{"total":43,"rows":[{"id":"2501.04227","title":"Agent Laboratory: Using LLM Agents as Research Assistants","created":"2025-01-08","cited_by_count":425,"area":"agents"},{"id":"2411.05185","title":"PentestAgent: Incorporating LLM Agents to Automated Penetration Testing","created":"2024-11-07","cited_by_count":47,"area":"agents"},{"id":"2412.01778","title":"HackSynth: LLM Agent and Evaluation Framework for Autonomous Penetration Testing","created":"2024-12-02","cited_by_count":37,"area":"agents"},{"id":"2501.13411","title":"VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework","created":"2025-01-23","cited_by_count":31,"area":"agents"},{"id":"2410.03225","title":"AutoPenBench: Benchmarking Generative Agents for Penetration Testing","created":"2024-10-04","cited_by_count":21,"area":"agents"},{"id":"2408.08902","title":"Audit-LLM: Multi-Agent Collaboration for Log-based Insider Threat Detection","created":"2024-08-12","cited_by_count":18,"area":"agents"},{"id":"2503.15552","title":"Personalized Attacks of Social Engineering in Multi-turn Conversations: LLM Agents for Simulation and Detection","created":"2025-03-18","cited_by_count":13,"area":"agents"},{"id":"2502.16730","title":"RapidPen: Fully Automated IP-to-Shell Penetration Testing with LLM-based Agents","created":"2025-02-23","cited_by_count":11,"area":"agents"},{"id":"2505.10321","title":"AutoPentest: Enhancing Vulnerability Management With Autonomous LLM Agents","created":"2025-05-15","cited_by_count":9,"area":"agents"},{"id":"2505.18384","title":"Dynamic Risk Assessments for Offensive Cybersecurity Agents","created":"2025-05-23","cited_by_count":8,"area":"agents"},{"id":"2511.02780","title":"PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts","created":"2025-11-04","cited_by_count":8,"area":"agents"},{"id":"2505.06913","title":"RedTeamLLM: an Agentic AI framework for offensive security","created":"2025-05-11","cited_by_count":7,"area":"agents"},{"id":"2510.05605","title":"AutoPentester: An LLM Agent-based Framework for Automated Pentesting","created":"2025-10-07","cited_by_count":6,"area":"agents"},{"id":"2502.18528","title":"ARACNE: An LLM-Based Autonomous Shell Pentesting Agent","created":"2025-02-24","cited_by_count":5,"area":"agents"},{"id":"2512.11143","title":"Automated Penetration Testing with LLM Agents and Classical Planning","created":"2025-12-11","cited_by_count":5,"area":"agents"},{"id":"2511.15998","title":"Hiding in the AI Traffic: Abusing MCP for LLM-Powered Agentic Red Teaming","created":"2025-11-20","cited_by_count":4,"area":"agents"},{"id":"2509.13021","title":"xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models","created":"2025-09-16","cited_by_count":3,"area":"agents"},{"id":"2503.15546","title":"Enforcing Cybersecurity Constraints for LLM-driven Robot Agents for Online Transactions","created":"2025-03-17","cited_by_count":2,"area":"agents"},{"id":"2605.24949","title":"APT-Agent: Automated Penetration Testing using Large Language Models","created":"2026-05-24","cited_by_count":2,"area":"agents"},{"id":"2606.03811","title":"AI Agents Enable Adaptive Computer Worms","created":"2026-06-02","cited_by_count":2,"area":"agents"},{"id":"2502.15506","title":"Construction and Evaluation of LLM-based agents for Semi-Autonomous penetration testing","created":"2025-02-21","cited_by_count":1,"area":"agents"},{"id":"2507.21113","title":"Vulnerability Mitigation System (VMS): LLM Agent and Evaluation Framework for Autonomous Penetration Testing","created":"2025-07-14","cited_by_count":1,"area":"agents"},{"id":"2510.17521","title":"Cybersecurity AI: Evaluating Agentic Cybersecurity in Attack/Defense CTFs","created":"2025-10-20","cited_by_count":1,"area":"agents"},{"id":"2603.00960","title":"AWE: Adaptive Agents for Dynamic Web Penetration Testing","created":"2026-03-01","cited_by_count":1,"area":"agents"},{"id":"2604.05440","title":"LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations","created":"2026-04-07","cited_by_count":1,"area":"agents"},{"id":"2604.27143","title":"Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents","created":"2026-04-29","cited_by_count":1,"area":"agents"},{"id":"2605.06486","title":"Autonomous Adversary: Red-Teaming in the age of LLM","created":"2026-05-07","cited_by_count":1,"area":"agents"},{"id":"2605.07830","title":"CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios","created":"2026-05-08","cited_by_count":1,"area":"agents"},{"id":"2608.03009","title":"Tiny Enough to Break In: Agentic Remote Access Trojans Powered by Small Language Models","created":"2026-08-04","cited_by_count":1,"area":"agents"},{"id":"2608.05199","title":"Post-Hoc Trajectory-Risk Certification for Modular LLM-Based Security Agents","created":"2026-08-04","cited_by_count":1,"area":"agents"},{"id":"2608.20563","title":"Beyond End-to-End Success: Diagnosing Failures in Long-Horizon Security LLM Agents","created":"2026-08-20","cited_by_count":1,"area":"agents"},{"id":"2506.08693","title":"Recognition Without Mitigation: Ethical Frameworks in Autonomous Offensive-LLM Agent Research","created":"2025-06-10","cited_by_count":0,"area":"agents"},{"id":"2603.24221","title":"Environment-Grounded Multi-Agent Workflow for Autonomous Penetration Testing","created":"2026-03-25","cited_by_count":0,"area":"agents"},{"id":"2605.00741","title":"Self-Adaptive Multi-Agent LLM-Based Security Pattern Selection for IoT Systems","created":"2026-05-01","cited_by_count":0,"area":"agents"},{"id":"2605.21694","title":"PocketAgents: A Manifest-Driven Library of Autonomous Defense Agents","created":"2026-05-20","cited_by_count":0,"area":"agents"},{"id":"2606.24496","title":"Red-Teaming the Agentic Red-Team","created":"2026-06-23","cited_by_count":0,"area":"agents"},{"id":"2607.09653","title":"VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents","created":"2026-07-10","cited_by_count":0,"area":"agents"},{"id":"2608.21423","title":"Agentic Security: A Systematization of Tools, Failure Modes, and Design Laws for LLM-Driven Penetration Testing","created":"2026-08-16","cited_by_count":0,"area":"agents"},{"id":"2609.01185","title":"Reveree: Diagnosing LLM Reverse-Engineering Agents","created":"2026-09-01","cited_by_count":0,"area":"agents"},{"id":"2609.02647","title":"PrimSynth: An Agentic Approach to Discover, Validate, and Synthesize Exploit Primitives for Linux Kernel Vulnerabilities","created":"2026-09-02","cited_by_count":0,"area":"agents"},{"id":"2609.11852","title":"BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense","created":"2026-09-10","cited_by_count":0,"area":"agents"},{"id":"2609.16694","title":"Toward Secure AI-Powered Penetration Testing Agents: Security Threats, Guardrails, and Architectural Perspectives","created":"2026-09-15","cited_by_count":0,"area":"agents"},{"id":"2609.28572","title":"Where Cyber Agents Struggle: Bottleneck Analysis of Multi-Stage LLM Agents","created":"2026-09-23","cited_by_count":0,"area":"agents"}],"next_cursor":null}