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AI_SAFETY

EU Regulatory Changes

668 changes tracked across 24 compliance frameworks including DORA, NIS2, GDPR, EU AI Act, Cyber Resilience Act, and more.

All DORA NIS2 GDPR CSRD MaRisk ISO27001 EU_AI_ACT CRA DSA DMA eIDAS2 SOC2 PCI_DSS HIPAA ISO42001 AMLD6 PSD3 DATA_ACT GPSR CER EUDR CVE BREACH AI_SAFETY
arXiv: TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems
arXiv: Probabilistic Agents in Deterministic Audits: Evaluating Multi-Agent Systems for Automated Audits Based on the...
arXiv: An Approach for a Supporting Multi-LLM System for Automated Certification Based on the German IT-Grundschutz
arXiv: Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks
arXiv: CrypFormBench: Benchmarking Formal Analysis Capability of Large Language Models for Cryptographic Schemes
arXiv: Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Direction...
arXiv: How Reliable Is Your Jailbreak Judge? Calibration and Adversarial Robustness of Automated ASR Scoring
arXiv: Information flow security on persistent memory
arXiv: Representation Matters: An Empirical Study of Program Representations for LLM Vulnerability Reasoning
arXiv: Maestro Order: A Model-Agnostic Orchestration Harness
This document, published on arXiv, introduces the Maestro Order, a proposed technical framework for orchestrating the safe deployment of AI models. It is not a regulation but a model-agnostic harne...
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arXiv: The Serialized Bridge: Understanding and Recovering LLM Serving Performance under Blackwell GPU Confidential C...
This publication, a research paper from June 2026, analyzes the performance impact of confidential computing on NVIDIA's Blackwell GPUs when serving large language models (LLMs). It introduces a co...
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arXiv: BipBipCache: Pipeline-Aware Integration of Low-Latency Tweakable Encryption in an Embedded Cache Controller
This publication introduces BipBipCache, a novel hardware-level encryption technique designed to secure data within a computer’s cache memory while maintaining very low latency. The paper proposes ...
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arXiv: AutoPRAC: Automating Attack Discovery for PRAC-Based Rowhammer Defenses using Model Checkers
This publication, titled AutoPRAC, presents a new automated method for discovering attack patterns that can bypass PRAC-based Rowhammer defenses in computer memory hardware. Rowhammer is a vulnerab...
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arXiv: Are Safety Guarantees in Neural Networks Safe? How to Compute Trustworthy Robustness Certifications
This publication, titled "Are Safety Guarantees in Neural Networks Safe? How to Compute Trustworthy Robustness Certifications," presents a critical analysis of existing methods used to certify the ...
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arXiv: HelpBench: Assessing the Ability of LLMs to Provide Privacy, Safety, and Security Advice
A new research paper, HelpBench, published on arXiv, introduces a benchmark designed to evaluate how well large language models provide advice on privacy, safety, and security. This is not a regula...
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arXiv: Burnyard: Future of Malware Analysis
This paper, published on arXiv, presents a new framework called Burnyard for analyzing malware using artificial intelligence. It is not a regulatory change from a governing body, but a technical pu...
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arXiv: PowerFuzz: Power-Based Black-Box Firmware Fuzzing
This publication introduces PowerFuzz, a novel black-box firmware fuzzing technique that uses power consumption measurements to detect vulnerabilities in embedded devices without requiring source c...
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arXiv: FirmCure:Towards Autonomous and Adaptive Rehosting of Linux-Based Firmware
This publication, FirmCure, presents a novel technical framework for the autonomous and adaptive rehosting of Linux-based firmware, enabling large-scale dynamic analysis of embedded systems. While ...
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arXiv: Red-Teaming the Agentic Red-Team
arXiv: Discrepancy for Random Linear Codes