Security Review Skill

Identify exploitable security vulnerabilities in code. Report only HIGH CONFIDENCE findings—clear vulnerable patterns with attacker-controlled input.

Scope: Research vs. Reporting

CRITICAL DISTINCTION:

• Report on: Only the specific file, diff, or code provided by the user
• Research: The ENTIRE codebase to build confidence before reporting

Before flagging any issue, you MUST research the codebase to understand:

• Where does this input actually come from? (Trace data flow)
• Is there validation/sanitization elsewhere?
• How is this configured? (Check settings, config files, middleware)
• What framework protections exist?

Do NOT report issues based solely on pattern matching. Investigate first, then report only what you're confident is exploitable.

Confidence Levels

Level	Criteria	Action
HIGH	Vulnerable pattern + attacker-controlled input confirmed	Report with severity
MEDIUM	Vulnerable pattern, input source unclear	Note as "Needs verification"
LOW	Theoretical, best practice, defense-in-depth	Do not report

Do Not Flag

General Rules

• Test files (unless explicitly reviewing test security)
• Dead code, commented code, documentation strings
• Patterns using constants or server-controlled configuration
• Code paths that require prior authentication to reach (note the auth requirement instead)

Server-Controlled Values (NOT Attacker-Controlled)

These are configured by operators, not controlled by attackers:

Source	Example	Why It's Safe
Django settings	settings.API_URL, settings.ALLOWED_HOSTS	Set via config/env at deployment
Environment variables	os.environ.get('DATABASE_URL')	Deployment configuration
Config files	config.yaml, app.config['KEY']	Server-side files
Framework constants	django.conf.settings.*	Not user-modifiable
Hardcoded values	BASE_URL = "https://api.internal"	Compile-time constants

SSRF Example - NOT a vulnerability:

# SAFE: URL comes from Django settings (server-controlled)
response = requests.get(f"{settings.SEER_AUTOFIX_URL}{path}")

SSRF Example - IS a vulnerability:

# VULNERABLE: URL comes from request (attacker-controlled)
response = requests.get(request.GET.get('url'))

Framework-Mitigated Patterns

Check language guides before flagging. Common false positives:

Pattern	Why It's Usually Safe
Django {{ variable }}	Auto-escaped by default
React {variable}	Auto-escaped by default
Vue {{ variable }}	Auto-escaped by default
User.objects.filter(id=input)	ORM parameterizes queries
cursor.execute("...%s", (input,))	Parameterized query
innerHTML = "<b>Loading...</b>"	Constant string, no user input

Only flag these when:

• Django: {{ var|safe }}, {% autoescape off %}, mark_safe(user_input)
• React: dangerouslySetInnerHTML={{__html: userInput}}
• Vue: v-html="userInput"
• ORM: .raw(), .extra(), RawSQL() with string interpolation

Review Process

1. Detect Context

What type of code am I reviewing?

Code Type	Load These References
API endpoints, routes	authorization.md, authentication.md, injection.md
Frontend, templates	xss.md, csrf.md
File handling, uploads	file-security.md
Crypto, secrets, tokens	cryptography.md, data-protection.md
Data serialization	deserialization.md
External requests	ssrf.md
Business workflows	business-logic.md
GraphQL, REST design	api-security.md
Config, headers, CORS	misconfiguration.md
CI/CD, dependencies	supply-chain.md
Error handling	error-handling.md
Audit, logging	logging.md

2. Load Language Guide

Based on file extension or imports:

Indicators	Guide
.py, django, flask, fastapi	languages/python.md
.js, .ts, express, react, vue, next	languages/javascript.md
.go, go.mod	languages/go.md
.rs, Cargo.toml	languages/rust.md
.java, spring, @Controller	languages/java.md

3. Load Infrastructure Guide (if applicable)

File Type	Guide
Dockerfile, .dockerignore	infrastructure/docker.md
K8s manifests, Helm charts	infrastructure/kubernetes.md
.tf, Terraform	infrastructure/terraform.md
GitHub Actions, .gitlab-ci.yml	infrastructure/ci-cd.md
AWS/GCP/Azure configs, IAM	infrastructure/cloud.md

4. Research Before Flagging

For each potential issue, research the codebase to build confidence:

• Where does this value actually come from? Trace the data flow.
• Is it configured at deployment (settings, env vars) or from user input?
• Is there validation, sanitization, or allowlisting elsewhere?
• What framework protections apply?

Only report issues where you have HIGH confidence after understanding the broader context.

5. Verify Exploitability

For each potential finding, confirm:

Is the input attacker-controlled?

Attacker-Controlled (Investigate)	Server-Controlled (Usually Safe)
request.GET, request.POST, request.args	settings.X, app.config['X']
request.json, request.data, request.body	os.environ.get('X')
request.headers (most headers)	Hardcoded constants
request.cookies (unsigned)	Internal service URLs from config
URL path segments: /users/<id>/	Database content from admin/system
File uploads (content and names)	Signed session data
Database content from other users	Framework settings
WebSocket messages

Does the framework mitigate this?

• Check language guide for auto-escaping, parameterization
• Check for middleware/decorators that sanitize

Is there validation upstream?

• Input validation before this code
• Sanitization libraries (DOMPurify, bleach, etc.)

6. Report HIGH Confidence Only

Skip theoretical issues. Report only what you've confirmed is exploitable after research.

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Severity Classification

Severity	Impact	Examples
Critical	Direct exploit, severe impact, no auth required	RCE, SQL injection to data, auth bypass, hardcoded secrets
High	Exploitable with conditions, significant impact	Stored XSS, SSRF to metadata, IDOR to sensitive data
Medium	Specific conditions required, moderate impact	Reflected XSS, CSRF on state-changing actions, path traversal
Low	Defense-in-depth, minimal direct impact	Missing headers, verbose errors, weak algorithms in non-critical context

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Quick Patterns Reference

Always Flag (Critical)

eval(user_input)           # Any language
exec(user_input)           # Any language
pickle.loads(user_data)    # Python
yaml.load(user_data)       # Python (not safe_load)
unserialize($user_data)    # PHP
deserialize(user_data)     # Java ObjectInputStream
shell=True + user_input    # Python subprocess
child_process.exec(user)   # Node.js

Always Flag (High)

innerHTML = userInput              # DOM XSS
dangerouslySetInnerHTML={user}     # React XSS
v-html="userInput"                 # Vue XSS
f"SELECT * FROM x WHERE {user}"    # SQL injection
`SELECT * FROM x WHERE ${user}`    # SQL injection
os.system(f"cmd {user_input}")     # Command injection

Always Flag (Secrets)

password = "hardcoded"
api_key = "sk-..."
AWS_SECRET_ACCESS_KEY = "..."
private_key = "-----BEGIN"

Check Context First (MUST Investigate Before Flagging)

# SSRF - ONLY if U