Implementing API Key Security Controls
When to Use
- Designing secure API key generation with sufficient entropy and identifiable prefixes for leak detection
- Implementing server-side API key hashing (never storing keys in plaintext) with SHA-256 or bcrypt
- Building key rotation workflows that allow zero-downtime key replacement for API consumers
- Configuring per-key scoping to limit each API key to specific endpoints, IP ranges, and rate limits
- Setting up automated monitoring for API key leakage in GitHub repos, logs, and client-side code
Do not use API keys as the sole authentication mechanism for user-facing applications. API keys are best suited for server-to-server communication and developer access.
Prerequisites
- Secure random number generator (os.urandom, secrets module) for key generation
- Database with proper encryption at rest for storing hashed API keys
- Redis or similar store for key-to-metadata caching and rate limiting
- Secret scanning tools (GitHub secret scanning, truffleHog, gitleaks)
- Monitoring and alerting infrastructure for key usage anomalies
Workflow
Step 1: Secure API Key Generation
import secrets
import hashlib
import hmac
import time
import json
from datetime import datetime, timedelta
class APIKeyManager:
"""Manages secure API key lifecycle: generation, storage, validation, rotation."""
# Key format: prefix_base64random (e.g., sk_live_a1b2c3d4e5f6...)
# Prefix identifies the key type and environment for leak detection
KEY_PREFIXES = {
"live_secret": "sk_live_",
"test_secret": "sk_test_",
"live_public": "pk_live_",
"test_public": "pk_test_",
}
def __init__(self, db_connection, redis_connection):
self.db = db_connection
self.redis = redis_connection
def generate_key(self, key_type="live_secret", owner_id=None, scopes=None,
rate_limit=None, ip_allowlist=None, expires_days=365):
"""Generate a new API key with metadata."""
prefix = self.KEY_PREFIXES.get(key_type, "sk_live_")
# Generate 32 bytes (256 bits) of randomness
random_bytes = secrets.token_bytes(32)
key_body = secrets.token_urlsafe(32) # Base64url-encoded
# Full API key that the client receives (shown only once)
full_key = f"{prefix}{key_body}"
# Hash the key for storage (never store the raw key)
key_hash = hashlib.sha256(full_key.encode()).hexdigest()
# Create a short key ID for reference (first 8 chars)
key_id = f"{prefix}{key_body[:8]}..."
# Store the hashed key with metadata
key_metadata = {
"key_hash": key_hash,
"key_id": key_id,
"key_type": key_type,
"owner_id": owner_id,
"scopes": scopes or ["read"],
"rate_limit": rate_limit or {"requests": 1000, "window": 3600},
"ip_allowlist": ip_allowlist or [],
"created_at": datetime.utcnow().isoformat(),
"expires_at": (datetime.utcnow() + timedelta(days=expires_days)).isoformat(),
"last_used": None,
"is_active": True,
"usage_count": 0,
}
# Store in database
self.db.execute(
"INSERT INTO api_keys (key_hash, key_id, metadata) VALUES (?, ?, ?)",
(key_hash, key_id, json.dumps(key_metadata))
)
# Cache in Redis for fast validation
self.redis.setex(
f"apikey:{key_hash}",
86400, # 24-hour cache TTL
json.dumps(key_metadata)
)
return {
"api_key": full_key, # Show to user ONCE
"key_id": key_id, # For reference/management
"scopes": key_metadata["scopes"],
"expires_at": key_metadata["expires_at"],
}
def validate_key(self, api_key):
"""Validate an API key and return its metadata."""
key_hash = hashlib.sha256(api_key.encode()).hexdigest()
# Check Redis cache first
cached = self.redis.get(f"apikey:{key_hash}")
if cached:
metadata = json.loads(cached)
else:
# Fall back to database
row = self.db.execute(
"SELECT metadata FROM api_keys WHERE key_hash = ?",
(key_hash,)
).fetchone()
if not row:
return None, "invalid_key"
metadata = json.loads(row[0])
# Refresh cache
self.redis.setex(f"apikey:{key_hash}", 86400, row[0])
# Validation checks
if not metadata.get("is_active"):
return None, "key_revoked"
if metadata.get("expires_at"):
if datetime.fromisoformat(metadata["expires_at"]) < datetime.utcnow():
return None, "key_expired"
# Update last used
metadata["last_used"] = datetime.utcnow().isoformat()
metadata["usage_count"] = metadata.get("usage_count", 0) + 1
self.redis.setex(f"apikey:{key_hash}", 86400, json.dumps(metadata))
return metadata, "valid"
def revoke_key(self, key_id):
"""Immediately revoke an API key."""
row = self.db.execute(
"SELECT key_hash, metadata FROM api_keys WHERE key_id = ?",
(key_id,)
).fetchone()
if row:
key_hash = row[0]
metadata = json.loads(row[1])
metadata["is_active"] = False
metadata["revoked_at"] = datetime.utcnow().isoformat()
self.db.execute(
"UPDATE api_keys SET metadata = ? WHERE key_id = ?",
(json.dumps(metadata), key_id)
)
# Invalidate cache immediately
self.redis.delete(f"apikey:{key_hash}")
return True
return False
def rotate_key(self, old_key_id, grace_period_hours=24):
"""Rotate an API key with a grace period where both old and new keys work."""
old_row = self.db.execute(
"SELECT key_hash, metadata FROM api_keys WHERE key_id = ?",
(old_key_id,)
).fetchone()
if not old_row:
return None, "key_not_found"
old_metadata = json.loads(old_row[1])
# Generate new key with same settings
new_key_data = self.generate_key(
key_type=old_metadata["key_type"],
owner_id=old_metadata["owner_id"],
scopes=old_metadata["scopes"],
rate_limit=old_metadata["rate_limit"],
ip_allowlist=old_metadata["ip_allowlist"],
)
# Schedule old key revocation after grace period
revoke_at = datetime.utcnow() + timedelta(hours=grace_period_hours)
old_metadata["scheduled_revocation"] = revoke_at.isoformat()
self.db.execute(
"UPDATE api_keys SET metadata = ? WHERE key_id = ?",
(json.dumps(old_metadata), old_key_id)
)
return {
"new_key": new_key_data,
"old_key_id": old_key_id,
"old_key_revokes_at": revoke_at.isoformat(),
"message": f"Old key will be revoked in {grace_period_hours} hours"
}, "success"
Step 2: API Key Validation Middleware
from flask import Flask, request, jsonify, g
from functools import wraps
app = Flask(__name__)
def require_api_key(required_scopes=None):
"""Middleware to validate API key and check scopes."""
def decorator(f):
@wraps(f)
def wrapped(*args, **kwargs):
# Extract API key from header
api_key = request.headers.get("X-API-Key")
if not api_key:
# Also check Authorization: Bearer <key>
auth_header = request.headers.get("Authorization", "")
if auth_header.startswith("Bearer "):
api_key = auth_header[7:]
if not api_key:
return jsonify({"error": "missing_api_key"}), 401
# Validate the key
metadata, status = key_manager.validate_key(api_key)
if status != "valid":
return jsonify({"error": status}), 401
# Check IP allowlist
if metadata.get("ip_allowlist"):
client_ip = request.remote_addr
if client_ip not in metadata["ip_allowlist"]:
return jsonify({"error": "ip_not_allowed"}), 403
# Check scopes
if required_scopes:
key_scopes = set(metadata.get("scopes", []))
if not key_scopes.intersection(required_scopes):
return jsonify({"error": "insufficient_scope"}), 403
# Attach metadata to request context
g.api_key_metadata = metadata
return f(*args, **kwargs)
return wrapped
return decorator
@app.route('/api/v1/data', methods=['GET'])
@require_api_key(required_scopes=["read", "admin"])
def get_data():
return jsonify({"data": "sensitive information"})
@app.route('/api/v1/data', methods=['POST'])
@require_api_key(required_scopes=["write", "admin"])
def create_data():
return jsonify({"created": True})
Step 3: Automated Key Leakage Detection
# Scan GitHub repositories for leaked API keys using gitleaks
gitleaks detect --source=/path/to/repo --config=gitleaks.toml --report-path=leaks.json
# Custom gitleaks configuration for API key prefix detection
# gitleaks.toml
cat <<'EOF'
[[rules]]
id = "company-api-key-live"
description = "Company Live API Key"
regex = '''sk_live_[A-Za-z0-9_-]{32,}'''
tags = ["api-key", "live", "critical"]
[[rules]]
id = "company-api-key-test"
description = "Company Test API Key"
regex = '''sk_test_[A-Za-z0-9_-]{32,}'''
tags = ["api-key", "test"]
[[rules]]
id = "company-public-key"
description = "Company Public API Key"
regex = '''pk_live_[A-Za-z0-9_-]{32,}'''
tags = ["api-key", "public"]
EOF
# Automated leaked key revocation
import json
def process_leaked_keys(leaks_file):
"""Automatically revoke API keys detected in public repositories."""
with open(leaks_file) as f:
leaks = json.load(f)
for leak in leaks:
key_match = leak.get("match", "")
# Extract the key from the match
for prefix in ["sk_live_", "sk_test_", "pk_live_"]:
if prefix in key_match:
start = key_match.index(prefix)
potential_key = key_match[start:start+50] # Max key length
# Validate and revoke
metadata, status = key_manager.validate_key(potential_key)
if status == "valid":
key_manager.revoke_key(metadata["key_id"])
print(f"[REVOKED] Key {metadata['key_id']} leaked in {leak.get('file')}")
# Notify the key owner
notify_owner(metadata["owner_id"], metadata["key_id"], leak)
Key Concepts
| Term | Definition |
|---|---|
| API Key | A secret string used to authenticate API requests, typically passed in headers or query parameters |
| Key Hashing | Storing only the hash (SHA-256) of the API key in the database, never the plaintext key, similar to password hashing |
| Key Rotation | Replacing an API key with a new one while maintaining a grace period where both keys work, ensuring zero-downtime transition |
| Key Scoping | Limiting each API key to specific endpoints, HTTP methods, IP ranges, and rate limits to minimize blast radius |
| Key Prefix | An identifiable prefix (e.g., sk_live_) that enables automated detection of leaked keys in logs, code, and public repositories |
| Secret Scanning | Automated monitoring of repositories, logs, and public sources for exposed API keys and credentials |
Tools & Systems
- GitHub Secret Scanning: Built-in GitHub feature that detects exposed secrets in repositories and alerts key providers
- gitleaks: Open-source tool for detecting secrets in git repositories using customizable regex patterns
- truffleHog: Secret scanning tool that searches entire git history for high-entropy strings and known secret patterns
- HashiCorp Vault: Enterprise secret management system for API key storage, rotation, and dynamic credential generation
- AWS Secrets Manager: Managed secret storage with automatic rotation support for API keys and credentials
Common Scenarios
Scenario: API Key Security Program for Developer Platform
Context: A developer platform provides public APIs authenticated with API keys. The platform has 10,000+ API consumers generating 50M+ requests per day. Keys are frequently leaked in public GitHub repositories.
Approach:
- Implement prefixed API keys (sk_live_, sk_test_) with 256-bit entropy for leak detection
- Store only SHA-256 hashes of keys in the database, cache validated keys in Redis
- Implement per-key scoping: each key restricted to specific endpoints, rate limits, and optional IP allowlists
- Build key rotation API with 24-hour grace period for seamless transitions
- Integrate with GitHub Secret Scanning to automatically detect and revoke leaked keys within minutes
- Run gitleaks in CI/CD pipelines to prevent key commits in first place
- Implement anomaly detection: alert on keys used from unusual IPs or with abnormal traffic patterns
- Add key expiration policy: all keys expire after 365 days with 30-day advance notification
Pitfalls:
- Storing API keys in plaintext in the database (use SHA-256 hashing)
- Using predictable or low-entropy key generation (use cryptographically secure random generators)
- Not implementing key prefixes, making it impossible to identify leaked keys in automated scans
- Allowing API keys in URL query parameters where they leak in logs, browser history, and Referer headers
- Not implementing rate limiting per key, allowing a single compromised key to abuse the entire API
Output Format
## API Key Security Implementation Report
**Platform**: Developer API v3
**Total Active Keys**: 12,450
**Daily Key Validations**: 52M
### Security Controls
| Control | Implementation | Status |
|---------|---------------|--------|
| Key Entropy | 256-bit (secrets.token_urlsafe(32)) | Implemented |
| Key Format | sk_live_/sk_test_ prefixed | Implemented |
| Storage | SHA-256 hashed, Redis cached | Implemented |
| Scoping | Per-key endpoint/IP/rate limits | Implemented |
| Rotation | 24-hour grace period API | Implemented |
| Expiration | 365-day max TTL | Implemented |
| Leak Detection | GitHub Secret Scanning + gitleaks | Active |
| Auto-Revocation | Leaked keys revoked within 5 min | Active |
### Key Leakage Stats (Last 30 Days)
- Keys detected in public repos: 23
- Average time to revocation: 3.2 minutes
- Keys detected in CI/CD pre-commit: 7 (prevented)
Verification Criteria
Confirm successful execution by validating:
- [ ] All prerequisite tools and access requirements are satisfied
- [ ] Each workflow step completed without errors
- [ ] Output matches expected format and contains expected data
- [ ] No security warnings or misconfigurations detected
- [ ] Results are documented and evidence is preserved for audit
Compliance Framework Mapping
This skill supports compliance evidence collection across multiple frameworks:
- SOC 2: CC6.1 (Logical Access), CC6.6 (System Boundaries)
- ISO 27001: A.14.1 (Security Requirements), A.9.4 (System Access Control)
- NIST 800-53: AC-3 (Access Enforcement), SI-10 (Input Validation), SC-8 (Transmission Confidentiality)
- OWASP LLM Top 10: LLM06 (Excessive Agency), LLM08 (Excessive Autonomy)
Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.
Deploying This Skill with Claw GRC
Agent Execution
Register this skill with your Claw GRC agent for automated execution:
# Install via CLI
npx claw-grc skills add implementing-api-key-security-controls
# Or load dynamically via MCP
grc.load_skill("implementing-api-key-security-controls")
Audit Trail Integration
When executed through Claw GRC, every step of this skill generates tamper-evident audit records:
- SHA-256 chain hashing ensures no step can be modified after execution
- Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
- Trust score impact — successful execution increases your agent's trust score
Continuous Compliance
Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.