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Security audit

Resume Builder

Security checks for vulnerabilities and agentic risk

Overview

This is a resume-writing skill with expected user-provided career details and no evidence of hidden execution, persistence, credential use, or data exfiltration.

Before installing, treat resume details as personal data: provide only information needed for the resume, avoid regulated identifiers or confidential employer material, and be aware that the skill does not state explicit privacy or retention practices. The Chinese examples may indicate the default output style, so specify your preferred language when using it.

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
  • 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
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (2)

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

This skill is designed to collect and process highly sensitive personal and employment data, including names, contact details, work history, education, and potentially inferred professional profile information, yet it provides no privacy notice, data handling expectations, or minimization guidance. That omission can lead users to disclose more sensitive data than necessary without understanding retention, sharing, or model-processing risks, making accidental privacy harm more likely.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The usage examples and generated output are entirely in Chinese, while the surrounding documentation is in English, and there is no statement that the skill supports multiple languages or that Chinese is only an example. This can indicate a language/locale policy issue because the skill appears to assume a specific language without offering user choice or justification.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.