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Security audit

Ai Agent Tools Version Changelog

Security checks for vulnerabilities and agentic risk

Overview

This skill is an informational version-check helper that fetches public GitHub release or changelog pages and does not include code execution, persistence, or hidden data access.

Before installing, be aware that generic requests about updates or latest versions may activate this skill; ask explicitly for the intended tool when multiple tools could match. The inspected artifact otherwise performs public changelog lookup and does not show hidden execution or persistence.

A.I.G

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

SkillSpector

Vulnerability Patterns
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (2)

Vague Triggers

Medium
Confidence
95% confidence
Finding
The trigger phrases are broad enough to match common requests such as '最新版本', '升级', or '检查更新', which can cause the skill to activate when the user did not clearly intend this specific workflow. In an agent system, over-broad activation can lead to unnecessary external fetching, incorrect tool selection, or unintended execution paths based on ambiguous user input.

Vague Triggers

Medium
Confidence
92% confidence
Finding
Automatic inference of the target tool from context without clear activation boundaries increases the chance that the skill will act on the wrong repository or fetch data for an unintended product. This ambiguity is especially risky in agent environments because nearby conversational context may be incomplete, stale, or attacker-influenced, leading to mis-scoped actions.

Static analysis

No suspicious patterns detected.