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AI_SAFETY

EU Regulatory Changes

1501 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: Not In My Git Yard: Catching Backdoors at Commit and Release Time
arXiv: Graph Is the Verifier: Agentic Reinforcement Learning for Interprocedural Vulnerability Detection
arXiv: Fingerprint-Driven Automation: Coupling Reconnaissance with POC Verification
arXiv: Borrowed Strength: Best-of-N Search over a Code EncodingBreaks Self-Check Jailbreak Defenses
arXiv: Guarding Organizations Against Malware Risk: A Novel Graph-Based Malware Detection Method
arXiv: CDN Tsunami: Exploiting HTTP/3-HTTP/1.1 Conversion for DoS Attacks
arXiv: Recover, Decode, Reguard: Guard-Agnostic Defense Amplification againstEncoded VLM Jailbreaks
arXiv: Explicit Separations for One-Query Unitary Synthesis
arXiv: Collusion with Competitive Marginals: Price-Level Audits Are Blind by Construction
arXiv: QUIC-TRIP: A Triple-Redundant Journey Toward Secure Substation Communications
arXiv: A Controlled Candidate-Set Benchmark for Offline Satellite-Security Plan Decomposition
arXiv: Optimistic Verifiable Claims: A Blockchain Protocol for Conditionally Confidential Bidding in Decentralized Ma...
This publication from arXiv introduces a blockchain protocol called Optimistic Verifiable Claims, designed to enable conditionally confidential bidding in decentralized manufacturing. The protocol ...
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arXiv: Anti-Backdoor Coreset Selection via Cumulative Entropy
A new research paper titled "Anti-Backdoor Coreset Selection via Cumulative Entropy" has been published on arXiv, proposing a method to detect and remove poisoned training data that could introduce...
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arXiv: Architectural Backdoors in Vision-Language Model Supply Chains via Representation Steering
This publication, titled Architectural Backdoors in Vision-Language Model Supply Chains via Representation Steering, is a pre-print research paper from July 2026 that identifies a novel class of su...
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arXiv: From Profiling to Parameterization: Physics-Guided Acoustic Eavesdropping via Smartphone Accelerometers
This paper, published on arXiv, demonstrates a novel method for acoustic eavesdropping using smartphone accelerometers, which are typically considered low-risk sensors. The research shows that by a...
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arXiv: Bits and Memories: Measuring Verbatim Extraction Across LLM Quantization
A new research paper, "Bits and Memories: Measuring Verbatim Extraction Across LLM Quantization," published on arXiv, presents findings that quantizing large language models (LLMs) to lower precisi...
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arXiv: SafeStats: Efficient 2PC Protocols for Data Statistic-Related Functions
This publication introduces SafeStats, a new set of cryptographic protocols designed to enable two-party computation (2PC) for common statistical functions, such as mean, variance, and regression, ...
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arXiv: The Disruptive Impact of Large Language Models on Capture the Flag Competitions and the Path Toward Fair Play
This paper, published on arXiv, analyzes the disruptive impact of large language models on Capture the Flag cybersecurity competitions, which are widely used for talent assessment and training. It ...
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arXiv: Bayesian-Guided Cooperative RL Beamforming for Wireless Adversarial User Detection
This publication from July 2026 introduces a novel machine learning framework, Bayesian-Guided Cooperative Reinforcement Learning, designed to improve wireless network security by detecting adversa...
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arXiv: Hybrid Analysis for Secure MCP Tool Use in LLM Agents
This paper, published on arXiv, introduces a novel hybrid analysis framework designed to enhance the security of Large Language Model (LLM) agents that use external tools via the Model Context Prot...
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