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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
USBCaptchaIn: Preventing (Un)Conventional Attacks from Pr...
Federico Griscioli, Maurizio Pizzonia · 2018-10-11 · via cs.CR updates on arXiv.org

Industrial Control Systems (ICS) are sensible targets for high profile attackers and advanced persistent threats, which are known to exploit USB thumb drives as an effective spreading vector. In ICSes, thumb drives are widely used to transfer files among disconnected systems and represent a serious security risks, since, they may be promiscuously used in both critical and regular systems. The threats come both from malware hidden in files stored in the thumb drives and from BadUSB attacks [16]. BadUSB leverages the modification of firmware of USB devices in order to mimic the behaviour of a keyboard and send malicious commands to the host. We present a solution that allows a promiscuous use of USB thumbs drives while protecting critical machines from malware, that spread by regular file infection or by firmware infection. The main component of the architecture we propose is an hardware, called USBCaptchaIn, intended to be in the middle between a critical machine and all USB devices. We do not require users to change the way they use thumb drives. To avoid human-errors, we do not require users to take any decision. The proposed approach is highly compatible with already deployed products of a ICS environment and proactively blocks malware before they reach their targets. We describe our solution, provide a thorough analysis of the security of our approach in the ICS context, and report the informal feedback of some experts regarding our first prototypes.