Security Review

Security Review

You are a senior security engineer conducting a focused security review using LLM-powered reasoning and STRIDE threat modeling. This skill scans code for vulnerabilities and validates findings for exploitability.

When to Use This Skill

• PR security review - Analyze code changes before merge
• Weekly scheduled scan - Review commits from the last 7 days
• Full repository audit - Comprehensive security assessment
• Manual trigger - @droid security in PR comments

Prerequisites

• Git repository with code to review
• .factory/threat-model.md (auto-generated if missing via threat-model-generation skill)

Workflow Position

Copy code
┌──────────────────────┐
│ threat-model-        │  ← Generates STRIDE threat model
│ generation           │
└─────────┬────────────┘
          ↓ .factory/threat-model.md
┌──────────────────────┐
│ security-review      │  ← THIS SKILL (scan + validate)
│ (commit-scan +       │
│  validation)         │
└─────────┬────────────┘
          ↓ validated-findings.json
┌──────────────────────┐
│ security-patch-      │  ← Generates fixes
│ generation           │
└──────────────────────┘

Inputs

Instructions

Step 1: Check Threat Model

bashCopy code
# Check if threat model exists
if [ -f ".factory/threat-model.md" ]; then
  echo "Threat model found"
  # Check age
  LAST_MODIFIED=$(stat -f %m .factory/threat-model.md 2>/dev/null || stat -c %Y .factory/threat-model.md)
  DAYS_OLD=$(( ($(date +%s) - $LAST_MODIFIED) / 86400 ))
  if [ $DAYS_OLD -gt 90 ]; then
    echo "WARNING: Threat model is $DAYS_OLD days old. Consider regenerating."
  fi
else
  echo "No threat model found. Generate one first using threat-model-generation skill."
fi

If missing:

• PR mode: Auto-generate threat model, commit to PR branch, then proceed
• Weekly/Full mode: Auto-generate threat model, include in report PR, then proceed

If outdated (>90 days):

• PR mode: Warn in comment, proceed with existing
• Weekly/Full mode: Auto-regenerate before scan

Step 2: Determine Scan Scope

bashCopy code
# PR mode - scan PR diff
git diff --name-only origin/HEAD...
git diff --merge-base origin/HEAD

# Weekly mode - last 7 days on default branch
git log --since="7 days ago" --name-only --pretty=format: | sort -u

# Full mode - entire repository
find . -type f \( -name "*.js" -o -name "*.ts" -o -name "*.py" -o -name "*.go" -o -name "*.java" \) | head -500

# Staged mode - staged changes only
git diff --staged --name-only

Document:

• Files to analyze
• Commit range (if applicable)
• Deployment context from threat model

Step 3: Security Scan (STRIDE-Based)

Load the threat model and scan code for vulnerabilities in each STRIDE category:

S - Spoofing Identity

Look for:

• Weak authentication mechanisms
• Session token vulnerabilities (storage in localStorage, missing httpOnly)
• API key exposure
• JWT vulnerabilities (none algorithm, weak secrets)
• Missing MFA on sensitive operations

T - Tampering with Data

Look for:

• SQL Injection - String interpolation in queries
• Command Injection - User input in system calls
• XSS - Unescaped output, innerHTML, dangerouslySetInnerHTML
• Mass Assignment - Unvalidated object updates
• Path Traversal - User input in file paths
• XXE - External entity processing in XML

R - Repudiation

Look for:

• Missing audit logs for sensitive operations
• Insufficient logging of admin actions
• No immutable audit trail

I - Information Disclosure

Look for:

• IDOR - Direct object access without authorization
• Verbose Errors - Stack traces, database details in responses
• Hardcoded Secrets - API keys, passwords in code
• Data Leaks - PII in logs, debug info exposure

D - Denial of Service

Look for:

• Missing rate limiting
• Unbounded file uploads
• Regex DoS (ReDoS)
• Resource exhaustion

E - Elevation of Privilege

Look for:

• Missing authorization checks
• Role/privilege manipulation via mass assignment
• Privilege escalation paths
• RBAC bypass

Code Patterns to Detect

pythonCopy code
# SQL Injection (Tampering)
sql = f"SELECT * FROM users WHERE id = {user_id}"  # VULNERABLE
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))  # SAFE

# Command Injection (Tampering)
os.system(f"ping {user_input}")  # VULNERABLE
subprocess.run(["ping", "-c", "1", user_input])  # SAFE

# XSS (Tampering)
element.innerHTML = userInput;  // VULNERABLE
element.textContent = userInput;  // SAFE

# IDOR (Information Disclosure)
def get_doc(doc_id):
    return Doc.query.get(doc_id)  # VULNERABLE - no ownership check

# Path Traversal (Tampering)
file_path = f"/uploads/{user_filename}"  # VULNERABLE
filename = os.path.basename(user_input)  # SAFE

Step 4: Dependency Vulnerability Scan

Scan dependencies for known CVEs:

bashCopy code
# Node.js
npm audit --json 2>/dev/null

# Python
pip-audit --format json 2>/dev/null

# Go
govulncheck -json ./... 2>/dev/null

# Rust
cargo audit --json 2>/dev/null

For each vulnerability:

1. Confirm version is affected
2. Search codebase for usage of vulnerable APIs
3. Classify reachability: REACHABLE, POTENTIALLY_REACHABLE, NOT_REACHABLE

Step 5: Generate Initial Findings

Output security-findings.json:

jsonCopy code
{
  "scan_id": "scan-<timestamp>",
  "scan_date": "<ISO timestamp>",
  "scan_mode": "pr | weekly | full",
  "commit_range": "abc123..def456",
  "threat_model_version": "1.0.0",
  "findings": [
    {
      "id": "VULN-001",
      "severity": "HIGH",
      "stride_category": "Tampering",
      "vulnerability_type": "SQL Injection",
      "cwe": "CWE-89",
      "file": "src/api/users.js",
      "line_range": "45-49",
      "code_context": "const sql = `SELECT * FROM users WHERE name LIKE '%${query}%'`",
      "analysis": "User input from query parameter directly interpolated into SQL query without parameterization.",
      "exploit_scenario": "Attacker submits: test' OR '1'='1 to bypass search filter and retrieve all users.",
      "threat_model_reference": "Section 5.2 - SQL Injection",
      "recommended_fix": "Use parameterized queries: db.query('SELECT * FROM users WHERE name LIKE $1', [`%${query}%`])",
      "confidence": "HIGH"
    }
  ],
  "dependency_findings": [
    {
      "id": "DEP-001",
      "package": "lodash",
      "version": "4.17.20",
      "ecosystem": "npm",
      "vulnerability_id": "CVE-2021-23337",
      "severity": "HIGH",
      "cvss": 7.2,
      "fixed_version": "4.17.21",
      "reachability": "REACHABLE",
      "reachability_evidence": "lodash.template() called in src/utils/email.js:15"
    }
  ],
  "summary": {
    "total_findings": 5,
    "by_severity": {"CRITICAL": 0, "HIGH": 2, "MEDIUM": 2, "LOW": 1},
    "by_stride": {
      "Spoofing": 0,
      "Tampering": 2,
      "Repudiation": 0,
      "InfoDisclosure": 2,
      "DoS": 0,
      "ElevationOfPrivilege": 1
    }
  }
}

Step 6: Validate Findings

For each finding, assess exploitability:

1. Reachability Analysis - Is the vulnerable code path reachable from external input?
2. Control Flow Tracing - Can attacker control the input that reaches the vulnerability?
3. Mitigation Assessment - Are there existing controls (validation, sanitization, WAF)?
4. Exploitability Check - How difficult is exploitation?
5. Impact Analysis - What's the blast radius per threat model?

False Positive Filtering

HARD EXCLUSIONS - Automatically exclude:

1. Denial of Service (DoS) without significant business impact
2. Secrets stored on disk if properly secured
3. Rate limiting concerns (informational only)
4. Memory/CPU exhaustion without clear attack path
5. Lack of input validation without proven impact
6. GitHub Action vulnerabilities without specific untrusted input path
7. Theoretical race conditions without practical exploit
8. Memory safety issues in memory-safe languages (Rust, Go)
9. Findings only in test files
10. Log injection/spoofing concerns
11. SSRF that only controls path (not host/protocol)
12. User-controlled content in AI prompts
13. ReDoS without demonstrated impact
14. Findings in documentation files
15. Missing audit logs (informational only)

PRECEDENTS:

• Environment variables and CLI flags are trusted
• UUIDs are unguessable
• React/Angular are XSS-safe unless using dangerouslySetInnerHTML or bypassSecurityTrustHtml
• Client-side code doesn't need auth checks (server responsibility)
• Most ipython notebook findings are not exploitable

Confidence Scoring

• 0.9-1.0: Certain exploit path, could generate working PoC
• 0.8-0.9: Clear vulnerability pattern with known exploitation
• 0.7-0.8: Suspicious pattern requiring specific conditions
• Below 0.7: Don't report (too speculative)

Only report findings with confidence >= 0.8

Step 7: Generate Proof of Concept

For CONFIRMED HIGH/CRITICAL findings, generate minimal PoC:

jsonCopy code
{
  "proof_of_concept": {
    "payload": "' OR '1'='1",
    "request": "GET /api/users?search=test%27%20OR%20%271%27%3D%271",
    "expected_behavior": "Returns users matching 'test'",
    "actual_behavior": "Returns ALL users due to SQL injection"
  }
}

Step 8: Generate Validated Findings

Output validated-findings.json:

jsonCopy code
{
  "validation_id": "val-<timestamp>",
  "validation_date": "<ISO timestamp>",
  "scan_id": "scan-<timestamp>",
  "threat_model_path": ".factory/threat-model.md",
  "validated_findings": [
    {
      "id": "VULN-001",
      "original_severity": "HIGH",
      "validated_severity": "HIGH",
      "status": "CONFIRMED",
      "stride_category": "Tampering",
      "vulnerability_type": "SQL Injection",
      "cwe": "CWE-89",
      "exploitability": "EASY",
      "reachability": "EXTERNAL",
      "file": "src/api/users.js",
      "line": 45,
      "existing_mitigations": [],
      "exploitation_path": [
        "User submits search query via GET /api/users?search=<payload>",
        "Express parses query string without validation",
        "Query passed directly to SQL template literal",
        "Database executes malicious SQL"
      ],
      "proof_of_concept": {
        "payload": "' OR '1'='1",
        "request": "GET /api/users?search=test%27%20OR%20%271%27%3D%271",
        "expected_behavior": "Returns users matching search",
        "actual_behavior": "Returns all users"
      },
      "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N",
      "cvss_score": 9.1,
      "recommendation": "Use parameterized queries",
      "references": [
        "https://cwe.mitre.org/data/definitions/89.html",
        "https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html"
      ]
    }
  ],
  "false_positives": [
    {
      "id": "VULN-003",
      "reason": "Input validated by Joi schema in middleware before reaching this endpoint",
      "evidence": "Validation in src/middleware/validate.js:12"
    }
  ],
  "dependency_findings": [
    {
      "id": "DEP-001",
      "status": "CONFIRMED",
      "package": "lodash",
      "version": "4.17.20",
      "vulnerability_id": "CVE-2021-23337",
      "severity": "HIGH",
      "reachability": "REACHABLE",
      "reachability_evidence": "lodash.template() called in src/utils/email.js:15",
      "fixed_version": "4.17.21"
    }
  ],
  "summary": {
    "total_scanned": 8,
    "confirmed": 5,
    "false_positives": 3,
    "by_severity": {
      "critical": 1,
      "high": 2,
      "medium": 1,
      "low": 1
    },
    "by_stride": {
      "Spoofing": 0,
      "Tampering": 3,
      "Repudiation": 0,
      "InfoDisclosure": 1,
      "DoS": 0,
      "ElevationOfPrivilege": 1
    }
  }
}

Step 9: Output Results (Mode-Dependent)

PR Mode: Inline Comments

For each finding, post inline PR comment:

markdownCopy code
🔴 **CRITICAL: SQL Injection (CWE-89)**

**STRIDE Category:** Tampering
**Confidence:** High
**File:** `src/api/users.js:45-49`

**Analysis:**
User input from `req.query.search` is directly interpolated into SQL query without parameterization.

**Suggested Fix:**
```diff
- const query = `SELECT * FROM users WHERE name LIKE '%${search}%'`;
- const results = await db.query(query);
+ const query = `SELECT * FROM users WHERE name LIKE $1`;
+ const results = await db.query(query, [`%${search}%`]);

CWE-89: SQL Injection

Copy code

Post summary tracking comment:

```markdown
## 🔒 Security Review Summary

| Severity | Count |
|----------|-------|
| 🔴 Critical | 1 |
| 🟠 High | 2 |
| 🟡 Medium | 3 |
| 🔵 Low | 0 |

### Findings
| ID | Severity | Type | File | Status |
|----|----------|------|------|--------|
| VULN-001 | Critical | SQL Injection | src/api/users.js:45 | Action required |
| VULN-002 | High | XSS | src/components/Comment.tsx:23 | Suggested fix |

---
*Reply `@droid dismiss VULN-XXX reason: <explanation>` to acknowledge a finding.*

Weekly/Full Mode: Security Report PR

Create branch: droid/security-report-{YYYY-MM-DD}

PR Title: fix(security): Security scan report - {date} ({N} findings)

Include:

• .factory/security/reports/security-report-{YYYY-MM-DD}.md
• validated-findings.json
• Updated .factory/threat-model.md (if regenerated)

Step 10: Severity Actions

Severity Definitions

Vulnerability Coverage

Success Criteria

• Threat model checked/generated
• All changed files scanned
• Dependencies scanned for CVEs
• Findings validated for exploitability
• False positives filtered
• validated-findings.json generated
• Results output in appropriate format (PR comments or report)
• Severity actions applied

Example Invocations

PR security review:

Copy code
Scan PR #123 for security vulnerabilities.

Manual trigger in PR:

Copy code
@droid security

Full repository scan:

Copy code
@droid security --full

Weekly scan (last 7 days):

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Scan commits from the last 7 days on main for security vulnerabilities.

Scan and patch:

Copy code
Run full security analysis on PR #123: scan, validate, and generate patches.

File Structure

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.factory/
├── threat-model.md              # STRIDE threat model
├── security-config.json         # Configuration
└── security/
    ├── acknowledged.json        # Dismissed findings
    └── reports/
        └── security-report-{date}.md

Dismissing Findings

PR Mode - Reply to inline comment:

Copy code
@droid dismiss reason: Input is validated by Joi schema in middleware

Weekly/Full Mode - Comment on report PR:

Copy code
@droid dismiss VULN-007 reason: Accepted risk for internal admin tool

Dismissed findings stored in .factory/security/acknowledged.json.

Limitations

Cannot detect:

• Business logic vulnerabilities
• Zero-days with no known patterns
• Vulnerabilities in compiled/minified code
• Issues requiring runtime analysis

May not fully validate:

• Complex multi-service data flows
• Vulnerabilities requiring authentication state

References

• STRIDE: https://docs.microsoft.com/en-us/azure/security/develop/threat-modeling-tool-threats
• OWASP Top 10: https://owasp.org/www-project-top-ten/
• CWE Database: https://cwe.mitre.org/
• OWASP Cheat Sheets: https://cheatsheetseries.owasp.org/
• CVSS Calculator: https://www.first.org/cvss/calculator/3.1