Sentinel: AI Powered Smart Contract Analyzer

Hyperion HyperHack Ideathon
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Sentinel: Real-Time Smart Contract Defense Layer for Metis Hyperion

Problem Statement

Smart contract exploits are costing the ecosystem billions — and it’s not because developers don’t care about security. It’s because the tools to proactively defend against live attacks simply don’t exist. Audits are static, expensive, and quickly outdated. Most teams are forced to choose between shipping fast or staying safe. That’s the real tradeoff we want to destroy.

Solution Overview

Sentinel is a real-time smart contract defense layer built natively for the Metis Hyperion stack. Think of it like a firewall and AI auditor for your dApps — detecting threats, scoring risks, and rerouting execution before exploits drain your contracts. It’s modular, trustless, and privacy-preserving by design.

What makes Sentinel different is it doesn’t just audit contracts after they’re built — it actively protects them while they run, leveraging encrypted mempools, ZK proofs, and a self-healing mechanism that respects immutability.

Architecture Overview

Figure 1: Sentinel Architecture
Figure 1: Sentinel Architecture3107×2309 461 KB

Project Description

Sentinel is a Web3-native security layer that plugs into smart contracts without requiring devs to rewrite them. Its core features include:

  • AI-Powered Audit Engine trained on datasets from Quill Audits, ScrawID, and public audit corpora.
  • Smart Contract Firewall that inspects and filters transaction behaviors in real time.
  • Self-Healing Contracts that redirect execution to patched logic without mutating on-chain state.
  • On-Chain Security Score to build user trust and prove protocol integrity.

We’re building on Metis Hyperion because of its:

  • Encrypted mempool and zkVM execution environment
  • Parallel execution support
  • Modular, developer-friendly architecture

Developers interact with Sentinel via CLI tools, SDKs, or dashboards — making it easy to integrate security into existing workflows.

What excites us? We’re flipping the paradigm — from audits as a checkbox to security as a continuous, runtime service.

Community Engagement Features

We’re turning smart contract security into a game.

Points System

  • Earn points on-chain
  • Redeem them for Sentinel access, merch, NFTs, or governance perks
  • Leaderboard for most secure builders

Why It Works

This incentivizes adoption through a feedback loop:

  • Teams secure their projects
  • Users learn by testing
  • Communities gain trust

Getting Involved

Sentinel is more than a tool — it’s a movement to make Web3 safer by default.

Here’s how you can contribute:

  • Developers: Build the CLI, SDK, and score dashboard
  • AI Hackers: Train and tune models with audit data
  • Security Experts: Join our DAO to review patches and audit logic
  • Community Creators: Educate, test, promote — be part of the mission

Interested? DM me

Diagram Space

FIgure 2: Metis Architecture with Sentinel
FIgure 2: Metis Architecture with Sentinel3390×881 280 KB

What’s Next?

For this hackathon, we’re focusing on shipping an AI-powered audit engine with 1–2 of the above features. Long-term, Sentinel will evolve into a full-blown security operating layer for Metis and beyond.

Together, we can make Web3 unbreakable.

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its amazing how the way you craft and explain it..

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@zuzuzu
Thanks a lot, that really means a lot to me! I’m just trying to explain things clearly and honestly. Glad it came through

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yep, i kinda like your vision.. keep it up man :right_facing_fist:

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How does the self-healing mechanism work, and how does it provide security without conflicting with the immutability of smart contracts?
What benefits could this bring to the Hyperion and broader Metis ecosystem?

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@han
The self-healing method only redirects to a secure smart contract, similar to a checkpoint, that does not conflict with immutability. It will never alter the contract state or have an impact on local storage.

The advantages, in my opinion, are enormous since smart contracts always require security. whether it’s a fledgling business or an established one. Additionally, I intended to attend tech presentations and workshops, which will boost Metis’s population and Sentinel’s appeal.

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You mentioned ZK Proofs, but it’s not clear exactly where they are applied in the pipeline — audit validation? Proof of patch? Proof of no tampering?

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Hi @ThalaZikol, sorry for the confusion.
I’m using ZK proofs in the auditing process to cryptographically prove that the smart contract hasn’t been tampered with after audit and validation.

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  1. How is the smart contract firewall implemented at the protocol level?

  2. How does the AI-powered audit engine determine threat severity?

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How are the threat identified? Is it from previously known issues or does the engine detect potential logic flaw?

It would be cool if the analyzer can generate POC for the exploit.

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Hi @priyankg3, sorry for the late reply

  • At the protocol level, a smart contract firewall hooks into the execution engine (like EVM) to inspect critical operations in real time, enforcing security rules before state changes occur. On Metis, it can integrate with the Optimistic Rollup’s fraud-proof system to catch and challenge malicious transactions, with optional ZK proofs to verify integrity without revealing contract internals.

  • Threat severity will be determined using multiple sources, primarily ScrawID, a repository of known smart contract exploits used by tools like Slither and Mythril. Enriched with data scraped from public audit reports such as those from Quill Audits, disclosed vulnerabilities, and any verifiable security findings available across the ecosystem.

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Hi @ubinhash

I want to incorporate data from sources like ScrawID and various audit report findings into my platform. To keep this native and reliable, I’m planning to build a master database that aggregates these findings, but only by following strict policies that require explicit user consent before storing any audit data.

This way, the database remains accurate, compliant, and user-trusted.

Would love your thoughts on this approach!

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That’s interesting and it sounds like a pretty ambitious project (in a good way)!

Training on scrawlID will probably be very helpful at identifying existing bugs! Do you plan on incorporating some non-AI method (eg fuzzing & taint analysis) to aid the process for discovering potentially new issues?

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Hey @ubinhash, not at the moment. This project is proving to be pretty time-intensive. But definitely down to explore it after HyperHack.

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@Aryanzutshi This is :fire:
one idea that might boost Sentinel’s privacy layer is using Alith’s TEE module to run your AI audit logic securely — like detecting threats or scoring risks inside a secure enclave

makes your defense engine more trustless & keeps sensitive detection logic private — fits cleanly with your zkVM + encrypted mempool setup

worth a peek: Trusted Execution Environment (TEE) - Alith

Let me know if you have more questions.

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Hi @nidhinakranii,

Thank you so much for your Input. I will make sure to include Trusted Execution Environment (TEE) in the architecture of Sentinel.

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Would love to see this integration. Please reach out to me for more support.
@EchoPabli on tele.

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Thank you for the clear explanation. self-healing checkpoints sound like a smart way to enhance security without compromising immutability.

Just one question: How do you envision the user experience when a contract triggers a self-healing redirect? Will it be seamless or require any manual intervention?

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