Anthropic is working on a system to prove AI models’ identity
Anthropic is working on a system to prove AI models’ identity
Anthropic has released an open-source system called FlashProve, which uses cryptography to verify that specific outputs come from designated AI models, preventing model spoofing or replacement; the system requires AI labs to publish model fingerprints for verification without disclosing model weights, and the code is open-source.
Same story4 other outlets also reported this
How the accounts differ:MarkTechPost states the proof volume is 18.78 MB; The Decoder states it is about 19 MB.
- Anthropic Research··First
Anthropic has released the verifiable reasoning system FlashProve, generating proofs at approximately 110 tokens/second on a single H100.
- MarkTechPost··+46 h 8 min
Anthropic open-sources FlashProve: using zkSNARK to prove responses from committed weights
- TechCrunch · AI··+46 h 41 min·Reading now
Anthropic is developing a system called FlashProve to verify the identity of AI models
Adds:TechCrunch mentions the system requires AI labs to release model fingerprints for verification.
- ITHome · AI··+2 d
Anthropic develops FlashProve open-source system: using cryptography to prove AI output source
- The Decoder··+3 d
Anthropic releases FlashProve prototype, using cryptography to verify if AI responses come from the claimed model
Adds:The Decoder mentions the overhead compared to normal inference is 70x-95x.
In order of publication · later reports are added as they appear · Compared by AI from each outlet’s title and summary
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.
Source: TechCrunch · AI · techcrunch.com