ClawHub
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Security audit

Product

Security checks for vulnerabilities and agentic risk

Overview

This is a documentation-only product strategy skill with one real caution around potentially misleading validation tactics, but no hidden execution, persistence, credential use, or data access.

Before relying on this skill for market validation, use transparent low-risk experiments where possible, disclose unavailable features after clicks, avoid collecting payment or sensitive information under unclear claims, and treat compliance/pricing/platform facts as reference material to verify against current official sources.

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
  • 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 (1)

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

This content recommends deceptive validation methods such as Fake Door and Wizard of Oz tests without any guardrails about informed consent, minimizing user harm, avoiding dark patterns, or preserving trust. In a product-building skill, these techniques could be adopted directly by users and lead to misleading experiences, reputational damage, policy violations, or collection of demand signals under false pretenses.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.