Back to skill

Security audit

Character Consistency Workflow

Security checks for vulnerabilities and agentic risk

Overview

This is a Markdown guide for keeping AI-generated characters visually consistent, with no executable code or hidden automation.

Install only if you want a Chinese-language character-consistency workflow. If using real performers or models, keep reference photos and meta.json private, get consent, and delete or minimize sensitive appearance details when no longer needed.

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
  • 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 (3)

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The manifest description and title are presented in Chinese, framing the skill for Chinese-language use without any indication that users may choose another language or locale. This is a natural-language policy concern because the file does not offer opt-in language selection or document a justified region-specific restriction.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The guide explicitly recommends storing personally identifying and sensitive attributes in meta.json, including age appearance, gender, skin tone, body build, distinguishing marks, and wardrobe details, but provides no privacy, consent, retention, or access-control guidance. In a character-consistency workflow this data may often describe real performers or models, so centralizing it in a structured file increases the risk of privacy leakage, profiling, or misuse if the project files are shared, synced, or exposed.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
76% confidence
Finding

The title and introduction present the material in a mixed Chinese-English format, and the document does not indicate that users can choose another language or locale. Under the policy, forcing a specific language or locale without opt-in can be a natural-language policy concern.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.