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name, description, domain, subdomain, tags, version, author, license
| name | description | domain | subdomain | tags | version | author | license | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| analyzing-api-gateway-access-logs | Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules. | cybersecurity | security-operations |
|
1.0 | mahipal | MIT |
Analyzing API Gateway Access Logs
Instructions
Parse API gateway access logs to identify attack patterns including broken object level authorization (BOLA), excessive data exposure, and injection attempts.
import pandas as pd
df = pd.read_json("api_gateway_logs.json", lines=True)
# Detect BOLA: same user accessing many different resource IDs
bola = df.groupby(["user_id", "endpoint"]).agg(
unique_ids=("resource_id", "nunique")).reset_index()
suspicious = bola[bola["unique_ids"] > 50]
Key detection patterns:
- BOLA/IDOR: sequential resource ID enumeration
- Rate limit bypass via header manipulation
- Credential scanning (401 surges from single source)
- SQL/NoSQL injection in query parameters
- Unusual HTTP methods (DELETE, PATCH) on read-only endpoints
Examples
# Detect 401 surges indicating credential scanning
auth_failures = df[df["status_code"] == 401]
scanner_ips = auth_failures.groupby("source_ip").size()
scanners = scanner_ips[scanner_ips > 100]