Home / fmind / dot · skills/ai-security-assessment/SKILL.md · GitHub

ai-security-assessment skillA

ai-security-assessment is agent-read markdown (skill) from fmind/dot: Assess AI security through adversarial scenarios, including prompt injection and tool misuse..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# AI Security Assessment

Turn a concrete AI attack path into a reproducible assessment and remediation test. [threat-model](../threat-model/SKILL.md) owns architectural analysis, [security-review](../security-review/references/code-review/GUIDE.md) owns source and dependency review, and [agent-evaluation](../agent-evaluation/SKILL.md) owns repeated-trial comparisons. Use PyRIT as the execution framework through a project-local `uv` environment.

## Workflow

1. **Record the boundary**: identify the application revision, model, retrieval sources, actors, tools, and granted authority in the [assessment record](templates/assessment.md). Reuse established target, data, action, and cost authorization; proceed autonomously within it. Keep customer evidence in the assessment project.
1. **Choose plausible scenarios**: read [attack cases](references/attack-cases.md). For each case name the attacker-controlled surface, required access, protected asset, and forbidden outcome. Include legitimate autonomous actions that must continue to succeed.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add fmind/dot/ai-security-assessment@git:20260920.f12fe11
Exact content
mdr add fmind/dot/ai-security-assessment@sha256:2dcd7bcaf02b9db1

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_3lliib4r7qyddsrr.svg)](https://markdownregistry.com/a/art_3lliib4r7qyddsrr)

1 badge views in 30 days

Versions

versioncommittedcommitsizeaudit
git:20260920.f12fe11 latest2026-09-20 f12fe11 4,780 BA view · diff
git:20260916.50d68102026-09-16 50d6810 4,780 BA view · diff
git:20260912.0ce18c02026-09-12 0ce18c0 4,793 BA view · diff
git:20260911.616be7a2026-09-11 616be7a 4,732 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (4780 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

fmind/dot · 9 stars · license MIT · pushed 2026-09-24 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_3lliib4r7qyddsrr
GET https://markdownregistry.com/api/v1/resolve?ref=fmind/dot/ai-security-assessment
GET https://markdownregistry.com/api/v1/blob/2dcd7bcaf02b9db1f221ad6cebf01984194c1fd67462dbeb3fcfa2953aa3e814

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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