Python Patterns
84+ vulnerability patterns for Python applications including Django, Flask, FastAPI, and data science libraries.
Overview
Bloodhound provides comprehensive Python security analysis covering web frameworks, data processing pipelines, and common security anti-patterns.
Injection Vulnerabilities
SQL Injection
String formatting in SQL queries allows database manipulation.
Command Injection
User input in shell commands enables arbitrary command execution.
Code Injection (eval)
Using eval() or exec() with user input enables arbitrary code execution.
Insecure Deserialization
Critical Risk
Insecure Pickle Deserialization
Unpickling untrusted data can execute arbitrary code.
YAML Deserialization
PyYAML full_load can instantiate arbitrary Python objects.
Path Traversal
Path Traversal
User-controlled paths can access files outside intended directories.
Django Security
Django Template XSS
Using |safe filter or mark_safe with user input bypasses auto-escaping.
Django Raw SQL
Raw SQL queries with string formatting bypass ORM protections.
Flask Security
Flask SSTI
Server-side template injection via render_template_string.
Flask Debug Mode in Production
Debug mode exposes Werkzeug debugger allowing RCE.