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AI_SAFETY

EU Regulatory Changes

571 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: Stealthy World Model Manipulation via Data Poisoning
arXiv: Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications
arXiv: TGCM: Topic-Guided Generative Disentanglement of Interleaved APT Technique Sequences
arXiv: Code-Augur: Agentic Vulnerability Detection via Specification Inference
arXiv: MIDS: Detecting Stealthy Masquerade and Tampering Attacks on CAN Bus via Bidirectional Mamba
arXiv: The Gate Is Only as Honest as Its Contracts: ContractGuard for the Contract Layer of Risk-Aware Causal Gating
arXiv: Confident yet Concerned: Inconsistencies in Computing Students' Attitudes on Cybersecurity
arXiv: AI Sandboxes: A Threat Model, Taxonomy, and Measurement Framework
arXiv: Evaluating Prompting-Based Defenses Against Domain-Camouflaged Injection Attacks
arXiv: From Bits to Mixed-Radix Keys: Horner Decomposition, Uniform Sampling, and the Information-Theoretic QKD Inter...
arXiv: SoK: AI-Augmented Binary Reversing
This publication is a Systematization of Knowledge (SoK) paper from arXiv that surveys how artificial intelligence is being used to automate binary code reverse engineering. It maps current AI tech...
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arXiv: OTRO: Oblivious Tokenization Path with Square-Root ORAM
This publication introduces OTRO, a novel cryptographic protocol for Oblivious Tokenization Path with Square-Root ORAM, designed to enhance privacy and security in data retrieval systems. The frame...
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arXiv: ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software
This publication introduces the ARVO framework, a comprehensive atlas cataloguing reproducible vulnerabilities in open-source software components. It systematically documents known security flaws w...
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arXiv: Syntactic Systems Cannot See Semantic Invariants
A new preprint from arXiv, titled "Syntactic Systems Cannot See Semantic Invariants," has been published under the AI Safety framework. The paper argues that current large language models and other...
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arXiv: Learning Red Agent Policy from Observations for Neurosymbolic Autonomous Cyber Agents
This paper, published on arXiv, presents a novel framework for training autonomous cyber agents using a neurosymbolic approach that learns from observations rather than explicit programming. The re...
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arXiv: Gatling: Rapid-Fire Consensus from Parallel Composition
This publication introduces a new consensus protocol called Gatling, designed to achieve rapid transaction finality through parallel processing. While not a regulatory change itself, it signals a s...
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arXiv: Seeing Is Not Screening: Multimodal Hidden Instruction Attacks on Agent Skill Scanners
This paper, published on arXiv, presents a new class of security vulnerability specifically targeting AI agents that use multimodal inputs—such as images, text, and audio. The authors demonstrate t...
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arXiv: A Red-Team Study of Anthropic Fable 5 & Opus 4.8 Models
A new red-team study published on arXiv evaluates the safety of Anthropic’s Fable 5 and Opus 4.8 models, focusing on their susceptibility to generating harmful or deceptive outputs. The research sy...
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arXiv: Multi-Source Cybersecurity Logs: An ATT&CK-Labeled Dataset and SLM Evaluation
A new research paper published on arXiv presents a dataset of multi-source cybersecurity logs labeled with the MITRE ATT&CK framework, along with an evaluation framework for small language models (...
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arXiv: Evaluating Open-Source LLMs for Multi-Label ATT&CK Technique Classification on CTI Reports