:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autor principal:	Abdulzada, Farzana
Formato:	Preprint
Publicado:	2025
Materias:	Cryptography and Security
Acceso en línea:	https://arxiv.org/abs/2507.21113
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Ethics Statements in Autonomous Penetration-Testing Agent Research
por: Happe, Andreas, et al.
Publicado: (2025)

PentestAgent: Incorporating LLM Agents to Automated Penetration Testing
por: Shen, Xiangmin, et al.
Publicado: (2024)

HackSynth: LLM Agent and Evaluation Framework for Autonomous Penetration Testing
por: Muzsai, Lajos, et al.
Publicado: (2024)

Automated Penetration Testing with LLM Agents and Classical Planning
por: Wang, Lingzhi, et al.
Publicado: (2025)

Insider Threats Mitigation: Role of Penetration Testing
por: Chauhan, Krutarth
Publicado: (2024)

A Comprehensive Evaluation and Practice of System Penetration Testing
por: Zhang, Chunyi, et al.
Publicado: (2025)

xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models
por: Luong, Phung Duc, et al.
Publicado: (2025)

Red-MIRROR: Agentic LLM-based Autonomous Penetration Testing with Reflective Verification and Knowledge-augmented Interaction
por: Khang, Tran Vy, et al.
Publicado: (2026)

Lessons from Penetration Tests on Large-Scale Agent Systems
por: Eykholt, Kevin, et al.
Publicado: (2026)

ICSSPulse: A Modular LLM-Assisted Platform for Industrial Control System Penetration Testing
por: Takaronis, Michail, et al.
Publicado: (2026)

What Makes a Good LLM Agent for Real-world Penetration Testing?
por: Deng, Gelei, et al.
Publicado: (2026)

AutoPentest: Enhancing Vulnerability Management With Autonomous LLM Agents
por: Henke, Julius
Publicado: (2025)

LLM Agents can Autonomously Exploit One-day Vulnerabilities
por: Fang, Richard, et al.
Publicado: (2024)

Penetration Testing for System Security: Methods and Practical Approaches
por: Zhang, Wei, et al.
Publicado: (2025)

Multi-Agent Penetration Testing AI for the Web
por: David, Isaac, et al.
Publicado: (2025)

RapidPen: Fully Automated IP-to-Shell Penetration Testing with LLM-based Agents
por: Nakatani, Sho
Publicado: (2025)

Evaluation of Reinforcement Learning for Autonomous Penetration Testing using A3C, Q-learning and DQN
por: Becker, Norman, et al.
Publicado: (2024)

AWE: Adaptive Agents for Dynamic Web Penetration Testing
por: Jaswal, Akshat Singh, et al.
Publicado: (2026)

Cochise: A Reference Harness for Autonomous Penetration Testing
por: Happe, Andreas, et al.
Publicado: (2026)

On the Surprising Efficacy of LLMs for Penetration-Testing
por: Happe, Andreas, et al.
Publicado: (2025)

Incorporation of Verifier Functionality in the Software for Operations and Network Attack Results Review and the Autonomous Penetration Testing System
por: Milbrath, Jordan, et al.
Publicado: (2024)

Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks
por: Happe, Andreas, et al.
Publicado: (2025)

Towards Supporting Penetration Testing Education with Large Language Models: an Evaluation and Comparison
por: Nizon-Deladoeuille, Martin, et al.
Publicado: (2025)

Shell or Nothing: Real-World Benchmarks and Memory-Activated Agents for Automated Penetration Testing
por: Mai, Wuyuao, et al.
Publicado: (2025)

PentestGPT: An LLM-empowered Automatic Penetration Testing Tool
por: Deng, Gelei, et al.
Publicado: (2023)

AutoPenBench: Benchmarking Generative Agents for Penetration Testing
por: Gioacchini, Luca, et al.
Publicado: (2024)

Enhancing LLM-based Autonomous Driving Agents to Mitigate Perception Attacks
por: Song, Ruoyu, et al.
Publicado: (2024)

How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency
por: Erdem, Galip Tolga
Publicado: (2026)

Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements
por: Isozaki, Isamu, et al.
Publicado: (2024)

APT-Agent: Automated Penetration Testing using Large Language Models
por: Li, William Guanting, et al.
Publicado: (2026)

Path-wise Vulnerability Mitigation
por: Huang, Zhen, et al.
Publicado: (2024)

Taming OpenClaw: Security Analysis and Mitigation of Autonomous LLM Agent Threats
por: Deng, Xinhao, et al.
Publicado: (2026)

Advanced Penetration Testing for Enhancing 5G Security
por: Smith-Haynes, Shari-Ann
Publicado: (2024)

PatchIsland: Orchestration of LLM Agents for Continuous Vulnerability Repair
por: Kim, Wonyoung, et al.
Publicado: (2026)

Evaluating the Vulnerability Landscape of LLM-Generated Smart Contracts
por: Do, Hoang Long, et al.
Publicado: (2026)

NASimJax: GPU-Accelerated Policy Learning Framework for Penetration Testing
por: Simon, Raphael, et al.
Publicado: (2026)

Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees
por: Nakano, Katsuaki, et al.
Publicado: (2025)

The Trust Paradox in LLM-Based Multi-Agent Systems: When Collaboration Becomes a Security Vulnerability
por: Xu, Zijie, et al.
Publicado: (2025)

LLM-BSCVM: An LLM-Based Blockchain Smart Contract Vulnerability Management Framework
por: Jin, Yanli, et al.
Publicado: (2025)

Atomicity for Agents: Exposing, Exploiting, and Mitigating TOCTOU Vulnerabilities in Browser-Use Agents
por: Jiang, Linxi, et al.
Publicado: (2026)