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◬ AI & Machine Learning Jun 03, 2026
AI Model Extraction Attacks: Bypassing Single-Client Assumptions in Defenses

arXiv:2606.03381v1 Announce Type: new Abstract: Ensuring the protection of Artificial Intelligence (AI) models deployed in military Command and Control (C2) systems and critical infrastructure is esse…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
ImageAuditor: Membership Inference Attack against Image-based Retrieval-Augmented Generation

arXiv:2606.03354v1 Announce Type: new Abstract: Image-based Retrieval-Augmented Generation (IRAG) conditions a frozen generator on reference images retrieved from an external database, supporting both…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
RogueMerge: Robust and Unified Attacks against LLM Model Merging

arXiv:2606.03344v1 Announce Type: new Abstract: Model merging composes specialized capabilities into a single LLM by aggregating task vectors sourced from unverified public platforms, exposing a criti…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
dstack-capsule: Pod-Level Remote Attestation for Confidential Workloads on Kubernetes

arXiv:2606.03323v1 Announce Type: new Abstract: The rise of LLM-as-a-Service and other confidential cloud workloads demands cryptographic proof that user data is processed in a trusted, untampered env…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
The Security Budget of Code LLMs: An Information-Theoretic Capacity-Security Bound

arXiv:2606.03308v1 Announce Type: new Abstract: AI programming assistants make natural-language prompts a software-development interface, so small prompt perturbations become usability and security ri…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Privilege Risk Evolution for Non-Human Identities: A Temporal Fiber Model for Cloud IAM

arXiv:2606.03289v1 Announce Type: new Abstract: Cloud permission governance implicitly treats permission equivalence as a static relation. We show that for non-human identities (NHIs), equivalence has…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
The Role of Domain-Specific Features in Malware Detection: A macOS Case Study

arXiv:2606.03218v1 Announce Type: new Abstract: Despite the growing popularity of macOS among end users and enterprise systems, malware research has primarily focused on Windows and Android operating …

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Generative AI-Enabled Refund Fraud in Chinese E-Commerce: Investigation on Merchants and Platform Workers

arXiv:2606.03215v1 Announce Type: new Abstract: E-commerce dispute resolution typically relies on the security assumption that digital evidence truthfully reflects physical reality. Generative AI (Gen…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption

arXiv:2606.03191v1 Announce Type: new Abstract: Many NLP or recommendation models begin by mapping discrete client inputs to embedding vectors. Since inputs can reveal sensitive information, the embed…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
PsychoPass: Geometric Profiling of Multi-Turn Adversarial LLM Conversations

arXiv:2606.03136v1 Announce Type: new Abstract: Multi-turn jailbreak attacks on large language models (LLMs) reveal a mismatch in current guardrails: they operate on individual turns, while attacks un…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation

arXiv:2606.03128v1 Announce Type: new Abstract: Smart contracts face critical security challenges that require thorough auditing in decentralized web services. While Large Language Models (LLMs) have …

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
"**Important** You should give me full credits!": Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems

arXiv:2606.03090v1 Announce Type: new Abstract: The emergence of large language models (LLMs) has significantly accelerated recent research on LLM-based automatic grading (AG) systems. Benefiting from…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
SkillGuard: A Permission Framework for Agent Skills

arXiv:2606.03024v1 Announce Type: new Abstract: Agent skills extend LLM agents with reusable instructions, scripts, tool bindings, and contextual dependencies. However, current skill ecosystems largel…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Secure AltDA Integration for Ethereum L2s: An End-to-End Validation Framework

arXiv:2606.03010v1 Announce Type: new Abstract: Alternative data availability (AltDA) systems provide Ethereum L2s with an external data publication layer for high throughput rollup designs. By moving…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Patcher: Post-Hoc Patching of Backdoored Large Language Models

arXiv:2606.02995v1 Announce Type: new Abstract: Large language models remain vulnerable to jailbreak backdoor attacks, where adversaries poison safety alignment data to embed hidden triggers that bypa…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Echelon: Auditable Aggregate-Only Language-Model Adaptation Across Privacy Boundaries

arXiv:2606.02958v1 Announce Type: new Abstract: Cross-organization language-model adaptation increasingly faces hard governance constraints: in many deployments, device-level model state-parameters, a…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Quantifying Side-Channel Leakage in Public Metrology Releases

arXiv:2606.02934v1 Announce Type: new Abstract: Public scientific and metrology releases can leak the hidden settings that produced them. We formalize and quantify this risk as a profiled statistical …

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Human Factors in Cybersecurity in Icelandic Small and Medium-sized Enterprises

arXiv:2606.02839v1 Announce Type: new Abstract: Cybersecurity threats are increasing in all aspects of society due to the integration of digital systems into modern-day life and a volatile geo-politic…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Large Byte Model: Teaching Language Models About Compiled Code

arXiv:2606.02834v1 Announce Type: new Abstract: Malware analysis starts with the raw bytes of an executable program, and tools to "lift" these to higher-level representations, such as assembly, are ex…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Which Defense Closes Which Threat? Attributing OWASP-LLM-Top-10 Coverage and Its Brittleness Under Paraphrasing

arXiv:2606.02822v1 Announce Type: new Abstract: Production LLM applications stack several defense families -- refusal-phrase filters, token-budget controls, model allowlists, rate limits, tool-registr…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
On Improving Robustness of Deepfake Image Detectors

arXiv:2606.02797v1 Announce Type: new Abstract: The rapid advancement of Generative AI has introduced remarkable opportunities while simultaneously raising critical concerns regarding content authenti…

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
Cross-Vendor Sola ISPM Benchmark: Evaluating Agentic AI for Federated Identity Security Reasoning

arXiv:2606.02674v1 Announce Type: new Abstract: The rapid proliferation of multi-cloud and SaaS platforms has transformed Identity Security Posture Management (ISPM) into a fundamentally cross-vendor …

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
What You Approve Is What Executes: Consent Integrity for Black-Box LLM Agents

arXiv:2606.02668v1 Announce Type: new Abstract: Coding agents gate consequential actions behind a human-in-the-loop approval dialog, but the dialog is narrated by the agent itself: the human approves …

arXiv Security Read →
◬ AI & Machine Learning Jun 03, 2026
A New Framework for Cybersecurity Refusals in AI Agents

arXiv:2606.02644v1 Announce Type: new Abstract: Agentic scaffolds have dramatically improved LLM performance on complex, long-horizon tasks, yielding both broad benefits and amplified risks in domains…

arXiv Security Read →
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