security-audit

Audit codebases for exploitable vulnerabilities and produce verified security reports.

214|7|Updated May 29, 2026
One-click install
npx skills add https://github.com/anolilab/lunora --skill security-audit-anolilab
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: security-audit
Source: https://github.com/anolilab/lunora/tree/main/.agents/skills/security-audit
Command: npx skills add https://github.com/anolilab/lunora --skill security-audit-anolilab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the complex process of performing a manual security audit on a codebase, moving beyond simple scanners to identify deep-seated logic flaws and exploitable vulnerabilities.

Core Features & Use Cases

  • Multi-Agent Orchestration: Coordinates specialized research and general hunting agents to explore different subsystems and attack classes in parallel.
  • Exploit-Focused Methodology: Prioritizes findings that have concrete, reproducible attack scenarios rather than theoretical risks.
  • Use Case: Use this Skill to audit a new API or microservice before deployment to ensure that business logic, authentication, and authorization boundaries are robust against real-world attack vectors.

Quick Start

Use the security-audit skill to perform a full vulnerability assessment on the current repository and save the findings to the default output directory.

Frequently Asked Questions about security-audit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform a security audit on a codebase to identify exploitable vulnerabilities?

Perform a security audit by orchestrating multi-agent hunting workflows to systematically map trust boundaries, input surfaces, and business logic. This process targets web applications, APIs, and services to produce verified, impact-oriented security reports.

What is the best way to find deep-seated logic flaws beyond simple scanner results?

Finding deep-seated logic flaws requires an exploit-focused methodology that prioritizes concrete, reproducible attack scenarios over theoretical risks. It coordinates specialized research agents to explore different subsystems and attack classes in parallel.

Can I use this automated vulnerability hunting to audit a new API before deployment?

Yes, you can audit a new API or microservice before deployment to ensure business logic, authentication, and authorization boundaries are robust. It validates real-world attack vectors specific to your codebase architecture.

How does threat modeling integrate into a comprehensive code review for security?

Threat modeling integrates into code review by systematically mapping trust boundaries and input surfaces across the codebase. This mapping directs specialized hunting agents to target specific attack classes and validate exploitable vulnerabilities.

Does a comprehensive pentest approach require mapping trust boundaries and input surfaces?

Yes, comprehensive pentest execution requires systematic mapping of trust boundaries, input surfaces, and business logic. This mapping is essential for orchestrating multi-agent hunting workflows and producing verified security reports.

What are the limitations of using automated multi-agent workflows for vulnerability hunting?

Automated multi-agent vulnerability hunting focuses exclusively on exploitable findings with concrete, reproducible attack scenarios. Theoretical risks are deprioritized, meaning the resulting security reports concentrate only on verified, impact-oriented threats.