Cover Image

UntrustVul: An Automated Approach for Identifying Untrustworthy Alerts in Vulnerability Detection Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tung, Lam Nguyen, Du, Xiaoning, Neelofar, Neelofar, Aleti, Aldeida
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers
by: Tung, Lam Nguyen, et al.
Published: (2024)

PAFOT: A Position-Based Approach for Finding Optimal Tests of Autonomous Vehicles
by: Crespo-Rodriguez, Victor, et al.
Published: (2024)

MORTAR: Multi-turn Metamorphic Testing for LLM-based Dialogue Systems
by: Guo, Guoxiang, et al.
Published: (2024)

The Role of Road Features and Vehicle Dynamics in Cost-Effective Autonomous Vehicles Safety Testing: Insights from Instance Space Analysis
by: Crespo-Rodriguez, Victor, et al.
Published: (2026)

UntrustVul: Improving the Usability of Vulnerability Detection Models by Reducing Untrustworthy Alerts
by: Anonymous, Anonymous
Published: (2025)

Experimental evaluation of architectural software performance design patterns in microservices
by: Meijer, Willem, et al.
Published: (2024)

Requirements-Driven Automated Software Testing: A Systematic Review
by: Wang, Fanyu, et al.
Published: (2025)

ViBR: Automated Bug Replay from Video-based Reports using Vision-Language Models
by: Feng, Sidong, et al.
Published: (2026)

Trustworthy AI Software Engineers
by: Aleti, Aldeida, et al.
Published: (2026)

Enhancing Large Language Models for Text-to-Testcase Generation
by: Alagarsamy, Saranya, et al.
Published: (2024)

VulWeaver: Weaving Broken Semantics for Grounded Vulnerability Detection
by: Cao, Yiheng, et al.
Published: (2026)

Unveiling Practical Shortcomings of Patch Overfitting Detection Techniques
by: Williams, David, et al.
Published: (2026)

A Semantic-based Optimization Approach for Repairing LLMs: Case Study on Code Generation
by: Gu, Jian, et al.
Published: (2025)

VulRTex: A Reasoning-Guided Approach to Identify Vulnerabilities from Rich-Text Issue Report
by: Jiang, Ziyou, et al.
Published: (2025)

From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry
by: Arora, Chetan, et al.
Published: (2025)

Neuron Patching: Semantic-based Neuron-level Language Model Repair for Code Generation
by: Gu, Jian, et al.
Published: (2023)

Empirical and Sustainability Aspects of Software Engineering Research in the Era of Large Language Models: A Reflection
by: Williams, David, et al.
Published: (2025)

VulGuard: An Unified Tool for Evaluating Just-In-Time Vulnerability Prediction Models
by: Nguyen, Duong, et al.
Published: (2025)

VulAgent: Hypothesis-Validation based Multi-Agent Vulnerability Detection
by: Wang, Ziliang, et al.
Published: (2025)

VulStamp: Vulnerability Assessment using Large Language Model
by: Shen, Hao, et al.
Published: (2025)

Test-based Patch Clustering for Automatically-Generated Patches Assessment
by: Martinez, Matias, et al.
Published: (2022)

Vul-R2: A Reasoning LLM for Automated Vulnerability Repair
by: Wen, Xin-Cheng, et al.
Published: (2025)

VulCoCo: A Simple Yet Effective Method for Detecting Vulnerable Code Clones
by: Bui, Tan, et al.
Published: (2025)

Enabling Cost-Effective UI Automation Testing with Retrieval-Based LLMs: A Case Study in WeChat
by: Feng, Sidong, et al.
Published: (2024)

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection
by: Ahmed, Md Basim Uddin, et al.
Published: (2025)

VulKey: Automated Vulnerability Repair Guided by Domain-Specific Repair Patterns
by: Li, Jia, et al.
Published: (2026)

Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG
by: Du, Xueying, et al.
Published: (2024)

VulEval: Towards Repository-Level Evaluation of Software Vulnerability Detection
by: Wen, Xin-Cheng, et al.
Published: (2024)

CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics
by: Li, Yikun, et al.
Published: (2024)

VulZoo: A Comprehensive Vulnerability Intelligence Dataset
by: Ruan, Bonan, et al.
Published: (2024)

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models
by: Liu, Yu, et al.
Published: (2024)

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
by: Wang, Fanyu, et al.
Published: (2025)

StagedVulBERT: Multi-Granular Vulnerability Detection with a Novel Pre-trained Code Model
by: Jiang, Yuan, et al.
Published: (2024)

MulVul: Retrieval-augmented Multi-Agent Code Vulnerability Detection via Cross-Model Prompt Evolution
by: Wu, Zihan, et al.
Published: (2026)

VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications
by: Zhu, Hao, et al.
Published: (2025)

ReposVul: A Repository-Level High-Quality Vulnerability Dataset
by: Wang, Xinchen, et al.
Published: (2024)

MegaVul: A C/C++ Vulnerability Dataset with Comprehensive Code Representation
by: Ni, Chao, et al.
Published: (2024)

ReVul-CoT: Towards Effective Software Vulnerability Assessment with Retrieval-Augmented Generation and Chain-of-Thought Prompting
by: Chen, Zhijie, et al.
Published: (2025)

You Only Train Once: A Flexible Training Framework for Code Vulnerability Detection Driven by Vul-Vector
by: Tian, Bowen, et al.
Published: (2025)

Identifying and Mitigating API Misuse in Large Language Models
by: Zhuo, Terry Yue, et al.
Published: (2025)