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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
Spying on the Spy: Security Analysis of Hidden Cameras
Samuel Herodotou, Feng Hao · 2023-06-01 · via cs.CR updates on arXiv.org

Hidden cameras, also called spy cameras, are surveillance tools commonly used to spy on people without their knowledge. Whilst previous studies largely focused on investigating the detection of such a camera and the privacy implications, the security of the camera itself has received limited attention. Compared with ordinary IP cameras, spy cameras are normally sold in bulk at cheap prices and are ubiquitously deployed in hidden places within homes and workplaces. A security compromise of these cameras can have severe consequences. In this paper, we analyse a generic IP camera module, which has been packaged and re-branded for sale by several spy camera vendors. The module is controlled by mobile phone apps. By analysing the Android app and the traffic data, we reverse-engineered the security design of the whole system, including the module's Linux OS environment, the file structure, the authentication mechanism, the session management, and the communication with a remote server. Serious vulnerabilities have been identified in every component. Combined together, they allow an adversary to take complete control of a spy camera from anywhere over the Internet, enabling arbitrary code execution. This is possible even if the camera is behind a firewall. All that an adversary needs to launch an attack is the camera's serial number, which users sometimes unknowingly share in online reviews. We responsibly disclosed our findings to the manufacturer. Whilst the manufacturer acknowledged our work, they showed no intention to fix the problems. Patching or recalling the affected cameras is infeasible due to complexities in the supply chain. However, it is prudent to assume that bad actors have already been exploiting these flaws. We provide details of the identified vulnerabilities in order to raise public awareness, especially on the grave danger of disclosing a spy camera's serial number.