PunchNJC suspends three judges, disciplines six othersThe Jerusalem PostPalestinian delegation seeks resolutions critical of Israel at UN General Assembly - report한겨레삼성바이오 부분파업 돌입…법원 요건 맞춰 전면파업은 3주 뒤 예고Daily MaverickNew wave of bomb hoaxes hits dozens of flights across EuropeZDF heuteEntdecken Sie das ZDF-NachrichtenstudioVarietyPriyanka Chopra Jonas, Russell Crowe Sci-Fi Thriller ‘Bluefly’ Adds ‘Beast’ Star Daniel MacPherson (EXCLUSIVE)سكاي نيوز عربيةهيغسيث يدافع عن خطته لإعادة هيكلة البنتاغون ويعلق عن "عزله"Seeking AlphaGEO forecasts Q4 2026 revenue $777M-$827M with adjusted EBITDA $149M-$154M as ICE activations expandDaily MailBondi Beach massacre death toll rises to 16: Survivor dies from complications resulting from their injuries almost eleven months laterSDP EspectáculosFrida Sofía acusa a Alejandra Guzmán de proteger a Enrique Guzmán pese a su denunciaNew Straits TimesSarawak polls set for Dec 12Globo EsporteCom golaço de Kaio Jorge, Cruzeiro vira sobre o Bahia e fica perto de confirmar vaga na Libertadores
The Daily Newsstand · Free, Always
Friday, November 6, 2026

Anthropic is working on a system to prove AI models’ identity

Translate

Anthropic is working on an open-source system to verify which AI model produced a given output, according to a blog post published Tuesday. The system, called FlashProve, is built to provide what researchers call “provable inference” – a cryptographic proof, essentially a mathematical guarantee, that a given output came from a specific model. It’s meant to let users confirm that the answer they received really came from the model they think they’re using.

Similar to cryptographic email signatures that let recipients confirm a message really came from its claimed sender, FlashProve would be robust against impostors attempting to disguise one model as another, even when the impostor is the lab that built and runs the model. In particular, the researchers note that the system could be used to prevent an AI company from secretly swapping in a cheaper model to cut costs, or a more expensive model to inflate its performance results.

FlashProve could also be used to verify claims by third parties that a specific task was done by an advanced model. “A developer might claim that their software library was scanned for vulnerabilities by a frontier cybersecurity model, or a company might claim that its business plan was given the go-ahead by an appropriate model,” the researchers write. “How can a user verify these claims?”

To work, the system requires AI labs to publish a “fingerprint” of each model they release that can later be matched to specific outputs and verified cryptographically. Crucially, the fingerprints don’t reveal a model’s weights, the internal numbers that define how it behaves and which closed-model makers like Anthropic and OpenAI keep private. That means labs could publish the fingerprints without giving up their most valuable asset, enabling the system to work with commercial models, too. The system is also designed to be lightweight, so verification could be performed on a local device.

As part of the announcement, researchers released a detailed technical specification and working code for various elements of the system, which is publicly available under an open-source license on GitHub. Research in the system is ongoing, and there are no plans to deploy it at Anthropic or any other lab.

“This research post is meant to share intermediate progress, and not a completed research agenda,” researchers explain in the announcement post. “We are sharing this explicitly with the goal that others look at what we have done, take it, and improve it.”

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

Russell Brandom has been covering the tech industry since 2012, with a focus on platform policy and emerging technologies. He previously worked at The Verge and Rest of World, and has written for Wired, The Awl and MIT’s Technology Review. He can be reached at [email protected] or on Signal at 412-401-5489.

View the original on TechCrunch →

KioskNews shows a cleaned-up reading view extracted from the publisher’s page — the original always lives on their site, not ours.