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Cyber Security Advisories - MS-ISAC
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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
QuickSync: A Quickly Synchronizing PoS-Based Blockchain P...
Shoeb Siddiqui, Varul Srivastava, Raj Maheshwari, Sujit Gujar · 2020-05-07 · via cs.CR updates on arXiv.org

To implement a blockchain, we need a blockchain protocol for all the nodes to follow. To design a blockchain protocol, we need a block publisher selection mechanism and a chain selection rule. In Proof-of-Stake (PoS) based blockchain protocols, block publisher selection mechanism selects the node to publish the next block based on the relative stake held by the node. However, PoS protocols, such as Ouroboros v1, may face vulnerability to fully adaptive corruptions. In this paper, we propose a novel PoS-based blockchain protocol, QuickSync, to achieve security against fully adaptive corruptions while improving on performance. We propose a metric called block power, a value defined for each block, derived from the output of the verifiable random function based on the digital signature of the block publisher. With this metric, we compute chain power, the sum of block powers of all the blocks comprising the chain, for all the valid chains. These metrics are a function of the block publisher's stake to enable the PoS aspect of the protocol. The chain selection rule selects the chain with the highest chain power as the one to extend. This chain selection rule hence determines the selected block publisher of the previous block. When we use metrics to define the chain selection rule, it may lead to vulnerabilities against Sybil attacks. QuickSync uses a Sybil attack resistant function implemented using histogram matching. We prove that QuickSync satisfies common prefix, chain growth, and chain quality properties and hence it is secure. We also show that it is resilient to different types of adversarial attack strategies. Our analysis demonstrates that QuickSync performs better than Bitcoin by an order of magnitude on both transactions per second and time to finality, and better than Ouroboros v1 by a factor of three on time to finality.