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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
The Reverse File System: Towards open cost-effective secu...
Gorka Guardiola Múzquiz, Juan González-Gómez, Enrique Soriano-Sa · 2025-09-23 · via cs.CR updates on arXiv.org

Write Once Read Many (WORM) properties for storage devices are desirable to ensure data immutability for applications such as secure logging, regulatory compliance, archival storage, and other types of backup systems. WORM devices guarantee that data, once written, cannot be altered or deleted. However, implementing secure and compatible WORM storage remains a challenge. Traditional solutions often rely on specialized hardware, which is either costly, closed, or inaccessible to the general public. Distributed approaches, while promising, introduce additional risks such as denial-of-service vulnerabilities and operational complexity. We introduce Socarrat, a novel, cost-effective, and local WORM storage solution that leverages a simple external USB device (specifically, a single-board computer running Linux with USB On-The-Go support). The resulting device can be connected via USB, appearing as an ordinary external disk formatted with an ext4 or exFAT file system, without requiring any specialized software or drivers. By isolating the WORM enforcement mechanism in a dedicated USB hardware module, Socarrat significantly reduces the attack surface and ensures that even privileged attackers cannot modify or erase stored data. In addition to the WORM capacity, the system is designed to be tamper-evident, becoming resilient against advanced attacks. This work describes a novel approach, the Reverse File System, based on inferring the file system operations occurring at higher layers in the host computer where Socarrat is mounted. The paper also describes the current Socarrat prototype, implemented in Go and available as free/libre software. Finally, it provides a complete evaluation of the logging performance on different single-board computers.