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Security audit

Elite Longterm Memory

Security checks for vulnerabilities and agentic risk

Overview

This appears to be a legitimate memory skill, but it encourages broad silent persistence of conversation details and optional third-party memory sync without enough user control or privacy disclosure.

Install only if you intentionally want an agent to keep durable memory about your work. Before using it, set rules that prohibit storing credentials, secrets, personal/health/financial data, and sensitive project details; review and prune SESSION-STATE.md, MEMORY.md, daily logs, Git notes, and vector memory regularly; enable Mem0 or SuperMemory only if you accept sending selected conversation-derived data to those providers.

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Tool MisuseTool Parameter Abuse, Chaining Abuse, Unsafe Defaults
  • Rogue AgentSelf-Modification, Session Persistence
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Findings (11)

Missing User Warnings

Medium
Confidence
94% confidence
Finding
The README promotes automatic fact extraction from conversations and optional cloud sync, but does not clearly warn users that potentially sensitive conversation content may be transmitted to third-party services or stored remotely. In an AI memory skill, users may reasonably assume local persistence only, so missing privacy and data-flow disclosures increases the risk of unintended exposure of secrets, personal data, or proprietary workspace context.

Vague Triggers

Medium
Confidence
90% confidence
Finding
The activation rule instructs the agent to write before responding based on broad categories of user input, which can cause routine conversation details to be persisted without meaningful filtering. In a memory skill, that context makes the issue more dangerous because the design goal is persistent capture across sessions, increasing overcollection risk.

Missing User Warnings

High
Confidence
96% confidence
Finding
The skill explicitly directs silent storage of decisions and preferences, without any user-facing disclosure that information will be retained. This is dangerous because users may reveal personal or sensitive data during normal interaction, and silent persistence removes the opportunity for informed consent or correction.

Missing User Warnings

High
Confidence
98% confidence
Finding
The optional cloud backup and Mem0 auto-extraction sections encourage sending conversation content to third-party services, but they do not present a clear privacy warning or consent requirement. Because this skill centers on long-term memory, external transmission materially increases confidentiality and compliance risk.

Ssd 3

Medium
Confidence
94% confidence
Finding
The instructions normalize persistent storage of user details, decisions, and preferences across sessions, creating a natural-language data retention risk. In the context of a memory system, this is not incidental logging but a core workflow, so without safeguards it can accumulate sensitive data and leak context to future sessions or agents.

Ssd 3

Medium
Confidence
95% confidence
Finding
The WAL protocol tells the agent to save user statements before responding, which encourages blanket capture of inputs regardless of sensitivity or necessity. This is dangerous because it converts transient conversation into durable records by default, increasing exposure in local files, indexes, and downstream sync targets.

Ssd 3

Medium
Confidence
96% confidence
Finding
Automatic fact extraction from conversations is promoted as a recommended feature without safeguards, implying broad ingestion of conversational content into an external memory service. This increases risk because extraction is harder for users to reason about than explicit saves and can capture sensitive facts they never intended to persist.

Session Persistence

Medium
Category
Rogue Agent
Content
- [ ] ...
```

**Rule:** Write BEFORE responding. Triggered by user input, not agent memory.

### Layer 2: WARM STORE (LanceDB Vectors)
**From: lancedb-memory**
Confidence
89% confidence
Finding
The instruction to write before responding establishes persistent session logging as a default behavior. In this skill's context, that increases the chance that routine or sensitive user content is retained automatically, making session persistence a real privacy and data-handling issue rather than a harmless note.

Session Persistence

Medium
Category
Rogue Agent
Content
User: "Let's use Tailwind for this project, not vanilla CSS"

Agent (internal):
1. Write to SESSION-STATE.md: "Decision: Use Tailwind, not vanilla CSS"
2. Store in Git-Notes: decision about CSS framework
3. memory_store: "User prefers Tailwind over vanilla CSS" importance=0.9
4. THEN respond: "Got it — Tailwind it is..."
Confidence
91% confidence
Finding
The example workflow concretely demonstrates persisting a user preference and decision into multiple storage layers before replying. That makes the retention behavior more operational and likely to be copied as-is, amplifying the privacy risk through duplication across files, vector stores, and git notes.

Tool Parameter Abuse

High
Category
Tool Misuse
Content
memory_recall query="*" limit=50

# Clear all vectors (nuclear option)
rm -rf ~/.openclaw/memory/lancedb/
openclaw gateway restart

# Export Git-Notes
Confidence
66% confidence
Finding
Although the command is scoped to ~/.openclaw/memory/lancedb/, it is still a destructive filesystem operation presented in documentation without safeguards or confirmation. In a skill context where agents may paraphrase or automate maintenance steps, destructive cleanup commands can cause data loss if copied incorrectly or run in the wrong environment.

Tool Parameter Abuse

High
Category
Tool Misuse
Content
memory_recall query="*" limit=50

# Clear all vectors (nuclear option)
rm -rf ~/.openclaw/memory/lancedb/
openclaw gateway restart

# Export Git-Notes
Confidence
66% confidence
Finding
Although the command is scoped to ~/.openclaw/memory/lancedb/, it is still a destructive filesystem operation presented in documentation without safeguards or confirmation. In a skill context where agents may paraphrase or automate maintenance steps, destructive cleanup commands can cause data loss if copied incorrectly or run in the wrong environment.

Static analysis

Detected: suspicious.destructive_delete_command

Documentation contains a destructive delete command without an explicit confirmation gate.

Warn
Code
suspicious.destructive_delete_command
Location
SKILL.md:293