Cover Image

Unleashing the Power of LLM to Infer State Machine from the Protocol Implementation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wei, Haiyang, Chen, Ligeng, Du, Zhengjie, Wu, Yuhan, Huang, Haohui, Liu, Yue, Cheng, Guang, Xu, Fengyuan, Wang, Linzhang, Mao, Bing
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Zero-Permission Manipulation: Can We Trust Large Multimodal Model Powered GUI Agents?
by: Qian, Yi, et al.
Published: (2026)

Unleashing GHOST: An LLM-Powered Framework for Automated Hardware Trojan Design
by: Faruque, Md Omar, et al.
Published: (2024)

LLM-Assisted Model-Based Fuzzing of Protocol Implementations
by: Huang, Changze, et al.
Published: (2025)

Unleash the Power of Ellipsis: Accuracy-enhanced Sparse Vector Technique with Exponential Noise
by: Liu, Yuhan, et al.
Published: (2024)

Everything You Wanted to Know About LLM-based Vulnerability Detection But Were Afraid to Ask
by: Li, Yue, et al.
Published: (2025)

Towards Next-Generation Steganalysis: LLMs Unleash the Power of Detecting Steganography
by: Yang, Minhao Bai. Jinshuai, et al.
Published: (2024)

Automatic State Machine Inference for Binary Protocol Reverse Engineering
by: Yang, Junhai, et al.
Published: (2024)

BrokerChain: A Blockchain Sharding Protocol by Exploiting Broker Accounts
by: Huang, Huawei, et al.
Published: (2024)

State Machine Mutation-based Testing Framework for Wireless Communication Protocols
by: Rashid, Syed Md Mukit, et al.
Published: (2024)

When LLMs Copy to Think: Uncovering Copy-Guided Attacks in Reasoning LLMs
by: Li, Yue, et al.
Published: (2025)

Automated Side-Channel Analysis of Cryptographic Protocol Implementations
by: Nasrabadi, Faezeh, et al.
Published: (2025)

If LLMs Would Just Look: Simple Line-by-line Checking Improves Vulnerability Localization
by: Li, Yue, et al.
Published: (2024)

A Systematic Study of Code Obfuscation Against LLM-based Vulnerability Detection
by: Li, Xiao, et al.
Published: (2025)

"MCP Does Not Stand for Misuse Cryptography Protocol": Uncovering Cryptographic Misuse in Model Context Protocol at Scale
by: Yan, Biwei, et al.
Published: (2025)

Here Comes The AI Worm: Unleashing Zero-click Worms that Target GenAI-Powered Applications
by: Cohen, Stav, et al.
Published: (2024)

Classifying Implementations of Cryptographic Primitives and Protocols that Use Post-Quantum Algorithms
by: Mallick, Tushin, et al.
Published: (2025)

The Quantum Cryptography Approach: Unleashing the Potential of Quantum Key Reconciliation Protocol for Secure Communication
by: Sharma, Neha, et al.
Published: (2024)

GRIDAI: Generating and Repairing Intrusion Detection Rules via Collaboration among Multiple LLM-based Agents
by: Li, Jiarui, et al.
Published: (2025)

Usability as a Weapon: Attacking the Safety of LLM-Based Code Generation via Usability Requirements
by: Li, Yue, et al.
Published: (2026)

Beyond Code Reasoning: Specification-Anchored Auditing of Multi-Implementation Distributed Protocols
by: Kamba, Masato, et al.
Published: (2026)

An Open-source Implementation and Security Analysis of Triad's TEE Trusted Time Protocol
by: Bettinger, Matthieu, et al.
Published: (2025)

Joint Optimization of Prompt Security and System Performance in Edge-Cloud LLM Systems
by: Huang, Haiyang, et al.
Published: (2025)

Measuring the Security of Mobile LLM Agents under Adversarial Prompts from Untrusted Third-Party Channels
by: Du, Chenghao, et al.
Published: (2025)

A Survey of Protocol Fuzzing
by: Zhang, Xiaohan, et al.
Published: (2024)

From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agents Workflows
by: Ferrag, Mohamed Amine, et al.
Published: (2025)

Do Reasoning LLMs Refuse What They Infer in Long Contexts?
by: Fu, Yu, et al.
Published: (2026)

RulePilot: An LLM-Powered Agent for Security Rule Generation
by: Wang, Hongtai, et al.
Published: (2025)

SemFuzz: A Semantics-Aware Fuzzing Framework for Network Protocol Implementations
by: Sun, Yanbang, et al.
Published: (2026)

An Empirical Analysis of EOS Blockchain: Architecture, Contract, and Security
by: Liu, Haiyang, et al.
Published: (2025)

All You Need Is A Fuzzing Brain: An LLM-Powered System for Automated Vulnerability Detection and Patching
by: Sheng, Ze, et al.
Published: (2025)

Whispering Agents: An Event-driven Covert Communication Protocol For the Internet of Agents
by: Huang, Kaibo, et al.
Published: (2025)

Revealing Adversarial Smart Contracts through Semantic Interpretation and Uncertainty Estimation
by: Liu, Yating, et al.
Published: (2025)

Binding Agent ID: Unleashing the Power of AI Agents with accountability and credibility
by: Lin, Zibin, et al.
Published: (2025)

Penetrating the Hostile: Detecting DeFi Protocol Exploits through Cross-Contract Analysis
by: Li, Xiaoqi, et al.
Published: (2025)

LLM-IFT: LLM-Powered Information Flow Tracking for Secure Hardware
by: Mashnoor, Nowfel, et al.
Published: (2025)

ConneX: Automatically Resolving Transaction Opacity of Cross-Chain Bridges for Security Analysis
by: Liang, Hanzhong, et al.
Published: (2025)

MALF: A Multi-Agent LLM Framework for Intelligent Fuzzing of Industrial Control Protocols
by: Ning, Bowei, et al.
Published: (2025)

Can LLM Infer Risk Information From MCP Server System Logs?
by: Fu, Jiayi, et al.
Published: (2025)

M3S-UPD: Efficient Multi-Stage Self-Supervised Learning for Fine-Grained Encrypted Traffic Classification with Unknown Pattern Discovery
by: Yuan, Yali, et al.
Published: (2025)

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures
by: Kong, Dezhang, et al.
Published: (2025)