Should you let OpenClaw pen test your system? Plus: Cybersecurity for ephemeral software

2026-04-22 · Source: IBM Technology · Field: Technology & Digital — Cybersecurity & Data Privacy, Artificial Intelligence & Machine Learning · Depth: Intermediate, extended

Summary

IBM's Security Intelligence podcast discussed the implications of AI agents in cybersecurity, focusing on Sofos's "Open Claw" experiment where an open-source AI agent acted as a red team operator in a legacy on-prem network. The agent identified 23 actionable high-quality findings, despite requiring significant guardrails to prevent malicious actions. Panelists debated the reliability of AI agents for pentesting, with some advocating for their adoption due to the inevitability of AI in security, while others highlighted challenges like managing guardrails and the potential for "shadow ephemeral IT." The discussion also covered Bruce Schneider's concept of "instant software" generated by AI, which could introduce numerous vulnerabilities if not properly managed, and the concerning trend of ransomware incidents increasing at 30% annually compared to a mere 10% rise in information security spending, emphasizing the need for effective, rather than just increased, security investment.

Key takeaway

For MLOps Engineers evaluating AI agent deployment in security, you should prioritize controlled experimentation with robust guardrails. Start with well-defined, data-rich areas like threat investigation or vulnerability scanning where AI can augment human efforts, rather than attempting full autonomy immediately. Focus on building an "always-on, ambient, predictive protective defense" system that integrates AI to operate at machine scale, understanding that effective security posture depends more on strategic implementation than just increased spending.

Key insights

AI agents offer significant potential for cybersecurity, but require careful management and integration to be effective and safe.

Principles

• Embrace AI in security; it's inevitable.
• Guardrails are crucial for AI agent safety.
• Effective spending trumps sheer budget size.

Method

Sofos's experiment involved deploying an open-source AI agent, Open Claw, in a contained legacy on-prem network, configured to act as a red team operator, to identify vulnerabilities and test its operational safety and efficacy.

In practice

• Experiment with AI agents in controlled environments.
• Prioritize AI for high-volume, data-intensive tasks.
• Implement "human in the loop" for critical AI decisions.

Topics

• Open Claw
• AI Pentesting
• Ephemeral Software
• AI Agents
• Ransomware Trends

Best for: AI Security Engineer, Security Engineer, MLOps Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by IBM Technology.