idor-analysis

idor-analysis is a skill for Claude Code, Codex from MingyiSecLab/Mingyi-Atlas. It costs 46 tokens per session (1,420 once invoked), scanned B, a copy of idor, Apache-2.0.

A security-testing method for finding insecure direct object references, where an application accepts an object ID without checking whether the requester may access that object. An object might be an invoice, user record, or order.

In plain words
What is it for?
Use it to inspect REST, GraphQL, and WebSocket endpoints, test IDs in URLs and request data, and check both same-level and higher-level access.
Why use it?
Guessing or changing an ID can expose another user's data or allow actions with higher privileges when ownership checks are missing.

Skill for Claude CodeCodex

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

Good fit Use it to inspect REST, GraphQL, and WebSocket endpoints, test IDs in URLs and request data, and check both same-level and higher-level access.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mingyiseclab/mingyi-atlas/idor-analysis
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 MingyiSecLab/Mingyi-Atlas --skill idor-analysis
Clone the repo
git clone --depth 1 https://github.com/MingyiSecLab/Mingyi-Atlas

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 idor-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/idor-analysis/github.svg)](https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/idor-analysis)
Your own site
<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/idor-analysis"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/idor-analysis/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 idor-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/idor-analysis"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/idor-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,420 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 97% copy Near-identical to another mod 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 $0.00046 $0.01420
Opus 5 $0.00023 $0.00710
Sonnet 5 $0.00009 $0.00284
Haiku 4.5 $0.00005 $0.00142

Measured 11d ago against content hash 35c393bd8d7f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade B, and why

idor-analysis scanned grade B with 2 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 11d 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 URLmediumData 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.

2. Call admin endpoint: `curl -b sessionU -X POST /api/admin/users/<victim>/role -d '{"role":"admin"}'`.

Makes network callslowCapability

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

curl -X POST https://target.com/graphql \
Origin

This is a copy

97% identical to idor — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

src/skills/standard/analyst/idor-analysis/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

IDOR Hunting Playbook

IDOR is the #1 source of bug bounty payouts because it's simple, ubiquitous, and scanners can't find it (authorization is business logic). Every endpoint that takes an object ID is a candidate.

1. Sources

  • URL path segments: /api/users/123/invoices/456
  • Query string: ?user_id=123
  • JSON body fields: {"orderId": 123}
  • Headers used as auth scope: X-Tenant-ID, X-Customer-Id
  • JWT claims that downstream handlers trust: sub, tenant, role
  • WebSocket subscription filters
  • GraphQL arguments (user(id: 123))

2. Audit workflow

Step 1 — enumerate object-handling endpoints

# REST
grep -rE '@(Get|Post|Put|Delete|Patch)Mapping.*\{[a-zA-Z]+Id\}' /workspace/src   # Spring
grep -rE 'router\.(get|post|put|delete)\([^)]*:id' /workspace/src                # Express
grep -rE '@app\.route\([^)]*<[a-z]+:' /workspace/src                             # Flask
grep -rE 'resources?\s+:[a-z]+' /workspace/src                                   # Rails

# GraphQL
grep -rE 'type Query|type Mutation' /workspace/src
grep -rE '\w+\(id: ID' /workspace/src

Step 2 — for each endpoint, answer three questions

  1. Does it check who the caller is? (auth middleware / decorator)
  2. Does it check whether the object belongs to the caller? (ownership check / tenant filter in the query)
  3. Does it check whether the caller's role permits the action? (RBAC / policy engine)

A "no" to question 2 = horizontal IDOR (read/write other users' data). A "no" to question 3 = vertical IDOR (regular user → admin action).

Step 3 — ownership-check grep patterns

# Django: should have .filter(user=request.user) on the queryset
grep -rE 'Model\.objects\.get\(pk=' /workspace/src | grep -v 'user=request\.user'

# Rails: should have current_user.posts.find(params[:id])
grep -rE 'Post\.find\(params\[:id\]\)' /workspace/src

# Spring: should have @PreAuthorize("#id == principal.id")
grep -rE 'findById\(id\)' /workspace/src | xargs -I{} grep -L '@PreAuthorize\|@PostAuthorize'

Read the full file on GitHub · 134 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. 11d ago First seen · 134 lines · 46 tokens per session scan B 35c393bd8d7f

Subscribe to this mod's changes

idor-analysis is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 1,420 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 97% identical to idor, differing in 5 lines, and is treated as a copy.