vuln-patterns-injection

To detect SQL injection vulnerabilities in Python code, this skill analyzes dangerous execution functions, identifies user input sources from HTTP requests or config files, and validates the presence of parameterized queries and input sanitization measures.

The best way to audit Python code for command injection flaws is to trace user input to dangerous sinks like subprocess with shell=True, checking if proper security measures and input validation are implemented before execution.

Yes, you can scan Python applications for code injection and template injection risks by analyzing dangerous functions like eval() and exec(), validating sanitization measures, and identifying sources of user input that reach these sinks.

Yes, this injection detection skill covers CWE-77, CWE-78, CWE-89, CWE-94, CWE-95, and CWE-917 for Python applications by identifying user input sources, analyzing dangerous sinks, and validating sanitization measures.

To check if user input from HTTP requests reaches dangerous Python sinks, this skill identifies sources of user input, analyzes functions like eval() and subprocess with shell=True, and validates existing sanitization measures.

Common sources of user input analyzed during Python code audits include HTTP requests, LLM outputs, and configuration files, which are traced to dangerous sinks to identify potential command injection, SQL injection, and code injection vulnerabilities.