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◬ AI & Machine Learning Jun 24, 2026
AutoSpec: Safety Rule Evolution for LLM Agents via Inductive Logic Programming

arXiv:2606.24245v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly automate complex tasks by integrating language models with external tools and environments. However, th…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Inside Crypter-as-a-Service: An Ecosystem Analysis of the exploit.in Underground Forum Research Talks

arXiv:2606.24226v1 Announce Type: cross Abstract: Crypter-as-a-Service (CraaS) has become a key enabling layer of the contemporary malware economy by providing on-demand evasion capabilities through u…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Decoherence as Defence and the Magnitude of Noise Regularisation: A Rigorous N -Qubit Theory of Stochastic Quantum Neural Networks for Adversarially Robust Network Intrusion Detection

arXiv:2606.24219v1 Announce Type: cross Abstract: Stochastic quantum neural networks (SQNNs) encode neuronal activations as qubits, synaptic topology as entanglement, and neural noise through a Lindbl…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Kops: Safely Extending the eBPF Compilation Pipeline with Native Operations

arXiv:2606.24213v1 Announce Type: cross Abstract: eBPF safely extends OS kernels in domains such as networking, observability, and security. The safety comes from an in-kernel compilation pipeline whe…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
A Conditional Timing Protection Level: Holdover-Limited Undetected Time Error Under GNSS Spoofing

arXiv:2606.24210v1 Announce Type: cross Abstract: A GNSS timing receiver under spoofing has no nominal-geometry fault for position-domain RAIM to bound: the threat is a slow, common-mode pull of serve…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Cyclic Denoising Reveals Ultrastable Memories in Diffusion Models

arXiv:2606.24000v1 Announce Type: cross Abstract: We introduce cyclic denoising -- repeated forward and reverse diffusion at controlled noise amplitudes -- as an extraction attack for image diffusion …

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
The Serialized Bridge: Understanding and Recovering LLM Serving Performance under Blackwell GPU Confidential Computing

arXiv:2606.23969v1 Announce Type: cross Abstract: GPU Confidential Computing (GPU-CC) now preserves GPU-local performance: on NVIDIA B300, BF16 matmul runs at 0.998x of non-confidential performance. Y…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Are Safety Guarantees in Neural Networks Safe? How to Compute Trustworthy Robustness Certifications

arXiv:2606.23858v1 Announce Type: cross Abstract: A primary challenge in AI safety is the existence of adversarial examples -- slightly distorted inputs that cause a neural network (NN) to misclassify…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
HelpBench: Assessing the Ability of LLMs to Provide Privacy, Safety, and Security Advice

arXiv:2606.24819v1 Announce Type: new Abstract: This paper introduces HelpBench, a benchmark for assessing whether LLMs are capable of providing accurate help in response to questions about digital pr…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Burnyard: Future of Malware Analysis

arXiv:2606.24778v1 Announce Type: new Abstract: Malware analysis is a critical aspect of modern cybersecurity. The prevailing industry practice, sandboxing, involves executing suspicious binaries with…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
PowerFuzz: Power-Based Black-Box Firmware Fuzzing

arXiv:2606.24692v1 Announce Type: new Abstract: Fuzzing is widely used for software and hardware verification, offering an effective alternative to random testing. While gray-box fuzzers benefit from …

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
FirmCure:Towards Autonomous and Adaptive Rehosting of Linux-Based Firmware

arXiv:2606.24549v1 Announce Type: new Abstract: Full-system rehosting plays a critical role in the security analysis of Linux-based firmware. It matches commonly deployed firmware with sufficient back…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Red-Teaming the Agentic Red-Team

arXiv:2606.24496v1 Announce Type: new Abstract: The use of agentic systems to perform offensive security operations has moved from a theoretical possibility to a commoditized capability. However, whil…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
A Comparison of Kubernetes Compliance Standards and Configuration Scanners

arXiv:2606.24438v1 Announce Type: new Abstract: Kubernetes has become the industry standard for orchestrating containers in microservice-based software architectures. While several hardening guideline…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Poisoned Playbooks: Demystifying Knowledge Poisoning Effects on AI Security Agents

arXiv:2606.24402v1 Announce Type: new Abstract: AI security agents increasingly rely on Retrieval-Augmented Generation (RAG) to use external security knowledge for vulnerability analysis and exploit r…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
ComputeFHE: A Privacy-Preserving General-Purpose Computation Library

arXiv:2606.24379v1 Announce Type: new Abstract: Fully Homomorphic Encryption (FHE) enables computations to be performed directly on encrypted data while preserving data confidentiality. However, its p…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Securing LLM-Agent Long-Term Memory Against Poisoning: Non-Malleable, Origin-Bound Authority with Machine-Checked Guarantees

arXiv:2606.24322v1 Announce Type: new Abstract: LLM agents increasingly rely on persistent long-term memory, which creates a critical vulnerability that we study here: memory poisoning. An adversary c…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
CORE-BREW: LLR-Based Soft Decoding for Robust Multi-Bit LLM Watermarking

arXiv:2606.24163v1 Announce Type: new Abstract: Reliable provenance for LLM outputs requires multi-bit watermarks that remain robust under editing while maintaining strict false-positive control. Exis…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
DoHFuse: A Dual-Branch Architecture with DMAGLSTM for Website Fingerprinting over DNS over HTTPS/3

arXiv:2606.24105v1 Announce Type: new Abstract: As personal data privacy becomes increasingly critical in Internet of Things (IoT) environments, secure DNS protocols such as DNS over HTTPS (DoH) and D…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
PixJail: Self-Evolving Paper-to-Pipeline Reproduction for Text-to-Image Jailbreak Evaluation

arXiv:2606.24081v1 Announce Type: new Abstract: As Text-to-Image (T2I) jailbreak techniques evolve rapidly, existing benchmarks and reproduction workflows often struggle to keep pace. More importantly…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Maestro Order: A Model-Agnostic Orchestration Harness

arXiv:2606.23983v1 Announce Type: new Abstract: A single forward pass of a capable model is a fast, fluent, and unreliable problem-solver: it is right often enough to be useful and wrong often enough …

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
BipBipCache: Pipeline-Aware Integration of Low-Latency Tweakable Encryption in an Embedded Cache Controller

arXiv:2606.23941v1 Announce Type: new Abstract: Consumer and embedded processors store sensitive data in on-chip SRAM caches that remain readable after power loss or physical probing unless ciphertext…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
AutoPRAC: Automating Attack Discovery for PRAC-Based Rowhammer Defenses using Model Checkers

arXiv:2606.23905v1 Announce Type: new Abstract: Per-Row Activation Counting (PRAC) in DDR5 is a specification to mitigate Rowhammer attacks by tracking activations per row and triggering mitigative re…

arXiv Security Read →
◬ AI & Machine Learning Jun 24, 2026
Cryptographic certificates of validity for trustworthy AI

arXiv:2606.23768v1 Announce Type: new Abstract: We propose cryptographic certificates of validity for agentic AI systems. The core idea is to formally specify a correctness or policy condition as a lo…

arXiv Security Read →
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