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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
The Heisenberg Defense: Proactively Defending SGX Enclave...
Raoul Strackx, Frank Piessens · 2017-12-22 · via cs.CR updates on arXiv.org

Protected-module architectures (PMAs) have been proposed to provide strong isolation guarantees, even on top of a compromised system. Unfortunately, Intel SGX -- the only publicly available high-end PMA -- has been shown to only provide limited isolation. An attacker controlling the untrusted page tables, can learn enclave secrets by observing its page access patterns. Fortifying existing protected-module architectures in a real-world setting against side-channel attacks is an extremely difficult task as system software (hypervisor, operating system, ...) needs to remain in full control over the underlying hardware. Most state-of-the-art solutions propose a reactive defense that monitors for signs of an attack. Such approaches unfortunately cannot detect the most novel attacks, suffer from false-positives, and place an extraordinary heavy burden on enclave-developers when an attack is detected. We present Heisenberg, a proactive defense that provides complete protection against page table based side channels. We guarantee that any attack will either be prevented or detected automatically before {\em any} sensitive information leaks. Consequently, Heisenberg can always securely resume enclave execution -- even when the attacker is still present in the system. We present two implementations. Heisenberg-HW relies on very limited hardware features to defend against page-table-based attacks. We use the x86/SGX platform as an example, but the same approach can be applied when protected-module architectures are ported to different platforms as well. Heisenberg-SW avoids these hardware modifications and can readily be applied. Unfortunately, it's reliance on Intel Transactional Synchronization Extensions (TSX) may lead to significant performance overhead under real-life conditions.