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

I
InfoQ
博客园_首页
美团技术团队
M
MIT News - Artificial intelligence
人人都是产品经理
人人都是产品经理
Blog — PlanetScale
Blog — PlanetScale
H
Help Net Security
J
Java Code Geeks
T
Tailwind CSS Blog
Jina AI
Jina AI
量子位
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
G
Google Developers Blog
爱范儿
爱范儿
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
宝玉的分享
宝玉的分享
小众软件
小众软件
MongoDB | Blog
MongoDB | Blog
博客园 - 三生石上(FineUI控件)
L
LangChain Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
V
Visual Studio Blog
博客园 - Franky
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知

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
NanoZone: Scalable, Efficient, and Secure Memory Protecti...
Shiqi Liu, Yongpeng Gao, Mingyang Zhang, Jie Wang · 2025-06-08 · via cs.CR updates on arXiv.org

Arm Confidential Computing Architecture (CCA) currently isolates at the granularity of an entire Confidential Virtual Machine (CVM), leaving intra-VM bugs such as Heartbleed unmitigated. The state-of-the-art narrows this to the process level, yet still cannot stop attacks that pivot within the same process, and prior intra-enclave schemes are either too slow or incompatible with CVM-style isolation. We extend CCA with a three-tier zone model that spawns an unlimited number of lightweight isolation domains inside a single process, while shielding them from kernel-space adversaries. To block domain-switch abuse, we also add a fast user-level Code-Pointer Integrity (CPI) mechanism. We developed two prototypes: a functional version on Arm's official simulator to validate resistance against intra-process and kernel-space adversaries, and a performance variant on Arm development boards evaluated for session-key isolation within server applications, in-memory key-value protection, and non-volatile-memory data isolation. NanoZone incurs roughly a 20% performance overhead while retaining 95% throughput compared to the system without fine-grained isolation.