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Security audit

Ai Agent Builder Zh

Security checks for vulnerabilities and agentic risk

Overview

This is a Markdown-only Chinese guide for designing AI agents, with no executable code or hidden behavior found.

Installers should treat this as general architecture guidance. If using its examples in a real enterprise agent, add explicit user consent, data minimization, retention limits, and confirmation before storing customer preferences or writing to CRM/Feishu-style systems.

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
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (3)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The Usage section lists open-ended prompts such as “帮我设计...” and “如何给智能体加上长期记忆...”, which are common natural-language requests rather than narrowly scoped activation phrases. The file does not provide explicit trigger constraints, exclusions, or negative examples to clarify when this skill should or should not activate.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The skill explicitly recommends long-term memory of user preferences and automated writes to external documents, but it does not mention consent, data minimization, retention limits, or confirmation before persistence. In an enterprise agent context, this can lead to unauthorized storage of personal or sensitive business data and unintended modification of systems like Feishu documents.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
78% confidence
Finding

The skill name and description are explicitly Chinese-focused, and the usage/examples are entirely in Chinese, which can imply a fixed language experience. There is no statement that users may interact in another language or opt into Chinese output.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.