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

云风的 BLOG
云风的 BLOG
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
博客园 - 叶小钗
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
V2EX
酷 壳 – CoolShell
酷 壳 – CoolShell
月光博客
月光博客
人人都是产品经理
人人都是产品经理
宝玉的分享
宝玉的分享
博客园 - 司徒正美
WordPress大学
WordPress大学
Microsoft Azure Blog
Microsoft Azure Blog
罗磊的独立博客
Vercel News
Vercel News
T
The Blog of Author Tim Ferriss
T
Tailwind CSS Blog
A
About on SuperTechFans
Apple Machine Learning Research
Apple Machine Learning Research
L
LangChain Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
V
Visual Studio Blog
S
SegmentFault 最新的问题
Google DeepMind News
Google DeepMind News
博客园 - 聂微东

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
Nethammer: Inducing Rowhammer Faults through Network Requ...
Moritz Lipp, Misiker Tadesse Aga, Michael Schwarz, Daniel Gruss, · 2018-05-14 · via cs.CR updates on arXiv.org

A fundamental assumption in software security is that memory contents do not change unless there is a legitimate deliberate modification. Classical fault attacks show that this assumption does not hold if the attacker has physical access. Rowhammer attacks showed that local code execution is already sufficient to break this assumption. Rowhammer exploits parasitic effects in DRAM to modify the content of a memory cell without accessing it. Instead, other memory locations are accessed at a high frequency. All Rowhammer attacks so far were local attacks, running either in a scripted language or native code. In this paper, we present Nethammer. Nethammer is the first truly remote Rowhammer attack, without a single attacker-controlled line of code on the targeted system. Systems that use uncached memory or flush instructions while handling network requests, e.g., for interaction with the network device, can be attacked using Nethammer. Other systems can still be attacked if they are protected with quality-of-service techniques like Intel CAT. We demonstrate that the frequency of the cache misses is in all three cases high enough to induce bit flips. We evaluated different bit flip scenarios. Depending on the location, the bit flip compromises either the security and integrity of the system and the data of its users, or it can leave persistent damage on the system, i.e., persistent denial of service. We investigated Nethammer on personal computers, servers, and mobile phones. Nethammer is a security landslide, making the formerly local attack a remote attack.