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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
A Wireless Intrusion Detection System for 802.11 WPA3 Net...
Neil Dalal, Nadeem Akhtar, Anubhav Gupta, Nikhil Karamchandani, · 2021-10-09 · via cs.CR updates on arXiv.org

Wi-Fi (802.11) networks have become an essential part of our daily lives; hence, their security is of utmost importance. However, Wi-Fi Protected Access 3 (WPA3), the latest security certification for 802.11 standards, has recently been shown to be vulnerable to several attacks. In this paper, we first describe the attacks on WPA3 networks that have been reported in prior work; additionally, we show that a deauthentication attack and a beacon flood attack, known to be possible on a WPA2 network, are still possible with WPA3. We launch and test all the above (a total of nine) attacks using a testbed that contains an enterprise Access Point (AP) and Intrusion Detection System (IDS). Our experimental results show that the AP is vulnerable to eight out of the nine attacks and the IDS is unable to detect any of them. We propose a design for a signature-based IDS, which incorporates techniques to detect all the above attacks. Also, we implement these techniques on our testbed and verify that our IDS is able to successfully detect all the above attacks. We provide schemes for mitigating the impact of the above attacks once they are detected. We make the code to perform the above attacks as well as that of our IDS publicly available, so that it can be used for future work by the research community at large.