Research, field notes and product news from the team building the end-to-end AI trust platform.
Unlike a traditional firewall that polices IP packets, an LLM firewall inspects natural language—the prompts users send and the responses models return.…
As the UN calls for global AI governance, Cranium addresses the risks raised through robust AI security, policy enforcement, and ethical development…
LLM hijacking campaigns show how attackers exploit large language models to leak data, manipulate outputs, and gain unauthorized access. Monitoring and governing…
Public LLMs offer baseline safety, but their built-in safeguards leave real gaps in security, privacy, and compliance. A dedicated AI firewall adds…
As AI grows more powerful, its decisions grow less transparent—and securing what you can't explain is just gambling. Explainability lets you trace…
Agentic AI can perceive, reason, and act autonomously, but that autonomy fails when an agent’s actions diverge from human intent. Closing this…
AI agents bring both opportunity and unique risk, and most cybersecurity programs have gaps they can't see. This framework maps AI agent…
Regex is transparent but brittle, LLMs are context-aware but non-deterministic, and Transformers stay powerful yet opaque. Cranium's deterministic semantic labeling combines their…
The clock is ticking on EU AI Act Article 4. Here's your to-do list for closing literacy gaps, training your workforce, and…
Cranium AI launched the Cranium Learning Environment, a free online platform of self-paced courses on AI security, red teaming, hallucinations, and adoption.…
See how Cranium helps your organization accelerate the secure adoption of AI — from your first model to your entire agentic supply chain.
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