senseguard

What This Skill Does

SenseGuard is a specialized semantic security scanner designed specifically for the OpenClaw AI agent ecosystem. Unlike traditional antivirus software or static analysis tools that look for malicious binaries or known malware signatures, SenseGuard operates on the LLM layer. It treats agent skills—often written in natural language—as a sequence of instructions for an AI, rather than just raw code. By analyzing these instructions, it detects sophisticated threats that evade conventional detection, such as prompt injection attacks, covert data exfiltration attempts masked in documentation, zero-width character obfuscation, and unauthorized persistence commands that try to modify local memory files.

Installation

To install SenseGuard, execute the following command in your OpenClaw terminal:

clawhub install openclaw/skills/skills/fermionoid/senseguard

Once installed, the scanner.py script becomes available, allowing you to audit your installed agents and individual skill manifests immediately.

Use Cases

SenseGuard is an essential component for any developer or user managing custom OpenClaw skills. Use it when:

• You are auditing third-party skills before integrating them into your agent.
• You suspect an agent is behaving unexpectedly or ignoring core safety guardrails.
• You want to ensure that documentation files are not being used as a staging area for malicious instructions.
• You are deploying a production agent and need a security compliance check.

Example Prompts

• "SenseGuard, please run a full security audit on all my currently installed skills and report any high-risk findings."
• "Scan the 'data-processor' skill with deep semantic analysis to check for potential prompt injection vulnerabilities."
• "Run a security audit on the web-browsing skill and provide the output in JSON format so I can review the findings."

Tips & Limitations

For the best results, always utilize the --deep flag when auditing skills from untrusted sources, as this triggers the Layer 2 LLM semantic analysis. Be aware that deep scans consume more resources as they require secondary LLM inference. SenseGuard is highly effective at identifying social engineering and command injection, but it should be used as part of a defense-in-depth strategy, alongside standard file system permissions and sandbox monitoring.