惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

腾讯CDC
Microsoft Azure Blog
Microsoft Azure Blog
B
Blog
S
SegmentFault 最新的问题
WordPress大学
WordPress大学
P
Proofpoint News Feed
Hugging Face - Blog
Hugging Face - Blog
MyScale Blog
MyScale Blog
A
About on SuperTechFans
雷峰网
雷峰网
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
T
The Blog of Author Tim Ferriss
MongoDB | Blog
MongoDB | Blog
博客园 - 【当耐特】
The Cloudflare Blog
F
Fortinet All Blogs
小众软件
小众软件
博客园 - 三生石上(FineUI控件)
宝玉的分享
宝玉的分享
罗磊的独立博客
量子位
有赞技术团队
有赞技术团队
V
V2EX
Engineering at Meta
Engineering at Meta

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
Store-to-Leak Forwarding: Leaking Data on Meltdown-resist...
Michael Schwarz, Claudio Canella, Lukas Giner, Daniel Gruss · 2019-05-15 · via cs.CR updates on arXiv.org

Meltdown and Spectre exploit microarchitectural changes the CPU makes during transient out-of-order execution. Using side-channel techniques, these attacks enable leaking arbitrary data from memory. As state-of-the-art software mitigations for Meltdown may incur significant performance overheads, they are only seen as a temporary solution. Thus, software mitigations are disabled on more recent processors, which are not susceptible to Meltdown anymore. In this paper, we show that Meltdown-like attacks are still possible on recent CPUs which are not vulnerable to the original Meltdown attack. We show that the store buffer - a microarchitectural optimization to reduce the latency for data stores - in combination with the TLB enables powerful attacks. We present several ASLRrelated attacks, including a KASLR break from unprivileged applications, and breaking ASLR from JavaScript. We can also mount side-channel attacks, breaking the atomicity of TSX, and monitoring control flow of the kernel. Furthermore, when combined with a simple Spectre gadget, we can leak arbitrary data from memory. Our paper shows that Meltdown-like attacks are still possible, and software fixes are still necessary to ensure proper isolation between the kernel and user space. This updated extended version of the original paper includes new results and explanations on the root cause of the vulnerability and shows how it is different to MDS attacks like Fallout.