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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
Nyon Unchained: Forensic Analysis of Bosch's eBike Board ...
Marcel Stachak, Julian Geus, Gaston Pugliese, Felix Freiling · 2024-04-19 · via cs.CR updates on arXiv.org

Modern eBike on-board computers are basically small PCs that not only offer motor control, navigation, and performance monitoring, but also store lots of sensitive user data. The Bosch Nyon series of board computers are cutting-edge devices from one of the market leaders in the eBike business, which is why they are especially interesting for forensics. Therefore, we conducted an in-depth forensic analysis of the two available Nyon models released in 2014 and 2021. On a first-generation Nyon device, Telnet access could be established by abusing a design flaw in the update procedure, which allowed the acquisition of relevant data without risking damage to the hardware. Besides the user's personal information, the data analysis revealed databases containing user activities, including timestamps and GPS coordinates. Furthermore, it was possible to forge the data on the device and transfer it to Bosch's servers to be persisted across their online service and smartphone app. On a current second-generation Nyon device, no software-based access could be obtained. For this reason, more intrusive hardware-based options were considered, and the data could be extracted via chip-off eventually. Despite encryption, the user data could be accessed and evaluated. Besides location and user information, the newer model holds even more forensically relevant data, such as nearby Bluetooth devices.