Bandit

Bandit is the most popular Python security linter, developed by the OpenStack Security Project and used by thousands of organizations including NASA, Red Hat, and IBM to secure Python applications. As a PyCQA (Python Code Quality Authority) project, it has become the de facto standard for Python security analysis.

What makes Bandit exceptional is its Python-specific security expertise - it understands Python idioms, common frameworks like Django and Flask, and the unique security challenges Python developers face. The tool provides actionable insights with minimal false positives through years of community refinement.

Python developers and security teams choose Bandit because it seamlessly integrates into existing workflows while providing immediate security value. From startups to enterprise applications, it catches vulnerabilities early in the development process when they’re cheapest to fix.

Key Features

• Python-Native Security Analysis - Deep understanding of Python syntax, libraries, and common security anti-patterns • OWASP Top 10 Coverage - Comprehensive detection of injection flaws, authentication issues, and security misconfigurations • Intelligent Severity Scoring - Risk-based prioritization with confidence levels and detailed vulnerability explanations • Seamless CI/CD Integration - Jenkins, GitHub Actions, GitLab CI support with configurable fail conditions • IDE & Editor Support - Real-time security feedback in VS Code, PyCharm, and other popular development environments • Flexible Rule Configuration - Custom security policies with rule exclusions and baseline management • Framework-Aware Scanning - Specialized checks for Django, Flask, SQLAlchemy, and other Python frameworks • Multiple Output Formats - JSON, XML, CSV, and human-readable reports for different integration needs

Pros and Cons

Pros

• Python-specific expertise with low false positive rates • Easy integration into existing Python development workflows • Active open source community with regular updates • Comprehensive framework support for popular Python libraries • Excellent documentation and learning resources

Cons

• Limited to Python codebases only • Static analysis cannot catch all runtime security issues • May require tuning to reduce noise in large codebases • Less comprehensive than commercial security testing platforms • Requires Python security knowledge to interpret results effectively

Get Started with Bandit

Secure your Python applications with the community’s trusted security linter. Visit bandit.readthedocs.io to start catching vulnerabilities before they reach production.