analyzing-api-gateway-access-logs skill
'Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect
Is the analyzing-api-gateway-access-logs skill safe?
Serious findings: read the flagged lines first. We read 4 files in the folder on 2026-09-28.
- high
references/api-reference.md:51Reads credential files (SSH keys, cloud or package-manager tokens) that a skill has no normal reason to touch.
path_traversal = r"\.\./\.\./|/etc/passwd" - high
scripts/agent.py:76Reads credential files (SSH keys, cloud or package-manager tokens) that a skill has no normal reason to touch.
r'(?:\.\./\.\./|/etc/passwd|/proc/self)',
Install the analyzing-api-gateway-access-logs skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. Read the findings above first.
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills mkdir -p ~/.claude/skills cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/analyzing-api-gateway-access-logs ~/.claude/skills/analyzing-api-gateway-access-logs
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
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.
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()
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