A recent cybersecurity investigation by Hudson Rock, a firm specializing in cybercrime intelligence and infostealer threat monitoring, has uncovered a real-world infostealer infection that successfully exfiltrated configuration files from an OpenClaw AI agent environment, signaling a notable shift in how malware targets sensitive data.
Unlike traditional infostealer activity focused on browser credentials, this incident involved the theft of files that define the identity, cryptographic trust, and behavioral context of a personal AI agent. The data was collected through a broad file-harvesting routine rather than a purpose-built OpenClaw module, suggesting attackers may already be gathering AI-related assets opportunistically.
Among the exposed files were:
- openclaw.json, containing workspace details and a gateway authentication token that could allow unauthorized access or impersonation if misused.
- device.json, which included both public and private cryptographic keys, potentially enabling attackers to bypass device trust controls.
- soul.md and memory files, outlining the AI agent’s behavioral rules and retaining contextual records that may reflect highly sensitive personal information.
Hudson Rock warns that as AI agents become more deeply embedded in professional and personal workflows, malware authors are likely to develop dedicated AI-stealer modules designed to specifically target these environments.
The company’s AI-powered analysis system, Enki, assessed the incident as a high-risk identity compromise, demonstrating how stolen tokens, keys, and contextual data could be combined to enable full digital impersonation.
They continue to monitor emerging infostealer tactics and emphasize that AI agent security is becoming a critical component of modern cybersecurity strategy.
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