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AI_SAFETY

EU Regulatory Changes

371 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: Secure and Parallel Determinant Computation for Large-Scale Matrices in Edge Environments
arXiv: VIPER-MCP: Detecting and Exploiting Taint-Style Vulnerabilities in Model Context Protocol Servers
This publication, titled VIPER-MCP, presents a new methodology for detecting and exploiting taint-style vulnerabilities within Model Context Protocol (MCP) servers. MCP is an emerging standard that...
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arXiv: Auditing Apple's DifferentialPrivacy.framework: Implementation Bugs, Misconfigurations, and Practical Risks
A new academic paper published on arXiv on May 20, 2026, presents an audit of Apple’s DifferentialPrivacy.framework, revealing implementation bugs, misconfigurations, and practical risks that under...
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arXiv: Onion-Routed Multi-Circuit Key Establishment for Quantum-Resilient Sessions
This publication from arXiv, dated May 2026, presents a technical proposal for a new cryptographic protocol called "Onion-Routed Multi-Circuit Key Establishment." The paper outlines a method for es...
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arXiv: Profiling User Vulnerability to Phishing Through Psychological and Behavioral Factors
This publication from arXiv, dated May 20, 2026, presents a research paper that profiles user vulnerability to phishing by analyzing psychological and behavioral factors. While not a regulatory cha...
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arXiv: Information Leakage Envelopes
A new preprint from arXiv, titled "Information Leakage Envelopes," introduces a formal method for quantifying and bounding the unintended disclosure of sensitive information by AI systems during in...
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arXiv: Detecting Trojaned DNNs via Spectral Regression Analysis
This publication introduces a novel technical method for detecting Trojan attacks in deep neural networks (DNNs) using spectral regression analysis. While not a regulatory change itself, it represe...
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arXiv: Image Encryption via Data-Identified Discrete Chaotic Maps
A new research paper published on arXiv proposes an image encryption method using data-identified discrete chaotic maps, which could have implications for data protection and AI safety compliance. ...
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arXiv: Backchaining Loss of Control Mitigations from Mission-Specific Benchmarks in National Security
This paper, published on arXiv under the AI Safety framework, introduces a novel methodology for managing loss of control risks in advanced AI systems, specifically tailored to national security co...
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arXiv: An Evidence-driven Protocol for Trustworthy CI Pipelines
This publication introduces a new evidence-driven protocol for building trustworthy continuous integration (CI) pipelines, specifically designed to align with the AI Safety framework. The protocol ...
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arXiv: Verifiable Provenance and Watermarking for Generative AI: An Evidentiary Framework for International Operation...
This paper, published on arXiv, proposes a new evidentiary framework for using verifiable provenance and watermarking technologies in generative AI. It specifically addresses how these technical me...
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arXiv: Domijn: The Security of Domain Registrars and the Risk of a Domain Name Takeover
arXiv: An IoT-Enabled Smart Home Automation System for Energy Efficiency with Web-Based Control
arXiv: Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning
arXiv: Comparative Evaluation of Deep Learning Models for Fake Image Detection
arXiv: Ark: Offchain Transaction Batching in Bitcoin
arXiv: Privacy-Preserving Distributed Optimization Under Time Constraints Using Secure Multi-Party Computation and Ev...
arXiv: GenAI-Driven Threat Detection with Microsoft Security Copilot
arXiv: Precision and Privacy in Distributed Quantum Sensing: A Quantum Fisher Information Duality
arXiv: Rethinking Fraud Safety Evaluation: Multi-Round Attacks Reveal Safety-Utility Tradeoffs in Graph-Context LLM D...