Risky Business Features

How private LLM inference actually works

Risky Business Features

Show Notes

In this podcast episode James Wilson chats with Tinfoil co-founder Tanya Verma about how you can run a powerful LLM in the cloud without the inference provider seeing your prompts.

Tanya talks James through how private inference works, from trusted execution environments and hardware attestation, to TLS termination and GPU isolation. Customers can verify the exact code and model processing their data, while Tinfoil and its infrastructure providers remain locked out.

That’s clever engineering… but who really needs it? Is private inference only useful if you’re doing something bad, or will it become a privacy baseline like TLS? James and Tanya discuss the costs and trade-offs, and how open weights make private inference more transparent and trustworthy.

More from Risky Business Features

Oct 2, 2026

In this solo Risky Business Features episode, James Wilson explains why “number of bugs” fixed in any given update is a misleading metric. We’ve seen up to 1,000 individual bug fixes in a single update recently, but that doesn’t give defenders the full picture they need to manage risks.

Sep 15, 2026

In this podcast episode, investigative journalist Geoff White joins James Wilson to talk about what happens to the money after ransomware gangs get a payday.

Sep 11, 2026

In this podcast episode, OpenSourceMalware founder Paul McCarty joins James Wilson to explain how researchers find and analyse malicious packages, GitHub repositories and developer tools.

Sep 3, 2026

In this podcast episode, Brad Arkin joins James Wilson to chat about the Trump administration’s call to let private entities conduct cyber operations against criminal groups.

Aug 28, 2026

In this podcast episode, James Wilson chats with Brian Krebs about the investigation that led him from recycled cybercrime handles and old forum records to the true identity of TeamPCP’s alleged leader in Perth.

See all episodes →