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LLMGrep combines the precision of Semgrep's static analysis with the power of Large Language Models to deliver comprehensive security scanning, interactive vulnerability discussions, and intelligent rule generation capabilities.

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LLMGrep Security Analysis Tool

LLMGrep

Advanced Security Analysis Powered by Large Language Models and Semgrep

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LLMGrep Demo

Intelligent Security Analysis

LLMGrep combines the precision of Semgrep's static analysis with the power of Large Language Models to deliver comprehensive security scanning, interactive vulnerability discussions, and intelligent rule generation capabilities.

Static Analysis LLM Intelligence Custom Rules
Semgrep-powered code scanning with pattern matching AI-driven vulnerability assessment Automated security rule generation

Core Features

Analysis Engine

  • Dual-engine security scanning
  • Pattern-based vulnerability detection
  • Machine learning insights
  • Real-time code analysis
  • Comprehensive security reports

Intelligence Layer

  • Context-aware security chat
  • Vulnerability explanation
  • Code improvement suggestions
  • Security best practices
  • Custom rule generation

Quick Start

# Clone repository
git clone https://github.com/codebytemirza/LLMgrep.git

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env

# Launch application
streamlit run app.py
Docker Deployment
docker build -t llmgrep .
docker run -p 8501:8501 --env-file .env llmgrep

Architecture

Component Technology Purpose
Static Analysis Semgrep Pattern matching & vulnerability detection
AI Engine Groq LLM Intelligent code analysis
Interface Streamlit Interactive web application

Security Analysis Workflow

  1. Code Input

    • Direct code entry
    • File upload support
    • Multi-file analysis
  2. Analysis Process

    • Semgrep pattern scanning
    • LLM-based code review
    • Vulnerability assessment
  3. Results & Insights

    • Detailed findings report
    • Security recommendations
    • Interactive consultation

Advanced Configuration

Parameter Description Default
Model LLM model selection deepseek-r1
Temperature Response variation 0.1
Rules Custom Semgrep rules Optional
Metrics Performance tracking Disabled

Development

# Setup development environment
python -m venv .venv
source .venv/bin/activate

# Install development dependencies
pip install -r requirements-dev.txt

Contributing

We welcome contributions to LLMGrep. Please review our Contributing Guidelines before submitting pull requests.

Contribution Process

  1. Fork repository
  2. Create feature branch
  3. Implement changes
  4. Submit pull request

Code Standards

  • PEP 8 compliance
  • Comprehensive testing
  • Documentation updates
  • Clean commit history

License

LLMGrep is released under the MIT License. See the LICENSE file for details.

Technology Stack

Semgrep Groq Streamlit

Built with precision by @codebytemirza

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LLMGrep combines the precision of Semgrep's static analysis with the power of Large Language Models to deliver comprehensive security scanning, interactive vulnerability discussions, and intelligent rule generation capabilities.

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