ADR: Skill for Claude Code

.claude/skills/submit-malicious-skill/SKILL.md

submit-malicious-skill is a skill for Claude Code from uber/ADR. It costs 65 tokens per session (768 once invoked), scanned A, original, Apache-2.0.

A workflow for reporting a malicious agent skill as a GitHub issue, including the skill's identifying hash and archive. A GitHub issue is a trackable report in a repository.

In plain words
What is it for?
It is for checking a skill archive, collecting its provenance and hash, asking for supporting details, and attaching the archive to a report.
Why use it?
It provides a defined way to preserve evidence and send a suspected malicious skill to the maintainers.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is uber/ADR's own configuration. It tells Claude Code how to work on ADR itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ADR configures →

About the project

ADR is an enterprise security system for AI agents that discovers AI tools, records agent activity, tests defenses, detects threats, and helps prevent unsafe actions. Organizations use it to secure employee-facing coding agents and customer-facing support agents; the catalogue contains one skill related to ADR.

uber/ADR · 2,083 stars · on GitHub · arxiv.org

Reuse

Borrowing it

Nothing to install: this file belongs to uber/ADR. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/uber/ADR/main/.claude/skills/submit-malicious-skill/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/uber/ADR

Made for: Claude Code.

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 submit-malicious-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/uber/adr/submit-malicious-skill/github.svg)](https://agentmods.dev/skills/uber/adr/submit-malicious-skill)
Your own site
<a href="https://agentmods.dev/skills/uber/adr/submit-malicious-skill"><img src="https://agentmods.dev/badge/skills/uber/adr/submit-malicious-skill/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 submit-malicious-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/uber/adr/submit-malicious-skill"><img src="https://agentmods.dev/badge/skills/uber/adr/submit-malicious-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 768 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.
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 $0.00065 $0.00768
Opus 5.5 $0.00026 $0.00307
Sonnet 5.5 $0.00013 $0.00154
Haiku 4.5 $0.00006 $0.00077

Measured 13d ago against content hash db97cbdf09bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

submit-malicious-skill 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 13d 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.

.claude/skills/submit-malicious-skill/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Report a malicious skill

You prepare one GitHub issue on the ADR repository. The skill's zip is attached to the issue on GitHub after it is created.

1. Identify the skill

You need its folder hash (skill_sha256, 64 hex characters) and its zip.

  • Take both from a Discovery snapshot: skill assets carry skill_sha256, install_path, provenance and, when the scan ran with --archive-skills, archive.path.
  • No snapshot, or no archive? Scan with archiving on: adr-discovery --output-dir OUT --archive-skills (or python -m adr_discovery.cli ... from Discovery/), and read the skill from the newest OUT/snapshot-*.json.
  • Check the zip is that skill. This must print the skill_sha256:
    python -c "import sys; from adr_discovery.archive import zip_content_sha256; print(zip_content_sha256(open(sys.argv[1], 'rb').read()))" <zip>
    

Ask the user in their own words why the skill is malicious, and for any public links that back it up.

If provenance shows a private or local marketplace, ask whether the skill belongs to their organisation. If it does, it should be reported there, not here.

2. Prepare the issue

Title: Malicious skill: <name> (<first 12 hex of skill_sha256>)

Body:

**Skill:** `<name>`
**Folder hash (`skill_sha256`):** `<skill_sha256>`
**Source:** <marketplace and plugin with version, and the marketplace repo, if public; otherwise "local or private">
**Seen at:** `~/<home-relative install path>`

**Why it is malicious**
<the user's reason>

**References**
- <https links, if any>

**Verify the attached zip**
`zip_content_sha256` of the zip must print the folder hash above:
`python -c "import sys; from adr_discovery.archive import zip_content_sha256; print(zip_content_sha256(open(sys.argv[1], 'rb').read()))" <skill_sha256>.zip`

**Proposed indicator**
```json
{"id": "skill-<name>-<first 12 hex>", "status": "active", "kind": "skill_sha256",
 "summary": "<one sentence: what the skill does>", "references": [...],
 "target": {"sha256": "<skill_sha256>"}}
```

Read the full file on GitHub · 74 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. 13d ago First seen · 74 lines · 65 tokens per session scan A db97cbdf09bf

Subscribe to this mod's changes

submit-malicious-skill is a skill published in the GitHub repository uber/ADR (2,083 stars, last pushed 3d ago), licensed Apache-2.0. It adds 65 tokens to every session and 768 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-14.

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