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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
Chameleon Cache: Approximating Fully Associative Caches w...
Thomas Unterluggauer, Austin Harris, Scott Constable, Fangfei Li · 2022-09-29 · via cs.CR updates on arXiv.org

Randomized, skewed caches (RSCs) such as CEASER-S have recently received much attention to defend against contention-based cache side channels. By randomizing and regularly changing the mapping(s) of addresses to cache sets, these techniques are designed to obfuscate the leakage of memory access patterns. However, new attack techniques, e.g., Prime+Prune+Probe, soon demonstrated the limits of RSCs as they allow attackers to more quickly learn which addresses contend in the cache and use this information to circumvent the randomization. To yet maintain side-channel resilience, RSCs must change the random mapping(s) more frequently with adverse effects on performance and implementation complexity. This work aims to make randomization-based approaches more robust to allow for reduced re-keying rates and presents Chameleon Cache. Chameleon Cache extends RSCs with a victim cache (VC) to decouple contention in the RSC from evictions observed by the user. The VC allows Chameleon Cache to make additional use of the multiple mappings RSCs provide to translate addresses to cache set indices: when a cache line is evicted from the RSC to the VC under one of its mappings, the VC automatically reinserts this evicted line back into the RSC by using a different mapping. As a result, the effects of previous RSC set contention are hidden and Chameleon Cache exhibits side-channel resistance and eviction patterns similar to fully associative caches with random replacement. We show that Chameleon Cache has performance overheads of < 1% and stress that VCs are more generically helpful to increase side-channel resistance and re-keying intervals of randomized caches.