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Security audit

马斯克神经记忆

Security checks for vulnerabilities and agentic risk

Overview

This memory skill is not deceptive, but it asks the agent to automatically store and reuse conversation memories across sessions without enough user control or privacy boundaries.

Review this before installing if your conversations may contain secrets, customer data, regulated information, or private project details. Use it only where persistent memory is intended, and prefer explicit confirmation before storing, recalling, or transferring memories across projects.

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
Findings (1)

other

Warning
Location
SKILL.md:118
Finding
Automatic Persistent Capture and Cross-Session Reuse of Conversation Data## Vulnerability Details **File Location**: `SKILL.md`, lines 52-72, 118-132, and 136-145 **Vulnerability Type**: `other: Unconsented Persistent Conversation Data Collection` **Risk Level**: Medium ### Relevant Skill Instructions The following is an English rendering of the complete relevant source segments: ```markdown | Tool | Purpose | When to use | |------|---------|-------------| | `nmem_remember` | Store memories | After decisions, errors, facts, insights, or user preferences | | `nmem_recall` | Query memories | Before tasks, when users reference previous context, or ask "Do you remember..." | | `nmem_context` | Obtain recent memories | At session start and when injecting fresh context | | `nmem_todo` | Quick TODO with 30-day expiration | Task tracking | | Tool | Purpose | When to use | |------|---------|-------------| | `nmem_auto` | Automatically extract memories from text | After important conversations; automatically capture decisions, errors, and TODOs | | Tool | Purpose | When to use | |------|---------|-------------| | `nmem_transplant` | Transfer memories between brains | Cross-project knowledge sharing | ``` ```markdown ## Workflow ### At session start 1. Call `nmem_context` to inject recent memories into awareness. 2. If the user mentions a specific topic, call `nmem_recall`. ### During the conversation 3. When a decision is made: call `nmem_remember` with `type="decision"`. 4. When an error occurs: call `nmem_remember` with `type="error"`. 5. When the user states a preference: call `nmem_remember` with `type="preference"`. 6. When asked about past events: call `nmem_recall`. ### At session end 7. Call `nmem_auto` with `action="process"` to process important conversation excerpts. 8. Automatically extract facts, decisions, errors, and TODOs. ``` ```markdown | Parameter | Type | Range | Default | Description | |-----------|------|-------|---------|-------------| | ...[truncated 2560 chars]
Remediation
## Remediation Suggestions 1. Set `autoCapture` and `autoContext` to `false` by default and require explicit, informed opt-in. 2. Present the exact content proposed for storage and obtain confirmation before persisting it. 3. Detect and redact passwords, API keys, authentication tokens, financial data, personal identifiers, and other sensitive material. 4. Isolate memory by authenticated user, tenant, session, and project using deny-by-default access controls. 5. Require separate confirmation and authorization before `nmem_transplant` transfers any memory across project boundaries. 6. Encrypt memory data in transit and at rest, and avoid recording secrets in logs or diagnostic output. 7. Add configurable retention periods, automatic expiration, searchable deletion, export, and complete revocation controls. 8. Record provenance, creation time, owner, intended scope, and expiration for every memory. 9. Treat recalled memories as untrusted contextual data. Never interpret recalled instructions as higher-priority Agent or system instructions. 10. Require confirmation before recalled data is exposed to another user, project, external tool, or model. 11. Document the storage location, threat model, authorization rules, and privacy guarantees. 12. Add tests covering tenant isolation, deletion, secret redaction, malicious stored instructions, and unauthorized cross-project transfer.
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)

Missing User Warnings

High
Confidence
96% confidence
Finding
The skill is centered on persistent memory, automatic context injection, and automatic extraction of facts, decisions, errors, TODOs, and preferences, yet it provides no clear privacy notice, retention warning, consent model, or guidance on sensitive data handling. In practice, this can lead to silent long-term storage of personal, confidential, or regulated information across sessions, making over-collection and unintended disclosure much more likely.

Vague Triggers

Medium
Confidence
91% confidence
Finding
The skill metadata explicitly instructs proactive use in many ordinary situations, including new tasks, user references to past conversations, decisions, errors, and causality questions. This broad trigger surface can cause the memory skill to activate without clear user intent, increasing the chance of unnecessary persistence and retrieval of prior context, especially when combined with autoContext/autoCapture behavior described later in the file.

Natural-Language Policy Violations

Medium
Confidence
88% confidence
Finding
整份技能描述与调用说明均以中文固定呈现,且未说明是否支持根据用户偏好切换语言,也未给出仅限中文场景的合规或业务理由。根据语言/locale 政策,若未提供用户选择或明确正当性,固定语言输出可能构成自然语言策略违规。

Static analysis

No suspicious patterns detected.