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Analyzing Api Gateway Access Logs

  • 581 installs
  • 27.3k repo stars
  • Updated August 2, 2026
  • mukul975/anthropic-cybersecurity-skills

analyzing-api-gateway-access-logs is a cybersecurity agent skill that parses API gateway access logs to identify traffic patterns, diagnose performance issues, and detect security anomalies in production backends.

About

analyzing-api-gateway-access-logs is an agent skill from mukul975/anthropic-cybersecurity-skills licensed under Apache 2.0 for investigating API gateway access logs in production backends. The skill guides developers through parsing request volumes, status code distributions, latency spikes, client IP clusters, and unusual endpoint access that may indicate abuse or misconfiguration. Developers reach for it during incident response, post-deploy performance regressions, or routine security reviews of AWS API Gateway, Kong, NGINX, or similar gateway log formats. It produces traffic summaries, anomaly flags, and remediation hints rather than replacing a SIEM. The workflow assumes raw or exported access log files or streams and focuses on pattern recognition across HTTP methods, paths, and response codes.

  • Diagnose latency and error patterns in production
  • Detect suspicious traffic and security threats
  • Optimize API performance with data-driven insights

Analyzing Api Gateway Access Logs by the numbers

  • 581 all-time installs (skills.sh)
  • +33 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #248 of 1,435 DevOps & CI/CD skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-api-gateway-access-logs

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Listed on Skillselion
Installs581
repo stars27.3k
Security audit3 / 3 scanners passed
Last updatedAugust 2, 2026
Repositorymukul975/anthropic-cybersecurity-skills

How do you analyze API gateway access logs?

Identify traffic patterns, diagnose performance issues, and detect potential security anomalies in their backend.

Who is it for?

Backend and security engineers investigating production API gateway logs for performance drops or suspicious traffic.

Skip if: Developers who need automated WAF rule deployment without manual log review and incident triage steps.

When should I use this skill?

A developer uploads or references API gateway access logs and asks about traffic anomalies, latency issues, or security patterns.

What you get

Traffic pattern summary, latency diagnosis, security anomaly flags, and endpoint abuse indicators from gateway logs

  • traffic analysis report
  • anomaly flags
  • latency diagnosis

By the numbers

  • Licensed under Apache License 2.0 in the anthropic-cybersecurity-skills repository

Files

SKILL.mdMarkdownGitHub ↗

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: 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

# 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]

Related skills

FAQ

What log sources does analyzing-api-gateway-access-logs support?

analyzing-api-gateway-access-logs targets API gateway access logs from common proxies such as AWS API Gateway, Kong, and NGINX. Developers supply raw or exported logs; the skill summarizes traffic, latency, and anomaly signals.

What security signals does the skill detect?

analyzing-api-gateway-access-logs flags unusual endpoint access, IP clustering, auth failures, and error bursts in gateway logs. Outputs include anomaly summaries and triage hints for backend and security engineers during incidents.

Is Analyzing Api Gateway Access Logs safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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