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cs.CR updates on arXiv.org

Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
HoneyWin: High-Interaction Windows Honeypot in Enterprise...
Yan Lin Aung, Yee Loon Khoo, Davis Yang Zheng, Bryan Swee Duo, S · 2025-05-01 · via cs.CR updates on arXiv.org

Windows operating systems (OS) are ubiquitous in enterprise Information Technology (IT) and operational technology (OT) environments. Due to their widespread adoption and known vulnerabilities, they are often the primary targets of malware and ransomware attacks. With 93% of the ransomware targeting Windows-based systems, there is an urgent need for advanced defensive mechanisms to detect, analyze, and mitigate threats effectively. In this paper, we propose HoneyWin a high-interaction Windows honeypot that mimics an enterprise IT environment. The HoneyWin consists of three Windows 11 endpoints and an enterprise-grade gateway provisioned with comprehensive network traffic capturing, host-based logging, deceptive tokens, endpoint security and real-time alerts capabilities. The HoneyWin has been deployed live in the wild for 34 days and receives more than 5.79 million unsolicited connections, 1.24 million login attempts, 5 and 354 successful logins via remote desktop protocol (RDP) and secure shell (SSH) respectively. The adversary interacted with the deceptive token in one of the RDP sessions and exploited the public-facing endpoint to initiate the Simple Mail Transfer Protocol (SMTP) brute-force bot attack via SSH sessions. The adversary successfully harvested 1,250 SMTP credentials after attempting 151,179 credentials during the attack.