python-security

name	python-security
description	Guideline for designing, implementing, and verifying secure Python applications following OWASP Top 10 best practices. Use when the user wants to: (1) review Python code for security vulnerabilities, (2) design a secure Python application architecture, (3) implement security features (authentication, authorization, cryptography, input validation), (4) audit Python dependencies for known vulnerabilities, (5) create security checklists or verification plans, (6) fix security bugs or harden existing Python code, (7) set up security testing and static analysis (bandit, safety, semgrep), or (8) handle any Python security concern including injection prevention, secure deserialization, SSRF protection, secrets management, and secure deployment.
license	GFDL-1.3-or-later
metadata	{"author":"[e-mail]"}

Python Security Development Guide

Provide a structured approach to building secure Python applications, covering the OWASP Top 10, secure coding patterns, and verification checklists. Apply these guidelines throughout the secure development lifecycle — from threat modeling through deployment.

Secure Development Lifecycle

Phase 1: Threat Modeling and Secure Design

Before writing code, identify and mitigate threats at the design level:

• Identify trust boundaries — Map where untrusted data enters the system (HTTP requests, file uploads, database reads, environment variables, third-party APIs)
• Map data flows — Trace sensitive data (credentials, PII, tokens) through the system and verify protection at each stage
• Enumerate entry points — List all routes, endpoints, CLI arguments, message queue consumers, and cron jobs
• Map attack surfaces to OWASP Top 10 — Cross-reference each entry point against the OWASP categories in the quick reference table below

Design with security controls built-in:

• Centralized authentication and authorization middleware — never scatter auth checks across handlers
• Input validation at every trust boundary — validate early, reject invalid data before processing
• Least-privilege database access — use read-only connections where writes are not needed
• Defense in depth — layer multiple controls (input validation + parameterized queries + WAF)
• Fail securely — deny by default, require explicit grants

Phase 2: Secure Implementation

Critical Prohibitions

Never use these patterns. Violations are high-severity findings in any review.

Never	Instead
eval() / exec() with untrusted input	ast.literal_eval() or a dedicated parser
pickle.load() with untrusted data	json.loads() or validated schema (e.g., Pydantic)
yaml.load()	yaml.safe_load()
shell=True + user input in subprocess	subprocess.run([cmd, arg1, arg2]) with list args
os.system()	subprocess.run()
String formatting / f-strings in SQL	Parameterized queries (cursor.execute(sql, params))
random module for security purposes	secrets module
MD5 / SHA1 for password hashing	bcrypt or argon2-cffi
assert for security checks	if not condition: raise SecurityError(...)
Bare except: or except Exception:	except SpecificException: with proper handling
Hardcoded secrets in source code	Environment variables or secret manager (Vault, AWS SM)
DEBUG=True in production	Environment-specific configuration

Secure Implementation References

• For OWASP Top 10 details with vulnerable → secure code examples: See references/owasp-top-10.md
• For secure coding patterns organized by domain (input validation, auth, crypto, serialization, subprocess, file I/O, web frameworks): See references/secure-coding.md

Phase 3: Security Verification

Apply a layered verification approach:

1. Static Analysis — Detect common vulnerability patterns automatically
   • bandit — Python-specific security linter (AST-based)
   • semgrep — Pattern-based analysis with OWASP and Python rulesets
   • pylint — General linting with some security-relevant checks
2. Dependency Audit — Identify known vulnerabilities in third-party packages
   • pip-audit — Check installed packages against the OSV database
   • safety — Check against the Safety vulnerability database
3. Secrets Detection — Find leaked credentials and API keys
   • detect-secrets — Baseline-aware secrets scanner
4. Code Review — Apply the security review workflow and checklists
5. Security Testing — Write negative tests that verify rejection of malicious inputs; fuzz-test parsers and validators

Quick tool commands:

# Bandit — static analysis
bandit -r src/ -f json -o bandit-report.json

# pip-audit — dependency vulnerabilities
pip-audit

# Safety — alternative dependency check
safety check

# detect-secrets — secrets scanning
detect-secrets scan > .secrets.baseline

# Semgrep — advanced pattern matching
semgrep --config=p/python --config=p/owasp-top-ten src/

For complete verification checklists (code review, architecture review, dependency audit, deployment, testing, incident response): See references/security-checklist.md

Phase 4: Dependency and Deployment Security

Dependency Management

• Pin all dependencies with exact versions in requirements.txt
• Use hash verification: pip install --require-hashes -r requirements.txt
• Run pip-audit in CI/CD pipeline on every build
• Monitor for typosquatting — verify package names carefully before installing
• Review new dependencies before adding — check maintainership, download counts, known issues

Deployment Hardening

• Container security — Scan images with trivy; use minimal base images (distroless, alpine); run as non-root user
• HTTPS/TLS — Enforce TLS 1.2+ for all connections; redirect HTTP to HTTPS; set Strict-Transport-Security header
• Security headers — Configure Content-Security-Policy, X-Content-Type-Options: nosniff, X-Frame-Options: DENY
• Secrets at runtime — Inject secrets via environment variables or mounted volumes; never bake into images
• Least privilege — Run processes as non-root; use read-only filesystems where possible; limit network access
• Logging — Use structured logging (JSON); never log passwords, tokens, PII, or full stack traces to users; log authentication events and access denials for audit

OWASP Top 10:2025 Quick Reference

Map each OWASP 2025 category to Python-specific risks and primary mitigations:

#	Category	Python-Specific Risks	Primary Mitigation
A01	Broken Access Control	Missing @login_required / auth decorators, IDOR via sequential IDs, path traversal, SSRF via requests.get(user_url)	Centralized auth middleware, object-level permissions, pathlib.resolve(), URL allowlisting
A02	Security Misconfiguration	DEBUG=True in prod, CORS(origins="*"), Swagger/docs exposed, default SECRET_KEY, XXE via xml.etree	Environment-specific config, explicit CORS origins, disable docs in prod, defusedxml
A03	Software Supply Chain Failures	Unpinned deps, typosquatting, no SBOM, unvetted transitive deps, CI/CD secrets exposure	pip-audit in CI, pinned versions with hashes, SBOM generation, CI/CD hardening
A04	Cryptographic Failures	random module for tokens, MD5/SHA1 password hashing, hardcoded API keys, no encryption at rest	secrets module, bcrypt/argon2, env vars / secret manager, cryptography library
A05	Injection	SQL via f-strings/.format(), shell=True, Jinja2 `	safe/ SSTI,eval()/exec()`
A06	Insecure Design	No rate limiting, missing input validation layer, no abuse case modeling	Threat modeling, validation at boundaries (Pydantic), rate limiting middleware
A07	Authentication Failures	Weak session config, JWT algorithm="none" or HS256 with public key, no brute-force protection	Secure session settings, explicit algorithms=["RS256"], account lockout / rate limiting
A08	Software or Data Integrity Failures	pickle.loads() / yaml.load() deserialization, unsigned updates, CI/CD pipeline injection	json.loads() / yaml.safe_load(), signed artifacts, pinned CI actions with SHA
A09	Security Logging and Alerting Failures	Logging passwords/tokens, no auth event logging, missing alerting, no playbooks	Structured logging with field filtering, audit trail, alerting thresholds, honeytokens
A10	Mishandling of Exceptional Conditions	Bare except: pass, failing open, transaction rollback failures, sensitive info in errors	Specific exception types, context managers, centralized error handlers, fail-closed patterns

For detailed vulnerable → secure code examples for each category: See references/owasp-top-10.md

Security Review Workflow

Follow this procedure when reviewing Python code for security:

1. Scan for critical prohibitions — Check for any pattern in the "Critical Prohibitions" table above. Each match is an immediate high-severity finding.
2. Check input validation — Verify every entry point (route handler, CLI argument, file parser, queue consumer) validates and sanitizes input before processing.
3. Verify authentication and authorization — Confirm every endpoint requires authentication (unless explicitly public) and checks authorization for the specific resource being accessed.
4. Review data handling — Trace how secrets, PII, and sensitive data flow through the system. Verify encryption at rest and in transit, proper key management, and secure deletion.
5. Check error handling — Ensure errors do not leak stack traces, internal paths, database details, or configuration to users. Verify fail-secure behavior.
6. Audit dependencies — Run pip-audit and safety check. Flag any unpinned dependencies or packages with known CVEs.
7. Verify logging — Confirm no sensitive data (passwords, tokens, PII) appears in logs. Verify authentication events, authorization failures, and security-relevant actions are logged.
8. Run static analysis — Execute bandit -r src/ and review findings. Run semgrep with Python and OWASP rulesets for deeper analysis.
9. Report findings — For each finding, document: severity (Critical/High/Medium/Low), location (file:line), vulnerable code snippet, explanation of the risk, and recommended fix with code example.

Security Hardening Quick Commands

# === Static Analysis ===
pip install bandit && bandit -r src/ -f json -o bandit-report.json
pip install semgrep && semgrep --config=p/python --config=p/owasp-top-ten src/

# === Dependency Audit ===
pip install pip-audit && pip-audit
pip install safety && safety check

# === Secrets Detection ===
pip install detect-secrets && detect-secrets scan > .secrets.baseline

# === Pin Dependencies with Hashes ===
pip install pip-tools && pip-compile --generate-hashes requirements.in

# === Container Scanning ===
# trivy image <image-name>

Reference Files

Consult these files for detailed guidance beyond this overview:

• references/owasp-top-10.md — Detailed OWASP Top 10 coverage with Python-specific vulnerable → secure code examples for each category, including Django, Flask, and FastAPI patterns
• references/secure-coding.md — Secure coding patterns organized by domain: input validation, authentication, cryptography, serialization, subprocess execution, file operations, and web framework configuration (Django, Flask, FastAPI)
• references/security-checklist.md — Actionable verification checklists for code review, architecture review, dependency audit, deployment hardening, security testing, and incident response