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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
Slick: Secure Middleboxes using Shielded Execution
Bohdan Trach, Alfred Krohmer, Sergei Arnautov, Franz Gregor, Pra · 2017-09-13 · via cs.CR updates on arXiv.org

Cloud computing offers the economies of scale for computational resources with the ease of management, elasticity, and fault tolerance. To take advantage of these benefits, many enterprises are contemplating to outsource the middlebox processing services in the cloud. However, middleboxes that process confidential and private data cannot be securely deployed in the untrusted environment of the cloud. To securely outsource middleboxes to the cloud, the state-of-the-art systems advocate network processing over the encrypted traffic. Unfortunately, these systems support only restrictive middlebox functionalities, and incur prohibitively high overheads due to the complex computations involved over the encrypted traffic. This motivated the design of Slick --- a secure middlebox framework for deploying high-performance Network Functions (NFs) on untrusted commodity servers. Slick exposes a generic interface based on Click to design and implement a wide-range of NFs using its out-of-the box elements and C++ extensions. Slick leverages SCONE (a shielded execution framework based on Intel SGX) and DPDK to securely process confidential data at line rate. More specifically, Slick provides hardware-assisted memory protection, and configuration and attestation service for seamless and verifiable deployment of middleboxes. We have also added several new features for commonly required functionalities: new specialized Click elements for secure packet processing, secure shared memory packet transfer for NFs chaining, secure state persistence, an efficient on-NIC timer for SGX enclaves, and memory safety against DPDK-specific Iago attacks. Furthermore, we have implemented several SGX-specific optimizations in Slick. Our evaluation shows that Slick achieves near-native throughput and latency.