Skill Sentinel

Security analysis engine for detecting malicious code, prompt injection, data exfiltration,
and supply chain threats in AI agent skills before they execute in your environment.

Why This Exists

The agent skills ecosystem has a supply chain problem. Snyk's ToxicSkills research found
that 13.4% of skills on public registries contain critical security issues. Cisco identified
341 malicious skills in a single audit. Skills operate with the full permissions of the agent
they extend, meaning a compromised skill inherits access to your filesystem, credentials,
environment variables, and network connectivity. This scanner catches threats before they
execute.

Activation Protocol

When triggered, follow this sequence exactly.

Step 1: Identify The Target

Determine which skill needs scanning. The user will either specify a path directly or
reference a skill by name. If the target is ambiguous, ask once for clarification. Confirm
the skill directory path before proceeding.

Step 2: Inventory All Files

Read the complete contents of every file in the skill directory and any subdirectories. This
includes SKILL.md, any referenced scripts, configuration files, agent definitions, helper
files, and knowledge documents. Record the total file count and types discovered.

Do not skip any file. Malicious payloads frequently hide in auxiliary files rather than
the main SKILL.md to evade casual review. The ClawHavoc campaign specifically exploited
this pattern by placing exfiltration code in referenced helper scripts while keeping the
primary skill description clean.

Step 3: Execute Threat Analysis

Analyze every file against all eight threat categories defined below. Each category operates
independently with its own detection criteria. Process them sequentially and document
findings per category.

Threat Categories

These eight categories are derived from the Snyk ToxicSkills taxonomy and real-world
malicious skill patterns documented across pu

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