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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
Defending Against Attack on the Cloned: In-Band Active Ma...
Wil Liam Teng, Kasper Rasmussen · 2024-10-21 · via cs.CR updates on arXiv.org

With Signal's position as one of the most popular secure messaging protocols in use today, the threat of government coercion and mass surveillance, i.e., active Man-in-the-Middle (MitM) attacks, are more relevant than ever. On the other hand, studies [29, 33, 37, 38] have shown that user awareness is very poor when it comes to authenticating keys in instant messaging applications, e.g., comparing key fingerprints out-of-band. The ideal solution to this problem should not require the active participation of the users. Our solution to active MitM attacks builds directly on Signal. We automate the process of key confirmation without relying on the intervention of users, and without using an out-of-band communication channel, at the cost of slightly altered trust assumptions on the server. We consider a powerful active MitM that not only controls the communication channel, but also has (one time) access to all secrets on one of the clients, i.e., can perform a key compromise attack. Our solution utilises the server to keep track of the changes in the clients key fingerprint as ratcheting is performed. Given that the server can keep a message log already, we find that any impact on deniability is minimal in practice. We present our detailed modifications to Signal, and document the new security guarantees while preserving the existing security guarantees of Signal. Our proof-of-concept implementation, which is based on the open-source Signal library used in real-world instant messaging applications, shows that our solution is practical and integrates well with the library. Our experimental results further show that our solution only has a tiny performance overhead when compared to Signal.