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cs.CR updates on arXiv.org

On the Security of Research Artifacts SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety 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 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
Very Pwnable Network: Cisco AnyConnect Security Analysis
Gerbert Roitburd, Matthias Ortmann, Matthias Hollick, Jiska Clas · 2022-02-11 · via cs.CR updates on arXiv.org

Corporate Virtual Private Networks (VPNs) enable users to work from home or while traveling. At the same time, VPNs are tied to a company's network infrastructure, forcing users to install proprietary clients for network compatibility reasons. VPN clients run with high privileges to encrypt and reroute network traffic. Thus, bugs in VPN clients pose a substantial risk to their users and in turn the corporate network. Cisco, the dominating vendor of enterprise network hardware, offers VPN connectivity with their AnyConnect client for desktop and mobile devices. While past security research primarily focused on the AnyConnect Windows client, we show that Linux and iOS are based on different architectures and have distinct security issues. Our reverse engineering as well as the follow-up design analysis and fuzzing reveal 13 new vulnerabilities. Seven of these are located in the Linux client. The root cause for privilege escalations on Linux is anchored so deep in the client's architecture that it only got patched with a partial workaround. A similar analysis on iOS uncovers three AnyConnect-specific bugs as well as three general issues in iOS network extensions, which apply to all kinds of VPNs and are not restricted to AnyConnect.