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.
npx skills add MingyiSecLab/Mingyi-Atlas --skill idor-analysisgit clone --depth 1 https://github.com/MingyiSecLab/Mingyi-AtlasWrote 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.
[](https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/idor-analysis)<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.
<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>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.
| Model | Per session | Once 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 |
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 \ 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.
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
- Does it check who the caller is? (auth middleware / decorator)
- Does it check whether the object belongs to the caller? (ownership check / tenant filter in the query)
- 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'
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.
- 11d ago First seen · 134 lines · 46 tokens per session scan B 35c393bd8d7f
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.
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