Security audit

Monitor Buying Consultant

Security checks for vulnerabilities and agentic risk

Overview

This is a pure instruction-based monitor buying guide with no code execution, persistence, or credential access, though users should note it does include named product suggestions despite claiming to be brand-neutral.

Install this only if you want the agent to guide monitor purchases and potentially name specific models. Treat product suggestions as research starting points, verify current specs, prices, warranty, and availability yourself, and be aware that the skill asks for location and hardware details to tailor advice.

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

Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access

Findings (4)

Ae4

Medium

Category: analysis-evasion
Confidence: 80% confidence
Finding: Suspicious Unicode normalization or mixed-script content

Description-Behavior Mismatch

Medium

Confidence: 95% confidence
Finding: The manifest markets the skill as brand-neutral, but the instructions later require recommending specific real monitor models by region. This creates a policy-integrity mismatch that can mislead users about neutrality and opens the door to covert product steering, affiliate-style influence, or undisclosed commercial bias under the guise of impartial advice.

Intent-Code Divergence

Medium

Confidence: 98% confidence
Finding: The skill explicitly says it will not recommend specific brands, then later mandates suggesting real products and models. Contradictory instructions like this can be exploited to mask promotional behavior, confuse auditors, and erode user trust because the user is told the consultation is independent while the workflow ultimately steers them toward named products.

Vague Triggers

Low

Confidence: 89% confidence
Finding: This markdown file includes activation examples such as "help me choose a monitor" and "best monitor for me," which are broad natural-language phrases rather than tightly scoped invocation triggers. Although the surrounding section provides some scope and negative examples, these phrases remain vague enough to match routine conversation and could cause unintended skill activation in systems that rely on phrase matching.

Static analysis

No suspicious patterns detected.