# **Request for Proposal (RFP): Integrating Large Language Models (LLMs) into Ethereum Protocol Security Research** ## 1. Overview The Protocol Security Research team seeks proposals to integrate Large Language Models (LLMs) into the workflow of its Protocol Security Research Team. The team currently invests significant manual effort in auditing Ethereum protocol codebases for clients listed on https://launchpad.ethereum.org and verifying their adherence to evolving specifications (https://github.com/ethereum/execution-specs, https://github.com/ethereum/consensus-specs/). The EF aims to reduce manual labor by leveraging LLMs for: - Ingesting and parsing specification updates - Identifying code-specification mismatches ## 2. Objectives 1. **Automated Specification Compliance** - Automatically parse and interpret the latest Ethereum specifications. - Compare specification details against various client implementations. 2. **Integration into Existing Workflows** - Provide tooling or automation that can run as part of GitHub PR checks or large-scale audits. 3. **Efficiency and Accuracy** - Reduce human error and labor, ensuring comprehensive and consistent auditing processes. ## 3. Scope of Work - **Data Ingestion and Processing** - Build mechanisms to continually parse and index the Ethereum specifications. - **Code Analysis** - Integrate static/semantic checks to verify code alignment with the specifications. - **Interface** - Present findings through GitHub checks or through a console. ## 4. Deliverables 1. **Technical Architecture & Design** - An overview of how the proposed system ingests specifications, analyzes code, and reports discrepancies. 2. **Prototype / Proof of Concept** - Demonstrate the end-to-end workflow on at least one Ethereum client. 3. **Integration Guidelines** - Documentation on how to integrate the solution into a GitHub CI/CD pipeline. 5. **Documentation** - Clear instructions for setup, maintenance, and extension. ## 5. Proposal Requirements - **Vendor Background** - Outline your experience in LLM-related solutions, code analysis, and/or Ethereum or blockchain security. - **Technical Approach** - Detail the methodologies, frameworks, and tools you plan to use. - **Project Plan & Timeline** - Provide milestones, key deliverables, and expected completion dates. - **Budget & Cost Structure** - Break down costs, including development, support, and potential licensing fees. - **References or Case Studies** - Showcase previous work in similar AI-driven or blockchain security contexts. ## 6. Evaluation Criteria - **Technical Feasibility & Innovation** - How effectively does the approach address the requirements? - **Scalability & Maintenance** - Capacity to handle frequent spec changes, multiple client codebases, and large-scale audits. - **Security & Reliability** - Demonstration of safe data handling and minimization of false positives/negatives. - **Cost & Timeline** - Overall value, clarity of milestones, and adherence to proposed schedule. - **Team Expertise** - Ability to deliver a working solution and collaborate closely with EF researchers.