EU Regulatory Changes

This publication, a research paper titled "When Good Verifiers Go Bad," presents findings that are highly relevant to AI safety compliance under the EU AI Act. The study demonstrates that self-impr...

This document is a research paper published on arXiv, not an official regulatory change. It analyzes security threats to blockchain interoperability, such as bridge attacks and oracle manipulation,...

This publication from June 2026 presents a systematic study on how websites detect and block automated data collection tools, known as bots. The research reveals that bot detection techniques are n...

This paper, published on arXiv on June 12, 2026, presents a novel vulnerability in AI safety guardrails. The research demonstrates that the very mechanisms designed to protect large language model ...

This publication, titled "Securing the Future of IoMT in the Post-Quantum Era: An Edge-Native Federated Learning Approach," is a research paper from arXiv, not a binding regulatory change. It propo...

A new academic paper published on arXiv, titled "Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis," highlights a critical vulnerability in quantized neural netw...

This publication, titled REPOSE: Quantifying the Price of Security in Weakly-Hard Real-Time Cyber-Physical Systems, introduces a formal framework for measuring the trade-off between security enforc...

A new research paper, AgentCyberRange, has been published on arXiv, proposing a framework for benchmarking the cybersecurity capabilities of advanced AI systems within realistic cyber range environ...

This publication from arXiv presents a technical research paper exploring how role-based agentic architectures—essentially, AI systems with specialized roles—can be used to improve vulnerability ha...

This paper, published on arXiv, evaluates the effectiveness of large language models in detecting and classifying obfuscation techniques within Android applications. It does not represent a new reg...