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Tom Lee
Tom Lee

Posted on • Originally published at blog.clawsouls.ai

Shadow AI Detection Tools Compared: Claw-Hunter vs openclaw-detect

Enterprise security teams have a new problem: employees are installing AI agents without approval.

As of February 2026, two open-source tools have emerged to detect OpenClaw's Shadow AI spread: Claw-Hunter from application security company Backslash Security, and openclaw-detect from AI agent visibility company Knostic.

Both solve the same problem, but with different approaches. One is a security audit tool. The other is an MDM sensor.

What Is Shadow AI?

Shadow IT refers to technology used by employees without IT department approval. Dropbox, Slack, and ChatGPT all started as Shadow IT before becoming official tools.

Shadow AI is the AI agent version of this pattern. OpenClaw is particularly prone to shadow adoption:

  • Local installation: Unlike cloud services, it's hard to detect via network traffic
  • Shell access: Can reach the file system, terminal, and browser
  • API key storage: Personal API keys stored in local config, potentially mixing with corporate credentials
  • Gateway daemon: A background service running persistently

Developers installing OpenClaw for productivity is natural. The problem is that security teams don't even know it exists.

Detailed Comparison

Claw-Hunter — Security Audit Tool

Claw-Hunter is an endpoint security audit tool built by Backslash Security (backslash.security).

Its distinguishing feature is going beyond detection to full audit:

Capability Description
Installation detection CLI binary, app bundle presence
Gateway status Background daemon running state
Shell access permissions Which shells are accessible
Credential exposure Credentials in config files
API key scanning Stored API key detection

Output is JSON format, ready for direct SIEM (Security Information and Event Management) integration. Each finding includes risk scoring at clean, warning, or critical levels.

# Example (macOS/Linux)
./claw-hunter.sh
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Built with pure bash + PowerShell, zero external dependencies. MDM support for Jamf and Intune. Licensed under MIT.

openclaw-detect — MDM Sensor

openclaw-detect is a lightweight detection sensor from Knostic (knostic.ai).

Unlike Claw-Hunter, it focuses on a single question: "Is it installed?"

Detection Target Description
CLI binary openclaw command presence
App bundle macOS .app, Windows install paths
Config files ~/.openclaw/ directory
Gateway Daemon process
Docker OpenClaw running in containers

Output is key-value text with exit codes: 0 for not found, 1 for detected. This simple interface enables support for 7 MDM platforms:

  • Jamf
  • Intune
  • JumpCloud
  • CrowdStrike
  • Addigy
  • Kandji
  • Workspace ONE

Licensed under Apache 2.0. Knostic also maintains a separate openclaw-telemetry repository, suggesting a pipeline from detection to telemetry collection.

Comparison Summary

Claw-Hunter openclaw-detect
Developer Backslash Security Knostic
Purpose Security audit Installation detection
Output JSON + risk scoring key-value + exit code
MDM support 2 (Jamf, Intune) 7
Credential scan
API key scan
Shell permission audit
SIEM integration Native JSON Manual parsing needed
License MIT Apache 2.0

Decision criteria: Choose Claw-Hunter for security audits, openclaw-detect for broad MDM coverage with quick presence checks.

Why Enterprises Are Pursuing AI Agent Detection

The existence of these tools is itself a market signal.

First, OpenClaw's adoption velocity. Two security companies independently building detection tools means enterprise customers have been asking "we don't know how much OpenClaw is deployed in our organization" frequently enough to justify the investment.

Second, the unique nature of AI agents. ChatGPT web usage shows up in proxy logs. But OpenClaw runs locally, has shell access, and stores API keys on disk. Network-based DLP (Data Loss Prevention) isn't enough.

Third, compliance requirements. Frameworks like SOC 2 and ISO 27001 require visibility into "unauthorized software" installations. AI agents are no exception.

Two Axes of Security: Infrastructure vs Content

Claw-Hunter and openclaw-detect operate at the infrastructure level. They answer "Is OpenClaw installed?" and "What permissions does it have?"

But infrastructure detection alone isn't sufficient. AI agent security has another axis:

  • Infrastructure level: Installation detection, permission auditing, credential exposure → Claw-Hunter, openclaw-detect
  • Content level: Safety verification of skills and config files the agent executes → e.g., content analysis tools like SoulScan

If infrastructure security checks "is there a lock on the door?", content security checks "what's behind the lock?" As the ClawHub malicious skill incident demonstrated, security verification of the content AI agents execute is becoming increasingly important.

The Future of AI Agent Ecosystem Security

Both tools currently target only OpenClaw. But OpenClaw isn't the only AI agent. Cursor, Windsurf, Devin, and countless agent frameworks share similar patterns — local installation, shell access, API key storage.

Expected evolution:

  1. Universal AI agent detection: Expanding from OpenClaw-specific to general agent detection
  2. Real-time monitoring: Evolving from installation scanning to real-time behavior monitoring
  3. Content security integration: Unified pipelines combining infrastructure detection + content verification
  4. Agent governance platforms: Platforms integrating detection, policy, and audit

AI agent security is still in its early stages. But two security companies simultaneously releasing open-source detection tools is a clear signal that this space is moving fast.

Conclusion

Shadow AI is already reality. And the enterprise security ecosystem has started responding.

Claw-Hunter offers deep security auditing, while openclaw-detect provides broad MDM compatibility. Both are open-source, dependency-free, and ready to run immediately.

Now that AI agents have become everyday developer tools, gaining visibility is the security team's first priority. These tools are the first step.


Originally published at https://blog.clawsouls.ai/posts/shadow-ai-detection-tools/

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