Skip to content
cccskills
FreePublished on GitHub

analyzing-api-gateway-access-logs

Analyze access logs from AWS API Gateway, Kong, and Nginx with pandas, a Python data analysis library. Examine resource access patterns, authentication failures, and suspicious requests to investigate API abuse and inform detection rules.

OriginalShow the original description

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.

Works withAWS
See how to install

Good for

  • Investigating sequential access to resource IDs
  • Examining spikes in authentication failures
  • Checking for rate limit bypass and injection attempts
  • Developing API abuse detection rules

Files included (4)

  • SKILL.md2.3 KB
  • LICENSE11.0 KB
  • references/api-reference.md1.4 KB
  • scripts/agent.py6.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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]

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.

  • Assessing saved credential exposure in authorized tests
  • Examining collected DPAPI files offline
  • Reviewing protected browser and RDP credentials
mukul975/Anthropic-Cybersecurity-Skills34.8KUpdated Aug 31, 2026

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

  • Assessing risky permissions identified in BloodHound
  • Validating account takeover without resetting a password
  • Generating directory change records during security exercises
mukul975/Anthropic-Cybersecurity-Skills34.8KUpdated Aug 31, 2026

Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.

  • Define the assessment scope for systems handling controlled information
  • Calculate an SPRS score and prioritize unmet security requirements
  • Prepare security plans, remediation milestones, and assessment evidence
mukul975/Anthropic-Cybersecurity-Skills34.8KUpdated Aug 31, 2026

Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.

  • Preserving a suspect drive before investigation
  • Creating evidence copies of USB devices or memory cards
  • Verifying that a disk image matches its source
mukul975/Anthropic-Cybersecurity-Skills34.8KUpdated Aug 31, 2026

Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.

  • Auditing excessive Active Directory permissions
  • Investigating privilege escalation paths from ordinary accounts
  • Reporting affected objects and permission remediation recommendations
mukul975/Anthropic-Cybersecurity-Skills34.8KUpdated Aug 31, 2026

Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.

  • Triage suspicious APK files without running them
  • Inspect dangerous permission combinations and suspicious API calls
  • Extract network indicators for malware detection rules
mukul975/Anthropic-Cybersecurity-Skills34.8KUpdated Aug 31, 2026

See all skills by mukul975

Report a problem with this skill