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

博客园 - 司徒正美
Jina AI
Jina AI
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 三生石上(FineUI控件)
宝玉的分享
宝玉的分享
MyScale Blog
MyScale Blog
I
InfoQ
爱范儿
爱范儿
Microsoft Security Blog
Microsoft Security Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
Stack Overflow Blog
Stack Overflow Blog
T
Tailwind CSS Blog
D
DataBreaches.Net
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
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
T
The Blog of Author Tim Ferriss
B
Blog
阮一峰的网络日志
阮一峰的网络日志
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
月光博客
月光博客
雷峰网
雷峰网
Recent Announcements
Recent Announcements
量子位
B
Blog RSS Feed

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
On the (In)security of Bluetooth Low Energy One-Way Secur...
Yue Zhang, Jian Weng, Rajib Dey, Yier Jin, Zhiqiang Lin, Xinwen · 2019-08-28 · via cs.CR updates on arXiv.org

To defeat security threats such as man-in-the-middle (MITM) attacks, Bluetooth Low Energy (BLE) 4.2 and 5.x introduce the Secure Connections Only mode, under which a BLE device accepts only secure paring protocols including Passkey Entry and Numeric Comparison from an initiator, e.g., an Android mobile. However, the BLE specification does not explicitly require the Secure Connection Only mode of the initiator. Taking the Android's BLE programming framework for example, we found that it cannot enforce secure pairing, invalidating the security protection provided by the Secure Connection Only mode. The same problem applies to Apple iOS too. Specifically, we examine the life cycle of a BLE pairing process in Android and identify four severe design flaws. These design flaws can be exploited by attackers to perform downgrading attacks, forcing the BLE pairing protocols to run in the insecure mode without the users' awareness. To validate our findings, we selected and tested 18 popular BLE commercial products and our experimental results proved that downgrading attacks and MITM attacks were all possible to these products. All 3501 BLE apps from Androzoo are also subject to these attacks. For defense, we have designed and implemented a prototype of the Secure Connection Only mode on Android 8 through the Android Open Source Project (AOSP). We have reported the identified BLE pairing vulnerabilities to Bluetooth Special Interest Group (SIG), Google, Apple, Texas Instruments (TI) and all of them are actively addressing this issue. Google rated the reported security flaw a High Severity.