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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
On Borrowed Time -- Preventing Static Side-Channel Analysis
Robert Dumitru, Thorben Moos, Andrew Wabnitz, Yuval Yarom · 2023-07-18 · via cs.CR updates on arXiv.org

In recent years a new class of side-channel attacks has emerged. Instead of targeting device emissions during dynamic computation, adversaries now frequently exploit the leakage or response behaviour of integrated circuits in a static state. Members of this class include Static Power Side-Channel Analysis (SCA), Laser Logic State Imaging (LLSI) and Impedance Analysis (IA). Despite relying on different physical phenomena, they all enable the extraction of sensitive information from circuits in a static state with high accuracy and low noise -- a trait that poses a significant threat to many established side-channel countermeasures. In this work, we point out the shortcomings of existing solutions and derive a simple yet effective countermeasure. We observe that in order to realise their full potential, static side-channel attacks require the targeted data to remain unchanged for a certain amount of time. For some cryptographic secrets this happens naturally, for others it requires stopping the target circuit's clock. Our proposal, called Borrowed Time, hinders an attacker's ability to leverage such idle conditions, even if full control over the global clock signal is obtained. For that, by design, key-dependent data may only be present in unprotected temporary storage when strictly needed. Borrowed Time then continuously monitors the target circuit and upon detecting an idle state, securely wipes sensitive contents. We demonstrate the need for our countermeasure and its effectiveness by mounting practical static power SCA attacks against cryptographic systems on FPGAs, with and without Borrowed Time. In one case we attack a masked implementation and show that it is only protected with our countermeasure in place. Furthermore we demonstrate that secure on-demand wiping of sensitive data works as intended, affirming the theory that the technique also effectively hinders LLSI and IA.