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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
SoK: A Security Architect's View of Printed Circuit Board...
Jacob Harrison, Nathan Jessurun, Mark Tehranipoor · 2024-10-14 · via cs.CR updates on arXiv.org

Many recent papers have proposed novel electrical measurements or physical inspection technologies for defending printed circuit boards (PCBs) and printed circuit board assemblies (PCBAs) against tampering. As motivation, these papers frequently cite Bloomberg News' "The Big Hack", video game modchips, and "interdiction attacks" on IT equipment. We find this trend concerning for two reasons. First, implementation errors and security architecture are rarely discussed in recent PCBA security research, even though they were the root causes of these commonly-cited attacks and most other attacks that have occurred or been proposed by researchers. This suggests that the attacks may be poorly understood. Second, if we assume that novel countermeasures and validation methodologies are tailored to these oft-cited attacks, then significant recent work has focused on attacks that can already be mitigated instead of on open problems. We write this SoK to address these concerns. We explain which tampering threats can be mitigated by PCBA security architecture. Then, we enumerate assumptions that security architecture depends on. We compare and contrast assurances achieved by security architecture vs. by recently-proposed electrical or inspection-based tamper detection. Finally, we review over fifty PCBA attacks to show how most can be prevented by proper architecture and careful implementation.