ato-methodology

ato-methodology is a skill for Claude Code, Codex from PurpleAILAB/Decepticon. It costs 39 tokens per session (1,089 once invoked), scanned A, original, Apache-2.0.

A decision guide for account takeover, meaning an attacker gains control of another person's account. It covers routes such as password-reset flaws, unsafe email changes, session fixation, token weaknesses, OAuth mistakes, IDOR, and cross-site scripting.

In plain words
What is it for?
Use it to investigate password recovery, session handling, JWT and OAuth flows, account changes, and other paths that could let an attacker access or modify a victim's account.
Why use it?
It helps connect different bugs to the concrete outcome of losing control of an account.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to investigate password recovery, session handling, JWT and OAuth flows, account changes, and other paths that could let an attacker access or modify a victim's account.

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Install with agentmods
npx agentmods add skills/purpleailab/decepticon/ato-methodology
About the project

Decepticon is an autonomous red-team agent that coordinates AI agents, security tools, sandboxes, and supporting services for authorized cybersecurity assessments. Security researchers and red teams can run it through its Docker stack, cloud service, command-line interface, or Python SDK, with the catalogue entries representing its available skills.

PurpleAILAB/Decepticon · 5,497 stars · on GitHub · decepticon.red

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add PurpleAILAB/Decepticon --skill ato-methodology
Clone the repo
git clone --depth 1 https://github.com/PurpleAILAB/Decepticon

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ato-methodology

README.md
[![agentmods](https://agentmods.dev/badge/skills/purpleailab/decepticon/ato-methodology/github.svg)](https://agentmods.dev/skills/purpleailab/decepticon/ato-methodology)
Your own site
<a href="https://agentmods.dev/skills/purpleailab/decepticon/ato-methodology"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/ato-methodology/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ato-methodology

Your own site · 80×15
<a href="https://agentmods.dev/skills/purpleailab/decepticon/ato-methodology"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/ato-methodology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,089 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.01089
Opus 5 $0.00019 $0.00544
Sonnet 5 $0.00008 $0.00218
Haiku 4.5 $0.00004 $0.00109

Measured 9d ago against content hash 4f11bfa0690d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ato-methodology scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

packages/decepticon/decepticon/skills/standard/exploit/web/ato-methodology/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Account Takeover (ATO) Methodology

ATO is an outcome, not a vuln class. Reach it via 9 canonical paths.

1. Password reset flaws

  • Token in URL leaked to Referer (3rd-party CDN, analytics)
  • Token guessable (timestamp + user_id, sequential int, predictable RNG)
  • Token-no-expiry → reuse forever
  • Reset accepts arbitrary email param (mass-assignment style)
  • Token not invalidated after password change
  • "Forgot username" flows revealing existence

2. Email change without re-auth

POST /api/users/me/email {email: ...} without verifying current password. Or with verification but verification token leaks.

3. Session fixation

Server accepts attacker-set session cookie. Victim's actions bind to attacker's session.

4. JWT-based ATO

See skills/exploit/web/jwt/SKILL.md — alg confusion, weak secret, kid injection.

5. OAuth-based ATO

See skills/exploit/web/oauth/SKILL.md — redirect_uri bypass + open-redirect chain → code to attacker.

6. IDOR-based ATO

  • PATCH /api/users/<id> w/o auth check → change victim's email/password
  • GET /api/users/<id>/sessions → harvest victim's session tokens

7. XSS-based ATO

Stored XSS on victim-visible page → exfil cookie / session token to attacker.

8. CSRF on critical state

  • CSRF on password change endpoint (no anti-CSRF token)
  • CSRF on email change
  • CSRF on MFA disable

9. MFA bypass

  • TOTP code accepted multiple times w/ short delay (race)
  • TOTP code accepted from past N-step (clock skew abuse)
  • Backup-code flow doesn't enforce TOTP
  • "Trust this device" w/o re-auth on critical action
  • Account recovery bypasses MFA entirely
  • Phone-number takeover (SIM swap) → SMS 2FA hijack

Chain table

Primary vuln Chain partner Outcome
Open redirect OAuth redirect_uri allowlist OAuth code → attacker → ATO
XSS (reflected) session cookie not HttpOnly Cookie exfil → ATO
XSS (stored) victim views page Cookie / session-storage exfil → ATO
IDOR on email change reset flow Change victim's email, reset, login
CSRF on password change predictable URL Phishing email triggers password change
Predictable reset token weak RNG audit Generate victim's token offline → reset
OAuth state missing account linking by email Attacker pre-creates account, links victim's OAuth → ATO
JWT alg=none server accepts Mint admin JWT → ATO
Email change w/o re-auth + ATO of email full account graph Standard playbook for multi-tenant SaaS

Read the full file on GitHub · 105 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 105 lines · 39 tokens per session scan A 4f11bfa0690d

Subscribe to this mod's changes

ato-methodology is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,497 stars, last pushed 13d ago), licensed Apache-2.0. It adds 39 tokens to every session and 1,089 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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