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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
HECTOR-V: A Heterogeneous CPU Architecture for a Secure R...
Pascal Nasahl, Robert Schilling, Mario Werner, Stefan Mangard · 2020-09-11 · via cs.CR updates on arXiv.org

To ensure secure and trustworthy execution of applications, vendors frequently embed trusted execution environments into their systems. Here, applications are protected from adversaries, including a malicious operating system. TEEs are usually built by integrating protection mechanisms directly into the processor or by using dedicated external secure elements. However, both of these approaches only cover a narrow threat model resulting in limited security guarantees. Enclaves in the application processor typically provide weak isolation between the secure and non-secure domain, especially when considering side-channel attacks. Although secure elements do provide strong isolation, the slow communication interface to the application processor is exposed to adversaries and restricts the use cases. Independently of the used implementation approach, TEEs often lack the possibility to establish secure communication to external peripherals, and most operating systems executed inside TEEs do not provide state-of-the-art defense strategies, making them vulnerable against various attacks. We argue that TEEs implemented on the main application processor are insecure, especially when considering side-channel attacks. We demonstrate how a heterogeneous architecture can be utilized to realize a secure TEE design. We directly embed a processor into our architecture to provide strong isolation between the secure and non-secure domain. The tight coupling of TEE and REE enables HECTOR-V to provide mechanisms for establishing secure communication channels. We further introduce RISC-V Secure Co-Processor, a security-hardened processor tailored for TEEs. To secure applications executed inside the TEE, RVSCP provides control-flow integrity, rigorously restricts I/O accesses to certain execution states, and provides operating system services directly in hardware.