VeriChat: An Agentic Conversational AI Assistant for Hardware Security Verification
On the map: LLM agents and tool use → Agent threats, guardrails and governance
Abstract (arXiv)
Hardware security verification is a multi-stage process in which engineers must navigate complex design analyses, threat considerations, and verification strategies. They often need security-focused guidance, yet current verification environments provide little structured support for such assistance. Although conversational AI could offer such on-demand assistance, directly using general-purpose chatbots like ChatGPT or Gemini is risky due to their tendency to hallucinate and their reliance on static, outdated knowledge. We present VeriChat, a domain-specialized conversational assistant designed to support, rather than replace, existing verification workflows by providing context-aware security guidance. VeriChat employs a retrieval-augmented, multi-agent workflow in which three specialized agents collaboratively minimize hallucinations while improving the transparency and reliability of the response. Beyond question answering, VeriChat integrates open-source EDA tools, including Icarus Verilog, Yosys, and SymbiYosys, to perform syntax checking, synthesis analysis, simulation, and formal verification directly on user-provided RTL designs. Evaluated using a comprehensive methodology, VeriChat achieves a Faithfulness score of 87.73%, significantly outperforming the leading proprietary models. We demonstrate the framework through a hardware Trojan detection case study on an AES S-Box IP, where VeriChat autonomously identifies, simulates, and formally proves a covert key-leakage vulnerability through a multi-turn conversational workflow.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 16 of its 28 references that are in the map. First posted on arXiv 2 Jul 2026.
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16 of 28 references.
Closest ancestors · 2
Same direction, newest first
- 2026Can Agents Secure Hardware? Evaluating Agentic LLM-Driven Obfuscation for IP Protection14 Apr
- 2025SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models25 Jun
Other references · 14
- 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,184
- 2023Query Rewriting for Retrieval-Augmented Large Language Modelscited by 213
- 2023ChatEDA: A Large Language Model Powered Autonomous Agent for EDAcited by 122
- 2019Improving Multi-turn Dialogue Modelling with Utterance ReWritercited by 58
- 2023LLM for SoC Security: A Paradigm Shiftcited by 22
- 2024A Surprisingly Simple yet Effective Multi-Query Rewriting Method for Conversational Passage Retrievalcited by 14
- 2025Enhancing Large Language Models for Hardware Verification: A Novel SystemVerilog Assertion Datasetcited by 10
- 2025ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verificationcited by 7
- 2024ORAssistant: A Custom RAG-based Conversational Assistant for OpenROADcited by 4
- 2025ChatIoT: Large Language Model-based Security Assistant for Internet of Things with Retrieval-Augmented Generationcited by 4
- 2019RTL-PSC: Automated Power Side-Channel Leakage Assessment at Register-Transfer Levelcited by 2
- 2026AI-Assisted Hardware Security Verification: A Survey and AI Accelerator Case Studycited by 2
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