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Pentest Skill

SkillSecurity

Once added, your AI can run security testing checks against a website URL or a codebase. Pentest is a skill that gives your AI a security testing workflow to follow. You can ask it to test a site or project, and it will run the checks against the target you name.

Use Pentest Skill in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Pentest Skill and connect your AI. About a minute.

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Also: Claude Code · Cursor · Codex

Then ask your AI: use the Pentest Skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

After adding the skill, give your AI the website URL or codebase you want tested and ask it to run the security testing workflow. It will run the checks against that target.

Pentest SkillStart free

What your AI can do with it

  • Run a security testing workflow against a target URL
  • Run a security testing workflow against a codebase
  • Run security testing checks on a website URL you provide
  • Run security testing checks on a codebase you provide
  • Work through the testing workflow when you ask for a security review of a site or project

What this skill tells your AI

The instructions your AI receives, as published by hoangnguyen0403/agent-skills-standard in .codex/skills/pentest/SKILL.md and read by Ahel’s review.

[!IMPORTANT] PTES-aligned adversarial security audit for backend, frontend, and mobile applications. Produces a CVSS-scored Hacker Report with verified PoCs and phased remediation.

Optional args: slug=, ticket=<id/url>, mode=interactive|autonomous|channel, channel=, auto_continue=true|false, profile=business|hybrid|technical.

Instructions

When the user asks to perform this workflow, execute the following steps:

🕵️‍♂️ Penetration Test (PTES-Aligned)

Goal: Execute a red-team assessment across backend, frontend, and mobile targets with verified PoCs and audit-grade evidence.

Steps

  1. Scope and authorization:

    • Determine mode (whitebox, greybox, blackbox) and targets.
    • Verify explicit, current authorization, target exclusions, permitted techniques, time window and stop contact. Require demonstrated runtime controls for live actions; unsupported controls block execution, not offline planning.

  2. Intel and threat model:

    • Identify stack, endpoints, parameters, local storage, schemes, and secrets.
    • Use common-security-audit, common-dast-tooling, and architecture docs when available.
    • Map trust boundaries, secrets, external integrations, and privileged workflows before exploit attempts.

  3. Vulnerability analysis:

    • Run scans and delegate: SAST/SCA to specialist-aspm-correlator, dynamic/logic to specialist-logic-hacker, binary/mobile to specialist-mobile-reverser.
    • Rank targets by exposure × sensitivity × auth_coverage.

  4. Exploit verification:

    • Confirm findings only with reproducible evidence within scope; never force unsafe exploitation.
    • Preserve suspected, blocked, not-tested and false-positive dispositions separately from confirmed; record missing evidence, preconditions and blast radius.
    • Use synthetic identities/data; no real sensitive-data extraction. Stop on scope drift or impact; obtain approval before restarting.

  5. Reporting:

    • Write artifacts/security-review.md with assumptions, source provenance, review context, runtime contract, PoCs, blast radius, finding confidence, exploit path, evidence gaps, and handoff notes.
    • Emit artifacts/security-review.dev.md, artifacts/security-review.appsec.md, or artifacts/security-review.exec.md only when leadership, client, or AppSec reporting is in scope.
    • Score from 100: Critical -25 (cap 25), High -15 (cap 40), Medium -8, Low -3.
    • Reuse the existing security-review.md record when pentest follows earlier design or PR security review work.
    • Deliver findings in the standard template below.

Output Template

Executive Summary

  • Hacker Score: X/100 ([Critical/Vulnerable/Moderate/Hardened])
  • Target Scope: [repos, URLs, mobile apps]
  • Findings: [Critical/High/Medium/Low counts]

Findings Table

IDTitlePlatformSeverityCVSSCWEPoC
SEC-01[title][backend|frontend|mobile][Critical|High|Medium|Low][score][CWE-id][Yes|No]

Signals

GitHub stars
569
Forks
166
Last commit
Oct 2026

Ahel review

  • K5info
    obfuscation

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Item type
skill
Key
pentest
Source
github.com/hoangnguyen0403/agent-skills-standard

github.com/hoangnguyen0403/agent-skills-standard

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