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Security audit

Github Trending

Security checks for vulnerabilities and agentic risk

Overview

This skill transparently fetches public GitHub Trending pages and prints repository rankings without credentials, persistence, or local data access.

Install this only if you are comfortable allowing the skill to make live requests to GitHub when used. It appears scoped to public trending data and does not require an API key or access to local/private data.

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
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • 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 (3)

Lp3

Medium
Category
MCP Least Privilege
Confidence
90% confidence
Finding
The skill clearly instructs execution of a Python script that performs live HTTP requests to GitHub, but the manifest does not declare any tool scope such as permissions or allowed-tools. This creates a transparency and policy-enforcement gap: an agent or reviewer may treat the skill as lower risk than it really is, while the skill can still induce network access and data exfiltration opportunities through fetched content.

Natural-Language Policy Violations

Medium
Confidence
91% confidence
Finding
The manifest description is entirely in Chinese and presents the skill's usage conditions in that language without any indication that users may interact in another language. This is a natural-language locale policy concern because the skill appears to impose a specific language rather than offering an opt-in or alternative.

Natural-Language Policy Violations

Medium
Confidence
93% confidence
Finding
The HTTP request hard-codes the Accept-Language header to "en-US,en;q=0.9", which imposes an English locale regardless of the user's preferences. This is a natural-language policy concern because the file does not offer locale opt-in/selection or explain why English is required.

Static analysis

No suspicious patterns detected.