Automated TEE Adaptation with LLMs: Identifying, Transforming, and Porting Sensitive Functions in Programs
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Ruidong, Yang, Zhou, Ma, Chengyan, Liu, Ye, Niu, Yuqing, Ma, Siqi, Gao, Debin, Lo, David |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DITING: A Static Analyzer for Identifying Bad Partitioning Issues in TEE Applications
by: Ma, Chengyan, et al.
Published: (2025)
by: Ma, Chengyan, et al.
Published: (2025)
Automated Repair of TEE Partitioning Issues via DSL-Guided and LLM-Assisted Patching
by: Ma, Chengyan, et al.
Published: (2026)
by: Ma, Chengyan, et al.
Published: (2026)
Finding Missing Input Validation in TEEs via LLM-Assisted Symbolic Execution
by: Ma, Chengyan, et al.
Published: (2026)
by: Ma, Chengyan, et al.
Published: (2026)
What You Trust Is Insecure: Demystifying How Developers (Mis)Use Trusted Execution Environments in Practice
by: Niu, Yuqing, et al.
Published: (2025)
by: Niu, Yuqing, et al.
Published: (2025)
Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learning
by: Liu, Ye, et al.
Published: (2025)
by: Liu, Ye, et al.
Published: (2025)
Characterizing Trust Boundary Vulnerabilities in TEE Containers: An Empirical Study
by: Liu, Weijie, et al.
Published: (2025)
by: Liu, Weijie, et al.
Published: (2025)
Decoding Secret Memorization in Code LLMs Through Token-Level Characterization
by: Nie, Yuqing, et al.
Published: (2024)
by: Nie, Yuqing, et al.
Published: (2024)
PrediQL: Automated Testing of GraphQL APIs with LLMs
by: Liu, Shaolun, et al.
Published: (2025)
by: Liu, Shaolun, et al.
Published: (2025)
Automated Repair of OpenID Connect Programs (Extended Version)
by: Rahat, Tamjid Al, et al.
Published: (2025)
by: Rahat, Tamjid Al, et al.
Published: (2025)
AUTOVR: Automated UI Exploration for Detecting Sensitive Data Flow Exposures in Virtual Reality Apps
by: Kim, John Y., et al.
Published: (2025)
by: Kim, John Y., et al.
Published: (2025)
Finding Memory Leaks in C/C++ Programs via Neuro-Symbolic Augmented Static Analysis
by: Huang, Huihui, et al.
Published: (2026)
by: Huang, Huihui, et al.
Published: (2026)
AutoFirm: Automatically Identifying Reused Libraries inside IoT Firmware at Large-Scale
by: Chen, YongLe, et al.
Published: (2024)
by: Chen, YongLe, et al.
Published: (2024)
An Investigation of Patch Porting Practices of the Linux Kernel Ecosystem
by: Li, Xingyu, et al.
Published: (2024)
by: Li, Xingyu, et al.
Published: (2024)
From LLMs to Agents: A Comparative Evaluation of LLMs and LLM-based Agents in Security Patch Detection
by: Han, Junxiao, et al.
Published: (2025)
by: Han, Junxiao, et al.
Published: (2025)
{A New Hope}: Contextual Privacy Policies for Mobile Applications and An Approach Toward Automated Generation
by: Pan, Shidong, et al.
Published: (2024)
by: Pan, Shidong, et al.
Published: (2024)
Rethinking and Exploring String-Based Malware Family Classification in the Era of LLMs and RAG
by: Chen, Yufan, et al.
Published: (2025)
by: Chen, Yufan, et al.
Published: (2025)
Automated Attack Synthesis for Constant Product Market Makers
by: Han, Sujin, et al.
Published: (2024)
by: Han, Sujin, et al.
Published: (2024)
SecureInfer: Heterogeneous TEE-GPU Architecture for Privacy-Critical Tensors for Large Language Model Deployment
by: Nayan, Tushar, et al.
Published: (2025)
by: Nayan, Tushar, et al.
Published: (2025)
PATCHEVAL: A New Benchmark for Evaluating LLMs on Patching Real-World Vulnerabilities
by: Wei, Zichao, et al.
Published: (2025)
by: Wei, Zichao, et al.
Published: (2025)
CNT: Safety-oriented Function Reuse across LLMs via Cross-Model Neuron Transfer
by: Zhao, Yue, et al.
Published: (2026)
by: Zhao, Yue, et al.
Published: (2026)
KEENHash: Hashing Programs into Function-Aware Embeddings for Large-Scale Binary Code Similarity Analysis
by: Liu, Zhijie, et al.
Published: (2025)
by: Liu, Zhijie, et al.
Published: (2025)
VulEval: Towards Repository-Level Evaluation of Software Vulnerability Detection
by: Wen, Xin-Cheng, et al.
Published: (2024)
by: Wen, Xin-Cheng, et al.
Published: (2024)
Guardians of the Ledger: Protecting Decentralized Exchanges from State Derailment Defects
by: Li, Zongwei, et al.
Published: (2024)
by: Li, Zongwei, et al.
Published: (2024)
Fixing 7,400 Bugs for 1$: Cheap Crash-Site Program Repair
by: Zheng, Han, et al.
Published: (2025)
by: Zheng, Han, et al.
Published: (2025)
Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap
by: Huang, Feiyang, et al.
Published: (2026)
by: Huang, Feiyang, et al.
Published: (2026)
Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models
by: Yang, Zhou, et al.
Published: (2023)
by: Yang, Zhou, et al.
Published: (2023)
CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics
by: Li, Yikun, et al.
Published: (2024)
by: Li, Yikun, et al.
Published: (2024)
Out of Distribution, Out of Luck: How Well Can LLMs Trained on Vulnerability Datasets Detect Top 25 CWE Weaknesses?
by: Li, Yikun, et al.
Published: (2025)
by: Li, Yikun, et al.
Published: (2025)
Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code Datasets
by: Xiao, Yuan, et al.
Published: (2026)
by: Xiao, Yuan, et al.
Published: (2026)
Beyond Function-Level Analysis: Context-Aware Reasoning for Inter-Procedural Vulnerability Detection
by: Li, Yikun, et al.
Published: (2026)
by: Li, Yikun, et al.
Published: (2026)
ACFIX: Guiding LLMs with Mined Common RBAC Practices for Context-Aware Repair of Access Control Vulnerabilities in Smart Contracts
by: Zhang, Lyuye, et al.
Published: (2024)
by: Zhang, Lyuye, et al.
Published: (2024)
OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine
by: Ma, Jie, et al.
Published: (2025)
by: Ma, Jie, et al.
Published: (2025)
Identifying Adversary Tactics and Techniques in Malware Binaries with an LLM Agent
by: Xuan, Zhou, et al.
Published: (2026)
by: Xuan, Zhou, et al.
Published: (2026)
Backdoors in Code Summarizers: How Bad Is It?
by: Wang, Chenyu, et al.
Published: (2025)
by: Wang, Chenyu, et al.
Published: (2025)
Large Language Models for Code Analysis: Do LLMs Really Do Their Job?
by: Fang, Chongzhou, et al.
Published: (2023)
by: Fang, Chongzhou, et al.
Published: (2023)
Provenance of Adaptation in Scientific and Business Workflows -- Literature Review
by: Stage, Ludwig, et al.
Published: (2025)
by: Stage, Ludwig, et al.
Published: (2025)
AdProv: A Method for Provenance of Process Adaptations
by: Stage, Ludwig, et al.
Published: (2025)
by: Stage, Ludwig, et al.
Published: (2025)
Automated Generation of Cybersecurity Exercise Scenarios
by: Skandylas, Charilaos, et al.
Published: (2026)
by: Skandylas, Charilaos, et al.
Published: (2026)
Automated Penetration Testing: Formalization and Realization
by: Skandylas, Charilaos, et al.
Published: (2024)
by: Skandylas, Charilaos, et al.
Published: (2024)
NESSiE: The Necessary Safety Benchmark -- Identifying Errors that should not Exist
by: Bertram, Johannes, et al.
Published: (2026)
by: Bertram, Johannes, et al.
Published: (2026)
Similar Items
-
DITING: A Static Analyzer for Identifying Bad Partitioning Issues in TEE Applications
by: Ma, Chengyan, et al.
Published: (2025) -
Automated Repair of TEE Partitioning Issues via DSL-Guided and LLM-Assisted Patching
by: Ma, Chengyan, et al.
Published: (2026) -
Finding Missing Input Validation in TEEs via LLM-Assisted Symbolic Execution
by: Ma, Chengyan, et al.
Published: (2026) -
What You Trust Is Insecure: Demystifying How Developers (Mis)Use Trusted Execution Environments in Practice
by: Niu, Yuqing, et al.
Published: (2025) -
Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learning
by: Liu, Ye, et al.
Published: (2025)