Thought leadership on AI runtime governance, EU AI Act compliance, prompt injection defence and the security challenges of deploying AI agents in regulated industries.
Five risk categories, weighted scoring, and go/no-go criteria. A practical framework for evaluating AI agents before production deployment.
Read articleAI is transforming cybersecurity. But who secures the AI doing the securing? When your security tools are autonomous agents, they need governance too.
Read articleWhen a bad AI decision has a dollar figure, a patient outcome, or a legal liability attached, security is not optional.
Read articleDashboards were built for human-speed decisions. When AI agents process 200 cases per hour, you need monitoring that can keep up.
Read articleThe AI security landscape shifted from model safety to agent governance. Here is what matters now.
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draft-klrc-aiagent-auth-00 proposes SPIFFE, OAuth 2.0, and WIMSE for agent identity. A technical reading of what it means and what it misses.
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Every AI governance mistake was already made with cloud. Shadow IT, shared credentials, missing audit trails. The playbook exists.
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8 dimensions, scored 0-4. A practical framework to measure where your organization stands on AI agent governance.
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Enforcement starts August 2026. Here is what to do before the deadline.
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Most teams retrofit auditability. Here are five design principles for agents that generate compliance evidence as a byproduct.
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Shared API keys mean you can't tell agents apart. Here is what real agent identity looks like.
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Three scenarios. Three cost calculations. The math is clearer than you think.
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DORA treats AI agents as ICT assets. Operational resilience testing, incident reporting, third-party risk.
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Least privilege for humans is well understood. For AI agents, it barely exists.
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The real risk is not making the model say bad things. It's making the agent do bad things.
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Ethics is about what you should build. Governance is about what you can prove you controlled.
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Kernel sandboxes lock down the process. Policy governs what the agent is allowed to do.
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Everyone knows they need "human oversight." Almost nobody agrees on what that means.
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Your teams are deploying AI agents without telling security. You need a governed path that's faster than going around you.
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Most teams log prompts and token counts. When the auditor asks what happened, the answer is incomplete.
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The threat model is fundamentally different from securing a language model.
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AI agents are deploying faster than governance can keep up. Here's what needs to change.
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