and a multi-stage filtering pipeline, AutoGrep transforms vulnerability patches into precise, generalizable security rules while eliminating duplicates and overly specific patterns.
+This article presents [Autogrep](https://github.com/lambdasec/autogrep), an automated system for generating and filtering high-quality security rules for static analysis tools. Motivated by recent licensing changes in the Semgrep ecosystem, Autogrep addresses the critical need for maintaining and expanding permissively licensed security rules. By leveraging Large Language Models (LLMs) and a multi-stage filtering pipeline, Autogrep transforms vulnerability patches into precise, generalizable security rules while eliminating duplicates and overly specific patterns.
 
 ## 1. Introduction
 
@@ -27,7 +27,7 @@ We make the following contributions:
 
 ### 2.1 Overview
 
-AutoGrep consists of two main components:
+Autogrep consists of two main components:
 
 1. **Rule Generation Pipeline**: Analyzes vulnerability patches and generates corresponding Semgrep rules using LLM-based pattern extraction
 2. **Rule Filtering System**: Validates and filters generated rules through multiple quality checks
@@ -138,7 +138,7 @@ Compared to traditional manual rule creation:
 
 ## 6. Conclusion and Future Work
 
-AutoGrep demonstrates the feasibility of automated security rule generation and filtering at scale. The system successfully processes a large dataset of vulnerability patches to produce a focused set of high-quality, permissively licensed security rules.
+Autogrep demonstrates the feasibility of automated security rule generation and filtering at scale. The system successfully processes a large dataset of vulnerability patches to produce a focused set of high-quality, permissively licensed security rules.
 
 ### Future Work