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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
Hide & Seek: Seeking the (Un)-Hidden key in Provably-...
Satwik Patnaik, Nimisha Limaye, Ozgur Sinanoglu · 2022-09-05 · via cs.CR updates on arXiv.org

Logic locking protects an IC from threats such as piracy of design IP and unauthorized overproduction throughout the IC supply chain. Out of the several techniques proposed by the research community, provably-secure logic locking (PSLL) has acquired a foothold due to its algorithmic and provable-security guarantees. However, the security of these techniques is questioned by attackers that exploit the vulnerabilities arising from the hardware implementation. Such attacks (i) are predominantly specific to locking techniques and (ii) lack generality and scalability. This leads to a plethora of attacks, and defenders, find it challenging to ascertain the security of newly developed PSLL techniques. Additionally, there is no repository of locked circuits that attackers can use to benchmark (and compare) their attacks. In this work, we develop a generalized attack that can recover the secret key across different PSLL techniques. To that end, we extract functional and structural properties depending on the hardware construction of the PSLL techniques and develop two attacks based on the concepts of VLSI testing and Boolean transformations. We evaluate our attacks on 30,000 locked circuits across 14 PSLL techniques, including nine unbroken techniques. Our attacks successfully recover the secret key (100% accuracy) for all the techniques. Our experimentation across different (I) technology libraries, (ii) synthesis tools, and (iii) logic optimization settings provide interesting insights. For instance, our attacks recover the secret key by only using the locked circuit when an academic synthesis tool is used. Additionally, designers can use our attacks as a verification tool to ascertain the lower-bound security achieved by hardware implementations. We shall release our artifacts, which could help foster the development of future attacks and defenses in the PSLL domain.