We're always on the lookout for passionate people to join us to work on the most exciting projects in the ZK space. If you love finding bugs and are interested in ZK, you might want to take our new challenge: zkBank.
This challenge is for everyone, and you'll have to learn a bit of everything to solve it. If you think you have what it takes, then give it a go: https://github.com/zksecurity/zkBank/tree/main
In this final post of the series, we extend univariate KZG commitments to multilinear polynomials through Mercury. Building on Gemini, we fold half of the variables at once, use polynomial division to bind this large fold to the original commitment and reduce the remaining multilinear evaluations to a batched inner product check. We then walk through the end-to-end opening protocol. We conclude by examining its proof size, prover cost and verifier cost.
In this blog post, we extend univariate KZG commitments to multilinear polynomials through Gemini. We introduce recursive partial evaluations, derive the split-and-fold identity and express each fold as a univariate identity that can be checked using KZG openings. We then walk through the end-to-end opening protocol. We conclude by examining its proof size, prover cost, and verifier cost.
Many of us are using AI to generate code. Vibe coding cryptography is especially sensitive - you have to uphold strict mathematical correctness. This can lead to wrong security guarantees and soundness bugs. We will discuss what are some patterns to do it well.
Think you have what it takes to join zkSecurity? We're raising the bar with a second challenge! Now candidates must complete both zkBank and our new Curve Machine challenge to prove their skills across the full spectrum of ZK security. Are you ready to take on both challenges?
We're thrilled to introduce our new site, [bugs.zksecurity.xyz](https://bugs.zksecurity.xyz/), a hub for exploring past vulnerabilities in ZK circuits. Dive into our growing catalog of documented bugs and learn how we've reproduced some with comprehensive scripts. Discover evaluations of prominent security tools like Circomspect and Picus, and see where they shine or stumble. We're calling on the community to join us in expanding this invaluable resource, whether by adding bugs, reproducing them, or improving our platform. Let's collaborate to elevate ZK security together!
Check out our latest blog post where we dive into the world of Zero-Knowledge Proof (ZKP) vulnerabilities, sharing our insights from replicating known ZK circuit weaknesses. We’ve launched a GitHub repo with detailed scripts to help you understand, reproduce, and learn from these vulnerabilities. Discover how this hands-on approach aids in grasping attack vectors, testing fixes, and enriching educational resources. Whether you're a researcher or a developer, this post is packed with info to enhance your knowledge and skills in ZKP security. Plus, find out how you can contribute to expanding this invaluable resource!
A series of recent papers just disproved the proximity gaps conjecture, which has everyone wondering if hash-based SNARKs are in trouble. We break down what actually happened using some helpful visuals. Think of it as understanding which parameter choices are safe versus which ones are now confirmed to be risky. The post walks you through the different security zones (proven safe, conjectured safe, and definitely not safe), explains how these new results connect to other open math problems, and shows what it means for real-world SNARKs in terms of proof sizes and performance trade-offs.
In November 2024, we found a significant inflation bug in the Aleo mainnet that could have allowed token minting without proper checks. We immediately informed the Aleo team, who swiftly addressed the issue with no detected exploitation. This post dives into the inner workings of Aleo and explains how transitions and records operate, providing insight into how the vulnerability was discovered and resolved. It's an intriguing look at blockchain security, zero-knowledge proofs, and the importance of thorough type checks to ensure robust protocol integrity.
We recently brought Leo and Aleo support to zkao, our AI-powered bug-detection tool, and put it to work on a real engagement with HumanityLink. Getting an LLM to audit a young ecosystem like Aleo turned out to be less about the model and more about what we fed it - custom prompts or skills so it actually recognizes Aleo bug patterns, a harness called cheatVM that turns findings into real end-to-end proofs of concept instead of code that just looks right, and a clear threat model that significantly cut down our false positives.