Cover Image

The Best Defense is a Good Offense: Countering LLM-Powered Cyberattacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ayzenshteyn, Daniel, Weiss, Roy, Mirsky, Yisroel
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

What Was Your Prompt? A Remote Keylogging Attack on AI Assistants
by: Weiss, Roy, et al.
Published: (2024)

Counter-Samples: A Stateless Strategy to Neutralize Black Box Adversarial Attacks
by: Bokobza, Roey, et al.
Published: (2024)

PEAS: A Strategy for Crafting Transferable Adversarial Examples
by: Avraham, Bar, et al.
Published: (2024)

One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries
by: Zloczower, Itay, et al.
Published: (2026)

Trust Me, I Know This Function: Hijacking LLM Static Analysis using Bias
by: Bernstein, Shir, et al.
Published: (2025)

Hacking Back the AI-Hacker: Prompt Injection as a Defense Against LLM-driven Cyberattacks
by: Pasquini, Dario, et al.
Published: (2024)

Uplifted Attackers, Human Defenders: The Cyber Offense-Defense Balance for Trailing-Edge Organizations
by: Murphy, Benjamin, et al.
Published: (2025)

The Impact of AI on the Cyber Offense-Defense Balance and the Character of Cyber Conflict
by: Lohn, Andrew J.
Published: (2025)

ProxyPrints: From Database Breach to Spoof, A Plug-and-Play Defense for Biometric Systems
by: Hacmon, Yaniv, et al.
Published: (2025)

GAVEL: Towards Rule-Based Safety Through Activation Monitoring
by: Rozenfeld, Shir, et al.
Published: (2026)

Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams
by: Gressel, Gilad, et al.
Published: (2025)

Who Owns This Agent? Tracing AI Agents Back to Their Owners
by: Chocron, Ruben, et al.
Published: (2026)

Agentic AI and the Industrialization of Cyber Offense: Forecast, Consequences, and Defensive Priorities for Enterprises and the Mittelstand
by: Koch, Christopher
Published: (2026)

Efficient Model Extraction via Boundary Sampling
by: Dor, Maor Biton, et al.
Published: (2024)

A Framework for Evaluating Emerging Cyberattack Capabilities of AI
by: Rodriguez, Mikel, et al.
Published: (2025)

Binary and Multiclass Cyberattack Classification on GeNIS Dataset
by: Silva, Miguel, et al.
Published: (2025)

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

Multi-Granular Discretization for Interpretable Generalization in Precise Cyberattack Identification
by: Chung, Wen-Cheng, et al.
Published: (2025)

Simulating Cyberattacks through a Breach Attack Simulation (BAS) Platform empowered by Security Chaos Engineering (SCE)
by: Sánchez-Matas, Arturo, et al.
Published: (2025)

Transpose Attack: Stealing Datasets with Bidirectional Training
by: Amit, Guy, et al.
Published: (2023)

Catastrophic Cyber Capabilities Benchmark (3CB): Robustly Evaluating LLM Agent Cyber Offense Capabilities
by: Anurin, Andrey, et al.
Published: (2024)

How Good LLM-Generated Password Policies Are?
by: Vaidya, Vivek, et al.
Published: (2025)

The Role and Applications of Airport Digital Twin in Cyberattack Protection during the Generative AI Era
by: Weinberg, Abraham Itzhak
Published: (2024)

Exploring Backdoor Attack and Defense for LLM-empowered Recommendations
by: Ning, Liangbo, et al.
Published: (2025)

RAGRank: Using PageRank to Counter Poisoning in CTI LLM Pipelines
by: Jia, Austin, et al.
Published: (2025)

Tackling Cyberattacks through AI-based Reactive Systems: A Holistic Review and Future Vision
by: Molina, Sergio Bernardez, et al.
Published: (2023)

COGNITION: From Evaluation to Defense against Multimodal LLM CAPTCHA Solvers
by: Wang, Junyu, et al.
Published: (2025)

Operationalizing CaMeL: Strengthening LLM Defenses for Enterprise Deployment
by: Tallam, Krti, et al.
Published: (2025)

Taxonomy, Evaluation and Exploitation of IPI-Centric LLM Agent Defense Frameworks
by: Ji, Zimo, et al.
Published: (2025)

UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks
by: Yu, Tianlong, et al.
Published: (2026)

AdaPhish: AI-Powered Adaptive Defense and Education Resource Against Deceptive Emails
by: Meguro, Rei, et al.
Published: (2025)

SHIELD: An Auto-Healing Agentic Defense Framework for LLM Resource Exhaustion Attacks
by: Sivaroopan, Nirhoshan, et al.
Published: (2026)

DRIFT: Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents
by: Li, Hao, et al.
Published: (2025)

Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents
by: Zhang, Hanrong, et al.
Published: (2024)

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts
by: Hasan, Md. Mehedi, et al.
Published: (2025)

CCFC: Core & Core-Full-Core Dual-Track Defense for LLM Jailbreak Protection
by: Hu, Jiaming, et al.
Published: (2025)

A-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory
by: Wei, Qianshan, et al.
Published: (2025)

A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly
by: Yao, Yifan, et al.
Published: (2023)

SoK: The Last Line of Defense: On Backdoor Defense Evaluation
by: Abad, Gorka, et al.
Published: (2025)

The Defense Trilemma: Why Prompt Injection Defense Wrappers Fail?
by: Bhatt, Manish, et al.
Published: (2026)