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Security audit

Skill Distiller (Reference)

Security checks for vulnerabilities and agentic risk

Overview

This is a reference-only skill for compressing other skills, with disclosed local calibration logging and no evidence of hidden execution, exfiltration, or destructive behavior.

Before installing, decide whether local calibration history is acceptable in your workspace. If you use cloud LLM provider keys, compression content may be processed by that configured provider; use a local provider if the skills being compressed contain sensitive material.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (2)

Ae1

High
Category
analysis-evasion
Confidence
100% confidence
Finding

Referenced artifact was not completely inspected

Content

Scanner excerpt · SKILL.md (reported line 489)May include surrounding context.

md
anually verify you're using `--threshold=0.95` or higher. The formula variant (`SKILL.md`) should never be the input for self-compression.

Missing User Warnings

Low
Category
Not specified by scanner
Confidence
88% confidence
Finding

The skill specifies persistent logging of compression runs and later user feedback into a local .learnings/skill-distiller/calibration.jsonl file, including timestamps, skill names, token counts, and free-form outcome data, but does not clearly warn users that this data will be retained on disk. In context this is not overtly malicious, but it creates a privacy and data-governance risk because sensitive project names, prompts, metadata, or feedback details may be stored longer than users expect and could later be exposed to other local users, backups, or source control.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.