Empowering Security with Verifiable zkML for AI Agents
In the ever-evolving landscape of Web3 security, ensuring the accuracy and trustworthiness of AI-powered audits is paramount. QuillAI Network has been at the forefront of this revolution with QuillShield and QuillCheck—AI security agents leveraging large language models LLMs and RL to analyze and detect vulnerabilities in smart contracts. However, such outputs, especially in security-sensitive domains, require verifiable guarantees to enhance trust and reliability.
This is where our latest collaboration with Lagrange Labs comes in. Lagrange is pioneering zkML (zero-knowledge machine learning) technology that enables verifiable inference for machine learning models, providing a cryptographic proof of correctness for AI based results. Together, we are integrating Lagrange’s cutting-edge zkML framework into QuillShield and QuillCheck, reinforcing the security and verifiability of AI based smart contract auditing and scam due diligence.
Bridging AI-Powered Security with zkML Verification
Lagrange Labs: Pushing the Boundaries of zkML
Lagrange Labs is building a next-generation zkML prover based on GKR (Garbled Circuits for Randomized Computation), outperforming existing tools like EZKL. Their framework supports arbitrary models built on ONNX representations and will soon provide verifiable inference for various neural networks, including CNNs and LLMs. This means that any AI-generated output can now be accompanied by a cryptographic proof of correctness, ensuring that developers and users can trust the model’s inferences.
QuillShield & QuillCheck: AI Agents for Web3 Security
QuillShield and QuillCheck are AI Agents that leverage LLMs for smart contract auditing and token risk assessment. These agents detect vulnerabilities, analyze token authenticity, and generate security insights that developers and investors rely on. However, in high-stakes environments, it’s essential to go beyond trust in AI and introduce verifiable guarantees for AI generated audit reports.
By integrating Lagrange’s zkML framework, we can ensure that every security inference made by QuillShield and QuillCheck is backed by a zero-knowledge proof. This eliminates uncertainty, reduces reliance on black-box AI outputs, and enhances the security posture of Web3 projects.
How zkML Enhances AI Security Verification
1. Trustless AI Inference
With zkML, the security assessments generated by QuillShield and QuillCheck can be cryptographically verified, ensuring that:
- The AI model executed correctly without any tampering.
- The model weights were not altered during inference.
- The same input consistently produces the same verified output.
This eliminates concerns about AI model drift, adversarial tampering, or undetected hallucinations in AI audits.
2. Scalable and Efficient Verification
Lagrange’s zkML prover, built on GKR, is significantly more performant than traditional zkSNARK-based ML verification. This allows for:
- Fast verification of AI-generated security reports without bottlenecks.
- Low-cost proof generation, making cryptographic verification practical at scale.
- Seamless integration into decentralized applications, enabling on-chain security attestations.
3. Reinforcing Security for Web3 Developers & Investors
For Web3 developers building dApps and smart contracts, QuillShield’s AI audit reports will now come with verifiable proof, ensuring that:
- No false positives or misdiagnoses compromise development cycles.
- Developers can confidently integrate security insights into their CI/CD pipelines.
- Investors and users can trust token assessments provided by QuillCheck, backed by zkML proofs.
The Synergy of QuillShield and Lagrange zkML
Seamless Security Verification in Web3
By combining QuillShield’s AI auditing capabilities with Lagrange’s zkML verification, we are creating a new standard for Web3 security:
- Auditable Smart Contract Security Reports: Every security issue flagged by QuillShield is verified by Lagrange’s zkML, preventing false positives.
- Provably Secure Token Risk Analysis: QuillCheck’s assessments of honeypots and rug pulls will include zkML-backed proofs, ensuring authenticity.
Getting Started: Integrating zkML into QuillShield & QuillCheck
This collaboration brings real-time, verifiable security to the Web3 ecosystem. Developers and investors can leverage this integration by:
- Using QuillShield for smart contract audits, now with zkML-backed verification.
- Running QuillCheck for token risk assessment, with cryptographic guarantees.
- Exploring zkML-powered security proofs in Web3 dApps for added trust.
About QuillShield:QuillShield is an innovative AI Agent for auditing smart contracts that uses QuillAI’s Reinforcement learning framework to continuously learn from each contract it reviews. Leveraging advanced machine learning algorithms and real-time data insights, QuillShield is redefining how developers approach smart contract security.
Run QuillShield | Demo Video | Docs
About QuillCheck:QuillCheck is an AI Agent for detection of scam, rugpull and honeypot tokens that uses QuillAI’s Reinforcement learning framework to continuously learn from user feedback from various environment sources. Leveraging advanced machine learning algorithms and real-time data insights, QuillCheck is securing users by giving them complete diligence on their tokens.
Run QuillCheck | Demo Video | Docs
About QuillAI Network:QuillAI Network is the trust and security layer for AI and Web3. QuillAI Network secures AI Agents, Chains, Wallets, and dApps with it’s hyper-intelligent SLM Network and evolves to mitigate advance threats with a verified Reinforcement Learning framework.