wakehacker

About

The problem it solves Wakehacker is an autonomous AI agent designed to make **smart contract security** analysis more **accessible**. By combining Wake Framework's battle-tested detections with AI capabilities, Wakehacker delivers automated vulnerability detection for Ethereum smart contracts. # Agentic Security Model Traditionally, security audits were commissioned exclusively by project teams, **requiring users to trust** teams to manage risks effectively. Wakehacker introduces a **new paradigm** as a next-gen utility AI agent where **security analysis is triggered autonomously by AI, users and developers**. Wakehacker is poised to become a **voice of Web3 security**. Operating 24/7, continually scanning contracts and **advocating for better security** practices, it provides findings that help build more secure systems. User Interaction and Data Flow Smart contract security analysis is available through **X (Twitter) interactions**. Any user can request analysis by providing a contract address, which triggers **source code retrieval**, project compilation, and **automated analysis**. Wakehacker also **proactively scans** deployed contracts without user requests (random selection from Etherscan). ### Initial Scan & Public Summary The first message provides a **high-level overview** of detected issues without technical details; **Risk levels** (Low/Medium/High), **Confidence ratings** (Low/Medium/High). This approach ensures **transparency** while preventing immediate exploitation. ### Detailed Reports After the initial scan & public summary, Wakehacker provides a **sample set** of detailed findings. **Complete set of findings** is available upon users request (to prevent spamming X). ### Critical Issue Handling For **high-risk, high-confidence** detections (possible criticals) Wakehacker identifies associated X accounts from Etherscan and projects are first notified **publicly** through X tag. The finding details are provided only after **associated X account confirmation**. The project architecture and development process Wakehacker is implemented as plugin to ElizaOS that triggers Wake Framework on the background. Product Integrations We had to solve two problems: 1) get source codes of a deployed contract based just on the deployed address, 2) get X account associated with a contract address. For 1) we used a service https://sourcify.dev/, for 2) scraped Etherscan. Key differentiators and uniqueness of the project All security AI-agents take Slither and some findings summary using LLMs. We use Wake, that provides less findings (lower recall), but with higher precision. The goal is to produce as less false positives as possible rather than catch as many bugs as possible. Trade-offs and shortcuts while building ## X account problem We ran into an issue with X account - the agent got shadow banned. The replies with findings are not visible. This is of course a problem we will have to solve. ## Ethical questions The question problem we were solving was how to safely disclose findings, but remain fully public and transparent. We believe building & hacking should happen in public, however can't guarantee that the service won't be triggered by malicious actors. Our solution discloses a summary and details only of low and medium impact findings, where the high-impact findings are disclosed only after a confirmation from X account associated with the contract address. Additional Features Before the hackathon, we had a wakehacker character in ElizaOS that was shit-posting about frameworks and security (character.json file). During the hackathon, we cofused on the integration with Wake Framework to allow the AI agent executing security scans of deployed smart contracts. We created plugin-wake plugin for ElizaOS.