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◬ AI & Machine Learning Jun 02, 2026
NICE: A Framework for Declarative and Machine-Checkable Vulnerability Reproduction

arXiv:2606.00625v1 Announce Type: new Abstract: Reproducing software vulnerabilities is fundamental to security researchers, open-source maintainers, and educators. Yet, vulnerabilities remain hard to…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Authenticity Debt and the Synthetic Content Threat Landscape: A Layered Framework for Trust, Provenance, and IP Governance in the Generative AI Era

arXiv:2606.00621v1 Announce Type: new Abstract: Generative artificial intelligence has fundamentally changed how content is now produced. It has enabled how high-fidelity text, images, audio, and vide…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
"I Strongly Suspect This Website Is a Scam": Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents

arXiv:2606.00497v1 Announce Type: new Abstract: Deceptive web content, widely instantiated across the internet and commonly known as \textit{social-engineering attacks}, manipulates autonomous web age…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Confused ChatGPT: Cross-App Context Poisoning via First-Party APIs

arXiv:2606.00485v1 Announce Type: new Abstract: ChatGPT Apps, launched by OpenAI on Oct. 6, 2025, introduce an app-in-app paradigm in which third-party applications share a single chat context with th…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Stochastic Analysis of Cybersecurity Defense Strategies Under Single Attack Scenario

arXiv:2606.00481v1 Announce Type: new Abstract: This research presents a novel stochastic framework for proactive cybersecurity defense timing under a single attack scenario. The approach models the d…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Beyond Edge Coverage: Per-Task Data-Flow Extraction at Kernel Function Boundaries via LLVM

arXiv:2606.00455v1 Announce Type: new Abstract: Coverage-guided kernel fuzzers such as syzkaller rely on edge coverage (trace-pc) as their sole feedback signal. This context-blind approach cannot dist…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Bit-Exact AI Inference Verification Without Performance Tradeoffs

arXiv:2606.00279v1 Announce Type: new Abstract: Verifying claims about AI workloads is a pre- requisite for credible AI governance of covert adversaries (who comply with monitoring only when detection…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
A Moderatorless Protocol for WEREWOLF

arXiv:2606.00190v1 Announce Type: new Abstract: Social deduction games, or hidden-role games, are multiplayer games in which players are assigned private roles and act under asymmetric information abo…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
How to Compare the Security of Code Written by Humans to LLM-generated Code

arXiv:2606.00186v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly transforming how software is created and maintained. Comparing LLM-generated code against human-written standar…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Inferring Routing-Layer Defense Mechanisms from Observable Behavior in OLSR-Based MANETs

arXiv:2606.00184v1 Announce Type: new Abstract: Mobile ad hoc networks (MANETs) based on proactive routing protocols such as OLSR remain vulnerable to routing-layer attacks. While prior work has focus…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

arXiv:2606.00161v1 Announce Type: new Abstract: The detection of intrusions in IoT-based networks poses challenges that cannot be overcome using traditional machine learning methods. Perhaps the bigge…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
DataShield: Safety-degrading Data Filtering for LLM Benign Instruction Fine-Tuning

arXiv:2606.00160v1 Announce Type: new Abstract: Large language models (LLMs) suffer from degraded safety capabilities even when fine-tuned with benign datasets. However, existing methods for identifyi…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection)

arXiv:2606.00155v1 Announce Type: new Abstract: Modern network intrusion detection systems (NIDS) are caught in a structural contradiction: the protocols carrying the highest threat intelligence are p…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
PrivacyPeek: Auditing What LLM-Based Agents Acquire, Not Just What They Say

arXiv:2606.00152v1 Announce Type: new Abstract: LLM-based agents are rapidly advancing, autonomously invoking external tools to complete multi-step tasks for users. However, agents often acquire more …

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models

arXiv:2606.00150v1 Announce Type: new Abstract: As Large Language Models evolve for user convenience, vulnerability to jailbreak attacks continues to be reported despite ongoing efforts in safety trai…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
XAI-SOH-FL: Enhancing SOH-FL with Adaptive Aggregation and Explainable AI for Intrusion Detection in Heterogeneous IoT

arXiv:2606.00134v1 Announce Type: new Abstract: Intrusion Detection Systems (IDS) in Internet of Things (IoT) environments face significant challenges due to data heterogeneity, lack of labeled data, …

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
From Frontier to Shadow AI: A Simmering Threat to Assurance and Security in Critical Infrastructure

arXiv:2606.00088v1 Announce Type: new Abstract: Frontier AI systems, including large language models and emerging agentic AI tools, offer significant operational benefits but present unique challenges…

arXiv Security Read →
◬ AI & Machine Learning Jun 02, 2026
A Survey on Security with Quantum Computing

arXiv:2606.00058v1 Announce Type: new Abstract: Quantum computing has emerged as a transformative computing paradigm capable of solving problems that remain computationally infeasible for classical sy…

arXiv Security Read →
◬ AI & Machine Learning Jun 01, 2026
How we used Gemini to build Google I/O 2026

Learn how Googlers used AI to produce Google I/O 2026.

Google AI Read →
◬ AI & Machine Learning Jun 01, 2026
Beyond LLMs: Why Scalable Enterprise AI Adoption Depends on Agent Logic
Hugging Face Read →
◬ AI & Machine Learning Jun 01, 2026
Introducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains
Hugging Face Read →
◬ AI & Machine Learning Jun 01, 2026
Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action
Hugging Face Read →
◬ AI & Machine Learning Jun 01, 2026
Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration

arXiv:2605.31365v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on han…

arXiv AI Read →
◬ AI & Machine Learning Jun 01, 2026
Diagnosing Failure Modes of Shared-State Collaboration in Resource-Constrained Visual Agents

arXiv:2605.31354v1 Announce Type: new Abstract: Modular visual reasoning systems increasingly rely on shared working memory for multi-step collaboration, yet the failure dynamics of intermediate state…

arXiv AI Read →
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