Cover Image

Automated Vulnerability Validation and Verification: A Large Language Model Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lotfi, Alireza, Katsis, Charalampos, Bertino, Elisa
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ZT-SDN: An ML-powered Zero-Trust Architecture for Software-Defined Networks
by: Katsis, Charalampos, et al.
Published: (2024)

Zero-Trust Strategies for O-RAN Cellular Networks: Principles, Challenges and Research Directions
by: Katsis, Charalampos, et al.
Published: (2025)

Graphene: Infrastructure Security Posture Analysis with AI-generated Attack Graphs
by: Jin, Xin, et al.
Published: (2023)

LFreeDA: Label-Free Drift Adaptation for Windows Malware Detection
by: Li, Adrian Shuai, et al.
Published: (2025)

LLMalMorph: On The Feasibility of Generating Variant Malware using Large-Language-Models
by: Akil, Md Ajwad, et al.
Published: (2025)

vEcho: A Paradigm Shift from Vulnerability Verification to Proactive Discovery with Large Language Models
by: Jiang, Mingcheng, et al.
Published: (2026)

Breaking 5G on The Lower Layer
by: Shanto, Subangkar Karmaker, et al.
Published: (2026)

Gotta Detect 'Em All: Fake Base Station and Multi-Step Attack Detection in Cellular Networks
by: Mubasshir, Kazi Samin, et al.
Published: (2024)

Information Theoretic Adversarial Training of Large Language Models
by: Zhang, Yiwei, et al.
Published: (2026)

Can Drift-Adaptive Malware Detectors Be Made Robust? Attacks and Defenses Under White-Box and Black-Box Threats
by: Li, Adrian Shuai, et al.
Published: (2026)

CellularLint: A Systematic Approach to Identify Inconsistent Behavior in Cellular Network Specifications
by: Rahman, Mirza Masfiqur, et al.
Published: (2024)

Revisiting Concept Drift in Windows Malware Detection: Adaptation to Real Drifted Malware with Minimal Samples
by: Li, Adrian Shuai, et al.
Published: (2024)

Weaponizing Language Models for Cybersecurity Offensive Operations: Automating Vulnerability Assessment Report Validation; A Review Paper
by: Almuhaidib, Abdulrahman S, et al.
Published: (2025)

An Investigation of Large Language Models and Their Vulnerabilities in Spam Detection
by: Tang, Qiyao, et al.
Published: (2025)

SoK: Leveraging Transformers for Malware Analysis
by: Kunwar, Pradip, et al.
Published: (2024)

CryptoScope: Utilizing Large Language Models for Automated Cryptographic Logic Vulnerability Detection
by: Li, Zhihao, et al.
Published: (2025)

LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models
by: Fakih, Mohamad, et al.
Published: (2025)

How Feasible is Augmenting Fake Nodes with Learnable Features as a Counter-strategy against Link Stealing Attacks?
by: Mostafiz, Mir Imtiaz, et al.
Published: (2025)

Evaluating and Enhancing the Vulnerability Reasoning Capabilities of Large Language Models
by: Lu, Li, et al.
Published: (2026)

Evaluating Large Language Models' Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects
by: Heiding, Fred, et al.
Published: (2024)

LAAF: Logic-layer Automated Attack Framework A Systematic Red-Teaming Methodology for LPCI Vulnerabilities in Agentic Large Language Model Systems
by: Atta, Hammad, et al.
Published: (2026)

An Automated Attack Investigation Approach Leveraging Threat-Knowledge-Augmented Large Language Models
by: Dai, Rujie, et al.
Published: (2025)

Toward Automated Security Risk Detection in Large Software Using Call Graph Analysis
by: Pecka, Nicholas, et al.
Published: (2025)

Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security
by: Zhang, Yiwei, et al.
Published: (2025)

Semi-Automated Threat Modeling of Cloud-Based Systems Through Extracting Software Architecture from Configuration and Network Flow
by: Pecka, Nicholas, et al.
Published: (2026)

APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching
by: Nong, Yu, et al.
Published: (2024)

Validating Threat Modeling Results with the Help of Vulnerable Test Applications
by: Adamov, Oleksandr, et al.
Published: (2026)

Generative Large Language Model usage in Smart Contract Vulnerability Detection
by: Ince, Peter, et al.
Published: (2025)

SoK: Understanding Vulnerabilities in the Large Language Model Supply Chain
by: Wang, Shenao, et al.
Published: (2025)

Towards Automated Pentesting with Large Language Models
by: Bessa, Ricardo, et al.
Published: (2026)

A Survey of Agentic AI and Cybersecurity: Challenges, Opportunities and Use-case Prototypes
by: Lazer, Sahaya Jestus, et al.
Published: (2026)

Soley: Identification and Automated Detection of Logic Vulnerabilities in Ethereum Smart Contracts Using Large Language Models
by: Soud, Majd, et al.
Published: (2024)

Leveraging Large Language Models and Machine Learning for Smart Contract Vulnerability Detection
by: Hossain, S M Mostaq, et al.
Published: (2025)

Chain-of-Thought Prompting of Large Language Models for Discovering and Fixing Software Vulnerabilities
by: Nong, Yu, et al.
Published: (2024)

Detect Llama -- Finding Vulnerabilities in Smart Contracts using Large Language Models
by: Ince, Peter, et al.
Published: (2024)

VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification
by: Bonhomme, Cédric, et al.
Published: (2025)

IRCopilot: Automated Incident Response with Large Language Models
by: Lin, Xihuan, et al.
Published: (2025)

Agentic Discovery and Validation of Android App Vulnerabilities
by: Wang, Ziyue, et al.
Published: (2025)

Quantum-Resistant Networks: A Review of Primitives, Protocols and Best Practices
by: Bertino, Elisa, et al.
Published: (2026)

EvilScreen Attack: Smart TV Hijacking via Multi-channel Remote Control Mimicry
by: Zhang, Yiwei, et al.
Published: (2022)