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Security audit

Xiaohongshu Writing

Security checks for vulnerabilities and agentic risk

Overview

This writing skill has no code or system access, but it explicitly teaches users to make AI-assisted social posts look non-AI-generated while only briefly noting disclosure later.

Review before installing if you need transparent or compliant social-media workflows. The skill is technically low-risk because it is only Markdown, but users should avoid using its 'de-AI' and personal-experience phrasing to mislead readers or bypass platform disclosure rules; any AI-assisted posts should be labeled when required and firsthand claims should only be used when true.

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
Vulnerability Patterns
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • 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 (6)

Natural-Language Policy Violations

High
Category
Not specified by scanner
Confidence
97% confidence
Finding

The skill's stated goal of producing content '像人写' goes beyond ordinary style polishing and, in context, is tied to disguising AI generation. In a social content skill, that increases the risk of impersonation-like deception, policy evasion, and misleading audiences about the origin of promotional or persuasive content.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The '去AI味检查' instruction explicitly directs the model to conceal signals of AI authorship. This is dangerous because it operationalizes evasion: it provides users a step-by-step process to make synthetic content harder for readers, moderators, or compliance systems to identify.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The humanization rules explicitly advise simulating human imperfections, varying rhythm, and adding personal-sounding phrasing to avoid looking AI-generated. In context, these are not merely stylistic suggestions; they are tactics for obscuring provenance, which can enable deceptive marketing, spam, or circumvention of platform rules.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The skill explicitly promotes generating text that appears human-written and includes a dedicated '去AI味检查' section aimed at removing signs of AI authorship. In a content-generation context, this can facilitate deception of readers, platforms, or disclosure regimes that require transparency about AI-generated material.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The skill's stated goal of producing content '像人写' goes beyond ordinary style polishing and, in context, is tied to disguising AI generation. In a social content skill, that increases the risk of impersonation-like deception, policy evasion, and misleading audiences about the origin of promotional or persuasive content.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The document contains conflicting compliance guidance: it teaches users how to hide AI-like traits, yet later states AI-generated content must be labeled. This inconsistency encourages unsafe use because users are given concrete evasion tactics alongside a weaker disclosure note, undermining trustworthy and compliant deployment.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.