Claroty Claire: How AI Security Agents Are Reshaping Cyber-Physical Defense

Claroty Claire: A New Era for AI-Powered Infrastructure Security

Claroty has announced the launch of Claroty Claire, an AI-powered security agent specifically designed to defend cyber-physical systems (CPS). Built on a language model trained with over a decade of industry expertise, Claire represents a significant shift in how organizations approach mission-critical infrastructure protection. But this innovation also raises important questions about the risks inherent in deploying LLM-based tools in high-stakes environments.

Why This Matters: The Expanding Attack Surface

Cyber-physical systems control everything from power grids to manufacturing plants to water treatment facilities. As AI itself becomes more powerful—and more weaponized—the attack surface for critical infrastructure has grown exponentially. Claroty's move to develop a CPS-native AI agent signals that traditional security tools are no longer sufficient for defending these mission-critical assets. The expansion of AI capabilities has created a paradox: AI can defend infrastructure more effectively, but it also enables more sophisticated attacks.

The Core Challenge

Claire's approach centers on understanding CPS-specific vulnerabilities through domain-specific training. This is smart architecture. However, deploying large language models in critical infrastructure environments introduces new risks that security teams and AI builders must carefully consider.

The Hidden Risks: LLM Vulnerabilities in Critical Systems

When you deploy LLM-based agents in cyber-physical environments, you inherit a new class of risks:

• Prompt Injection Attacks: Attackers could craft malicious inputs to manipulate Claire's decision-making, potentially causing false alerts or missed threats
• Hallucination Risks: LLMs can generate confident but incorrect responses, which in critical infrastructure could have catastrophic consequences
• Model Poisoning: Training data could be compromised, causing the security agent to learn incorrect threat patterns
• Black-Box Decision Making: Security teams need to understand why an AI agent made a decision—opacity is unacceptable in infrastructure defense
• Adversarial Examples: Sophisticated attackers can craft inputs specifically designed to fool AI-based security systems

What Builders Should Do Next: Essential Guardrails

Organizations implementing AI security agents in critical infrastructure need robust guardrails. These aren't optional—they're essential for safe deployment.

1. Implement Explainability Layers

Every decision the AI makes should be traceable and explainable to human operators. This requires building interpretability into the system architecture from day one, not bolting it on afterward.

2. Create Multi-Stage Validation

Don't allow LLM outputs to directly trigger infrastructure changes. Implement human-in-the-loop verification for critical actions, with clear escalation procedures.

3. Test for Adversarial Robustness

Red-team your AI security tools specifically for prompt injection, jailbreak attempts, and adversarial examples before deployment. This should be continuous, not one-time.

4. Establish Data Provenance

Know where your training data comes from. For CPS models like Claire, ensure that training data is clean, representative, and continuously validated against real-world threat intelligence.

5. Build Graceful Degradation

Systems should fall back to rule-based, deterministic security protocols if the AI component becomes compromised or unreliable.

The Bottom Line

Claroty Claire represents an important evolution in AI-driven security for critical infrastructure. However, as Help Net Security reports, the rise of AI-powered agents in high-stakes environments means builders must prioritize security architecture alongside capability. The future of infrastructure defense depends not just on smarter AI, but on AI systems that are transparent, robust, and fail safely. Organizations deploying these tools should demand rigorous guardrails—and builders should design with guardrails first, features second.