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Security audit

AI懂帮我巧匠

Security checks for vulnerabilities and agentic risk

Overview

The skill is mainly a personalization assistant, but it asks agents to compile user profiles, memories, and confidential information into persistent files while making privacy claims it cannot support.

Install only if you are comfortable with the agent generating persistent local documents about your identity, work, preferences, memories, and possibly confidential information. Do not put passwords, API keys, tokens, regulated data, financial identifiers, or private personal details into the generated files; review and redact them before sharing, syncing, committing, or using them as future agent context.

Vulnerability Patterns
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • 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
Findings (1)

T09 · Insecure Skill Coding Practices

Warning
Location
SKILL.md:89
Finding

Plaintext Persistence of Sensitive User Data Under Misleading Privacy Assurances

Content
View full analysis

Vulnerability Details

File Location: SKILL.md, lines 89, 107, 409-415, 477, 578-588, and 629
Vulnerability Type: Plaintext sensitive-data storage and unsupported privacy claims
Risk Level: Medium

Vulnerable Skill Instructions

The following is an English translation of the relevant instructions:

text
Line 89:
Privacy and security come first—all data only exists on the user's own
device and will not be uploaded anywhere. Make the user feel 100% safe.

Line 107:
You can be completely assured about security: I will not store a single
character from our conversation. I only organize the information into
documents and give them to you. These materials only exist on your own
device; nobody else can see them, and the platform cannot see them.

Lines 409-415:
I will generate six files:
- SOUL.md — the AI's personality, character, and speaking style
- USER.md — the AI's knowledge of the user, preferences, and needs
- MEMORY.md — long-term memories and task progress from conversations
- TOOLS.md — experience and lessons from using tools
- SECRET.md — confidential information needed repeatedly
- EMAIL_RULES.md — behavioral and communication rules

Line 477:
Based on the user's answers, first-stage information, and reasonable
inference, generate six files.

Lines 578-588:
# SECRET.md · Confidential Information

## Sensitive Information
- [Information type]: [Usage context and precautions]

## Security Reminder
- This information is only stored locally and will not be uploaded anywhere.
- Remove sensitive content before sharing the document.

Line 629:
These files only exist on your own device, so you can be completely assured.

Technical Analysis

The Skill makes absolute claims that conversation content is not stored and cannot be seen by the platform, while subsequently directing the Agent to persist user information in several Markdown files. The contradiction is e ...[truncated 3233 chars]

Remediation
View remediation

Remediation Suggestions

  1. Remove unsupported guarantees

    • Replace claims such as “I will not store a single character,” “the platform cannot see it,” and “100% safe” with an accurate disclosure of what is collected, where it is written, and who may be able to access it.
    • Do not claim local-only storage unless the implementation verifies and enforces that property.
  2. Eliminate the plaintext secret file

    • Remove SECRET.md from the workflow.
    • Explicitly instruct users not to provide passwords, API keys, access tokens, private keys, financial identifiers, medical information, or other regulated data.
    • Where sensitive persistence is essential, use an approved encrypted secret store rather than Markdown.
  3. Require informed consent

    • Before writing files, display the proposed filenames, destination, information categories, retention behavior, and access implications.
    • Require explicit opt-in consent and allow users to exclude individual fields.
    • Present a redacted preview of the exact content before persistence.
  4. Minimize and classify collected data

    • Collect only fields necessary for the stated personalization purpose.
    • Separate user-confirmed facts from Agent inferences.
    • Do not persist inferred sensitive attributes without explicit confirmation.
    • Apply allowlists for acceptable fields and automatic detection or redaction for likely credentials and secrets.
  5. Protect persisted data

    • Use a dedicated private storage directory with least-privilege filesystem permissions.
    • Encrypt sensitive profiles at rest when supported.
    • Prevent generated files from being placed in source-controlled or publicly shared locations by default.
    • Warn users about backup, synchronization, repository, and document-sharing exposure.
  6. Implement lifecycle controls

    • Define a short retention period appropriate to the feature.
    • Provide clear comm ...[truncated 442 chars]
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Findings (10)

Tp2

High
Category
MCP Tool Poisoning
Confidence
85% confidence
Finding

Mixing characters from multiple Unicode scripts in a single identifier is a common technique to create visually ambiguous tool names.

Content

No source excerpt is available for this finding.

Ssd 3

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The skill explicitly instructs the agent to compile user knowledge, memory, tool-use experience, and secrets into dedicated files. Persisting such a consolidated dossier creates a sensitive profile that could expose personal preferences, workflows, confidential data, and inferred behavioral patterns if accessed or shared improperly.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The skill assures users that nothing is stored and that data exists only on their device, yet later instructs creation of persistent documents containing profiling data. This is dangerous because it misleads users about retention and exposure, undermining informed consent around collection of personal and behavioral information.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The second stage repeats strong privacy assurances while directing the agent to compile long-term memory, secret, and behavior files. This contradiction is dangerous because it normalizes extraction and persistence of sensitive user details under false assurances, increasing the chance users reveal information they otherwise would withhold.

Content

No source excerpt is available for this finding.

Ssd 3

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The '搜魂大法' stage is designed to surface remembered user details, long-term memory, and 'secrets' back to the user as files. This is dangerous because memory introspection features can overexpose accumulated sensitive context and train users to normalize secret extraction/export, making accidental leakage far more likely.

Content

No source excerpt is available for this finding.

Ssd 3

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The provided templates operationalize storage and output of sensitive details including preferences, feedback history, task progress, and confidential information. Structured templates make the risky behavior repeatable and scalable, turning ad hoc disclosure into systematic retention of user dossiers.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
84% confidence
Finding

The manifest limits the skill to helping AI understand the user and says it does not directly help complete work tasks. However, the documented behavior includes analyzing the user's work, recommending tools, and producing concrete operational action plans, which goes beyond mere user-profile generation into work-planning assistance.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

Broad triggers such as '小懂' or generic phrases can cause unintended invocation during ordinary conversation, pulling users into a flow that solicits personal profiling information. In this skill, accidental activation is more dangerous because the workflow collects identity, work, preference, and potentially sensitive memory data.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The template hard-codes the language field as "中文" in the generated user booklet, and the surrounding instructions are written as if Chinese is the required default behavior. There is no opt-in, alternative language path, or documented reason that the skill must operate only in Chinese.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

Directing the skill to create a dedicated SECRET.md encourages centralization of confidential material in a plaintext-style artifact. Such aggregation increases the blast radius of accidental disclosure, local compromise, or unintended sharing, especially because the skill is framed as casual chat assistance rather than a secure secrets manager.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.