# 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 using pandas for statistical analysis and anomaly detection.

- Skill: `mukul975/analyzing-api-gateway-access-logs` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add mukul975/analyzing-api-gateway-access-logs`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mukul975/analyzing-api-gateway-access-logs/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security, DevOps & Infra, Vulnerability Scanning
- Tags: Api Gateway, Aws Api Gateway, Bola, Idor, Kong, Nginx, Pandas, Threat Detection
- License: Apache-2.0
- Author: mukul975 (https://skillmd.com/u/mukul975)
- Updated: 2026-07-06
- Page: https://skillmd.com/skills/mukul975/analyzing-api-gateway-access-logs

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# Analyzing API Gateway Access Logs


## When to Use

- When investigating security incidents that require analyzing api gateway access logs
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques

## Prerequisites

- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities

## Instructions

Parse API gateway access logs to identify attack patterns including broken object
level authorization (BOLA), excessive data exposure, and injection attempts.

```python
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:
1. BOLA/IDOR: sequential resource ID enumeration
2. Rate limit bypass via header manipulation
3. Credential scanning (401 surges from single source)
4. SQL/NoSQL injection in query parameters
5. Unusual HTTP methods (DELETE, PATCH) on read-only endpoints

## Examples

```python
# 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]
```