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Perform static taint analysis on Python code to detect security vulnerabilities.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Lanalyzer MCP Server" yet — see the docs or source repo.
Run static taint analysis on this Python web service code. Identify dangerous data flows from user input to database queries, file operations, or command execution, and output findings by vulnerability type, propagation path, and remediation advice.
A list of potential vulnerabilities with sources, propagation paths, dangerous sinks, and remediation suggestions.
Analyze the following Python script for command injection risks, focusing on whether external input flows into subprocess, os.system, or similar interfaces, and explain which paths are exploitable.
Command injection findings, exploitable paths, and safer implementation alternatives.
Inspect this Python file upload handling code. Track whether user-provided filenames, paths, and content flow into sensitive filesystem operations, and identify path traversal or arbitrary file write risks.
Filesystem-related taint paths, risk levels, and input validation recommendations.
Analyze AI security, scan vulnerabilities, and monitor code leaks efficiently.
Statically analyze Python code structure and dependencies without running the code.
Analyze, match, and transform code structures across multiple programming languages.
Run MegaLinter via MCP for linting, config checks, and quality analysis.
Analyze URLs, files, IPs, and domains for faster security investigation.
Analyze Android and iOS app packages for security issues via natural language.