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

N
Netflix TechBlog - Medium
I
InfoQ
Engineering at Meta
Engineering at Meta
Jina AI
Jina AI
Recent Announcements
Recent Announcements
T
The Blog of Author Tim Ferriss
P
Proofpoint News Feed
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
D
Docker
Microsoft Security Blog
Microsoft Security Blog
宝玉的分享
宝玉的分享
Last Week in AI
Last Week in AI
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
GbyAI
GbyAI
博客园 - Franky
博客园 - 聂微东
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 叶小钗
酷 壳 – CoolShell
酷 壳 – CoolShell
B
Blog RSS Feed
WordPress大学
WordPress大学
MyScale Blog
MyScale Blog
月光博客
月光博客
罗磊的独立博客

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
Sprobes: Enforcing Kernel Code Integrity on the TrustZone...
Xinyang Ge, Hayawardh Vijayakumar, Trent Jaeger · 2014-10-29 · via cs.CR updates on arXiv.org

Many smartphones now deploy conventional operating systems, so the rootkit attacks so prevalent on desktop and server systems are now a threat to smartphones. While researchers have advocated using virtualization to detect and prevent attacks on operating systems (e.g., VM introspection and trusted virtual domains), virtualization is not practical on smartphone systems due to the lack of virtualization support and/or the expense of virtualization. Current smartphone processors do have hardware support for running a protected environment, such as the ARM TrustZone extensions, but such hardware does not control the operating system operations sufficiently to enable VM introspection. In particular, a conventional operating system running with TrustZone still retains full control of memory management, which a rootkit can use to prevent traps on sensitive instructions or memory accesses necessary for effective introspection. In this paper, we present SPROBES, a novel primitive that enables introspection of operating systems running on ARM TrustZone hardware. Using SPROBES, an introspection mechanism protected by TrustZone can instrument individual operating system instructions of its choice, receiving an unforgeable trap whenever any SPROBE is executed. The key challenge in designing SPROBES is preventing the rootkit from removing them, but we identify a set of five invariants whose enforcement is sufficient to restrict rootkits to execute only approved, SPROBE-injected kernel code. We implemented a proof-of-concept version of SPROBES for the ARM Fast Models emulator, demonstrating that in Linux kernel 2.6.38, only 12 SPROBES are sufficient to enforce all five of these invariants. With SPROBES we show that it is possible to leverage the limited TrustZone extensions to limit conventional kernel execution to approved code comprehensively.