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AI Security

AI is changing both what we build and how fast attackers move. This collection explores threat modeling for AI and LLM systems, AI supply chain risk, agentic workflows and protocols like MCP, and how security teams can keep design reviews ahead of AI-driven development. Practical analysis for teams securing AI in production.

Latest articles

Beyond the sandbox: Threat modeling the OpenAI and Hugging Face incident

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Beyond the sandbox: Threat modeling the OpenAI and Hugging Face incident

We explored the initial sandbox escape in the OpenAI and Hugging Face incident. Here’s what it reveals about trust boundaries, connected services, and secure design in an agentic era.

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Secure by Design: Proactive Resilience in the era of AI Supply Chain Risk and MCP

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Secure by Design: Proactive Resilience in the era of AI Supply Chain Risk and MCP

After an MCP vulnerability reportedly impacting over 150 million downloads, see why AI supply chain risk demands architectural threat modeling, not just reactive scanning.

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Calm in the Chaos: Why Threat Modeling Matters More as AI Speeds Up the Build-Exploit-Patch Cycle

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Calm in the Chaos: Why Threat Modeling Matters More as AI Speeds Up the Build-Exploit-Patch Cycle

As AI accelerates the build-exploit-patch cycle, see why threat modeling — not more scanning — is the discipline built for this moment.

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2026 Predictions: AI-Acceleration Will Shift Security Back to Design

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2026 Predictions: AI-Acceleration Will Shift Security Back to Design

With global cybercrime costs projected to hit $11.3 trillion in 2026, our predictions show why secure-by-design is becoming a business requirement, not a buzzword.

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