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ai-attack-surface

Assess AI/ML attack surfaces mapped to MITRE ATLAS v2026.06.

Updated May 11, 2026
Search Tags:#ai security#prompt injection#mitre atlas#compliance gaps#attack surface assessment#mcp supply chain#framework lag
One-click install
npx skills add https://github.com/blamejs/exceptd-skills --skill ai-attack-surface
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-attack-surface
Source: https://github.com/blamejs/exceptd-skills/tree/main/skills/ai-attack-surface
Command: npx skills add https://github.com/blamejs/exceptd-skills --skill ai-attack-surface

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Legacy security and compliance frameworks (NIST 800-53, ISO 27001, SOC 2, PCI-DSS) were designed for network-centric, on-prem or early-cloud environments and lack controls for modern AI-specific threats like prompt injection, MCP supply chain attacks, and AI-powered covert C2. This Skill eliminates that gap by providing a structured, up-to-date assessment methodology grounded in mid-2026 threat reality.

Core Features & Use Cases

  • MITRE ATLAS v2026.06 Mapped Assessment: Aligns AI attack surface findings to the latest ATLAS threat taxonomy for consistent reporting and remediation tracking.
  • Framework Gap Flagging: Explicitly identifies where common compliance controls fail to address AI-specific attack patterns, removing ambiguity during audits and risk reviews.
  • Structured Output for Downstream Tools: Generates standardized assessment reports that integrate directly with MCP trust policy tools, RAG security scanners, and incident response playbooks.
  • Use Case: A security team deploying AI coding assistants and MCP servers can use this Skill to identify unpatched supply chain vulnerabilities, quantify prompt injection exposure, and produce auditor-ready evidence of AI-specific risk coverage.

Quick Start

Use the ai-attack-surface skill to run a full assessment of your organization's AI attack surface, including LLM integrations, MCP servers, and AI coding assistants, and generate a prioritized report of compliance framework gaps and remediation steps.

Frequently Asked Questions about ai-attack-surface

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I assess my AI attack surface for prompt injection and MCP supply chain threats?▼

To assess your AI attack surface, run a comprehensive evaluation mapped to MITRE ATLAS v2026.06 to identify prompt injection, MCP supply chain compromise, and model poisoning risks in your LLM and AI coding environments.

Why do legacy compliance frameworks fail to secure AI integrations and RAG pipelines?▼

Legacy compliance frameworks fail to secure AI integrations because they lack controls for modern AI-specific threats like prompt injection and AI-as-C2. This assessment explicitly flags these framework gaps to remove ambiguity during risk reviews.

Can I map AI coding assistant vulnerabilities to the MITRE ATLAS threat taxonomy?▼

You can map AI coding assistant vulnerabilities to the MITRE ATLAS v2026.06 threat taxonomy using this assessment. It aligns findings to ATLAS TTPs and generates structured reports for consistent remediation tracking.

What is the best way to identify compliance gaps in LLM and MCP server deployments?▼

The best way to identify compliance gaps in LLM and MCP server deployments is to perform an attack surface assessment that flags unaddressed AI-specific risks and produces auditor-ready evidence of risk coverage.

Does this AI security assessment provide remediation guidance for model poisoning and AI-as-C2 risks?▼

This AI security assessment provides prioritized remediation guidance for model poisoning and AI-as-C2 risks by recommending D3FEND defensive countermeasures aligned with mid-2026 threat realities.

When do I need to evaluate AI-specific threats unaddressed by NIST 800-53 or ISO 27001?▼

You need to evaluate AI-specific threats unaddressed by NIST 800-53 or ISO 27001 when deploying LLMs, AI coding assistants, or MCP servers, requiring a structured assessment to quantify exposure and close framework gaps.

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