Research, field notes and product news from the team building the end-to-end AI trust platform.
The line between human language and programming languages is blurring as AI agents interpret plain-language instructions as executable code. This shift democratizes…
Auditing an AI agent means more than capturing logs; it means understanding what an agent did, why it did it, and whether…
Agentic AI doesn't just generate text; it takes actions, makes decisions, and touches real systems, raising the stakes for security teams. These…
Agentic AI acts like an employee—making decisions, writing code, and taking actions—but without identity, oversight, or IAM policies. Traditional security built for…
With the Senate rejecting a federal AI moratorium, states like California and Texas are pursuing divergent rules, creating major compliance challenges for…
Questionnaire-based vendor diligence and self-attestations no longer provide real assurance in the AI era. Evidence-based, continuous technical assessment and AI Bills of…
Porting legacy human-led processes straight into agentic systems leaves them brittle and inefficient. The smarter path is to design backwards from outcomes…
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…
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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