Security Scan - API Key & Secret Detection

Overview

Problem: AI agents sometimes accidentally hardcode API keys, tokens, and secrets into source code, configs, or documentation, creating security vulnerabilities when committed to Git.

Solution: This skill provides fast, automated secret detection using xswarm-ai-sanitize — zero-install via npx, 607+ patterns, directory scanning, .gitignore-aware.

Used by: Coder agent as mandatory QA step before signaling completion.

Primary Use Case

Coder Agent QA Workflow (Mandatory)

After implementing code, before reporting completion:

1. •

   Run security scan

   bash

   npx xswarm-ai-sanitize detect .
   

2. •

   If NO secrets found (exit 0) — proceed to report completion

3. •

   If secrets FOUND (exit 1) — DO NOT proceed. Invoke @stuck with the file:line details. Remediate and re-scan.

This is non-negotiable. No code proceeds to testing with secrets present. The scan exists because AI agents are especially prone to hardcoding credentials they encounter during implementation.

Quick Start

No installation required. xswarm-ai-sanitize runs via npx:

# Scan entire project directory (respects .gitignore)
npx xswarm-ai-sanitize detect .

# Scan specific paths
npx xswarm-ai-sanitize detect src/ .env config/

# JSON output for CI/CD
npx xswarm-ai-sanitize detect --json .

# Scan everything (ignore .gitignore)
npx xswarm-ai-sanitize detect --no-gitignore .

Output Format

src/config.js:23:15 [CRITICAL] aws_access_key_id
    ...AWS_ACCESS_KEY_ID=AKIA...EXAMPLE...

.env.example:3:1 [HIGH] env_file_secret
    OPENAI_API_KEY=sk-proj-...

Each finding shows: file:line:column [SEVERITY] pattern_name with a context preview.

Exit Codes

What Gets Detected

xswarm-ai-sanitize detects 607+ secret patterns plus entropy analysis:

See: reference/secret-patterns.md for regex patterns.

What Gets Scanned

Included (all committable files by default)

• •Source code, configs, documentation, scripts, IaC manifests, build configs

Excluded (respects .gitignore)

• •node_modules/, vendor/, venv/, dist/, build/, .git/, ./tmp/

Principle: If it won't be committed, it won't be scanned. This prevents false positives from dependencies and build artifacts.

Coder Agent Workflow

Step 1: Scan after implementation

npx xswarm-ai-sanitize detect .

Step 2a: Clean (exit 0)

Security scan: PASSED
Ready to report completion.

Step 2b: Secrets found (exit 1)

Security scan: FAILED

Secrets detected:
- src/config.py:23:15 [CRITICAL] openai_project_key
- scripts/deploy.sh:45:8 [CRITICAL] aws_access_key

Cannot proceed. Invoking @stuck.

Step 3: Invoke @stuck (DO NOT proceed)

Provide the exact output with file:line details. The stuck agent will present remediation options to the user.

Step 4: Remediate

Common fixes:

# BEFORE (hardcoded secret)
API_KEY = "sk-proj-abc123def456..."

# AFTER (load from environment)
import os
API_KEY = os.getenv("OPENAI_API_KEY")
if not API_KEY:
    raise ValueError("OPENAI_API_KEY not set in environment")

# Add to .env (gitignored)
OPENAI_API_KEY=sk-proj-actual-key

# Ensure .env is gitignored
grep -q "^\.env$" .gitignore || echo ".env" >> .gitignore

Step 5: Re-scan and proceed

npx xswarm-ai-sanitize detect .
# Exit 0 → safe to report completion

JSON Output for CI/CD

npx xswarm-ai-sanitize detect --json .

{
  "version": "1.0.0",
  "summary": {
    "totalFiles": 45,
    "totalFindings": 2,
    "criticalCount": 1,
    "highCount": 1,
    "mediumCount": 0
  },
  "results": [
    {
      "file": "src/config.js",
      "findings": [
        {
          "line": 23,
          "column": 15,
          "severity": "critical",
          "type": "aws_access_key_id",
          "preview": "AWS_ACCESS_KEY_ID=AKIA...EXAMPLE..."
        }
      ]
    }
  ]
}

Use in GitHub Actions:

- run: npx xswarm-ai-sanitize detect --json . > report.json

False Positives

Common Sources

• •Example keys in documentation (YOUR-KEY-HERE, EXAMPLE)
• •Test fixtures with obvious fakes
• •High-entropy strings that aren't secrets (UUIDs, hashes, long URLs)

Managing False Positives

For documentation files with example patterns, use obviously fake placeholders:

# SAFE — clearly a placeholder
export OPENAI_API_KEY="sk-proj-YOUR-KEY-HERE"

For test data, use clearly labeled fakes:

def test_api_client():
    fake_key = "sk-proj-test-EXAMPLE-not-real-key"
    client = APIClient(api_key=fake_key)

Note: xswarm-ai-sanitize's entropy analysis may flag long random-looking strings (URLs, XSD references). These are typically MEDIUM severity and can be evaluated in context.

Sanitize Mode (Beyond Detection)

xswarm-ai-sanitize can also redact secrets in place of just detecting them — useful for cleaning content before it reaches AI agent memory:

# Redact secrets from text
cat .env | npx xswarm-ai-sanitize sanitize -q

# Block mode (exit 1 if secrets found, no redaction)
npx xswarm-ai-sanitize sanitize --block config.yml

The detect command is for pre-commit scanning. The sanitize command is for AI agent pipelines where content should be cleaned before processing.

Security Best Practices

1. •Never commit secrets. Use .env files or secret management services — hardcoded secrets are the #1 AI-generated vulnerability.
2. •Always .gitignore .env. Environment files should never be committed.
3. •Use environment variables. Load secrets at runtime via os.getenv() / process.env.
4. •Rotate leaked keys. If a secret was committed, rotate immediately — treat the old key as compromised.
5. •Document placeholders. Use YOUR-KEY-HERE in examples — real-looking fakes trigger GitHub Push Protection.
6. •MCP configs gitignored. Server configs often contain auth tokens.
7. •Regular audits. Periodic full scans with npx xswarm-ai-sanitize detect .

Reference Documentation

• •reference/secret-patterns.md - Detectable secret types with regex patterns
• •reference/false-positives.md - Managing allowlists
• •reference/remediation.md - Step-by-step guide to fixing leaked secrets
• •reference/gitleaks-guide.md - Legacy Gitleaks CLI reference (for projects still using gitleaks)

Examples

• •examples/coder-workflow-example.md - Complete coder agent workflow
• •examples/remediation-example.md - Step-by-step secret remediation

For coder agents: This skill is mandatory QA. No shortcuts. No proceeding with secrets present. Security is non-negotiable.