Vulnerability in the Oracle EDI Gateway product of Oracle E-Business Suite (component: All Miscellaneous EDI Issues). Supported versions that are affected are 12.2.3-12.2.15. E...

CVE-2026-101532

Vulnerability in the Oracle EDI Gateway product of Oracle E-Business Suite (component: All Miscellaneous EDI Issues). S

历史摘要 · 未重新核验 · NVD

Vulnerability in the Oracle EDI Gateway product of Oracle E-Business Suite (component: All Miscellaneous EDI Issues). Supported versions that are affected are 12.2.3-12.2.15. E...

CVE-2026-101519

Vulnerability in the Oracle EDI Gateway product of Oracle E-Business Suite (component: All Miscellaneous EDI Issues). S

历史摘要 · 未重新核验 · NVD

Vulnerability in the Siebel CRM Deployment product of Oracle Siebel CRM (component: Cloud Gateway). Supported versions that are affected are 17.0-26.9. Easily exploitable vulne...

CVE-2026-101468

Vulnerability in the Siebel CRM Deployment product of Oracle Siebel CRM (component: Cloud Gateway). Supported versions

历史摘要 · 未重新核验 · NVD

Vulnerability in the Oracle EDI Gateway product of Oracle E-Business Suite (component: All Miscellaneous EDI Issues). Supported versions that are affected are 12.2.3-12.2.15. E...

CVE-2026-101466

Vulnerability in the Oracle EDI Gateway product of Oracle E-Business Suite (component: All Miscellaneous EDI Issues). S

历史摘要 · 未重新核验 · NVD

Acrobat for Edge is affected by an out-of-bounds write vulnerability that could result in arbitrary code execution in the context of the current user. Exploitation of this issue...

CVE-2026-100134

Acrobat for Edge is affected by an out-of-bounds write vulnerability that could result in arbitrary code execution in th

历史摘要 · 未重新核验 · NVD

MASAR: Multi-stage Attack Surface Analysis and Reasoning Framework for Telecom Networks

The increasing complexity of modern telecommunications networks introduces security challenges that require systematic t

历史摘要 · 未重新核验 · arXiv cs.CR

A Unified Evaluation Framework of Physical Adversarial Robustness in the Edge VLM Era

Recent advancements in Vision-Language Models (VLMs) enable end-to-end visual grounding via language prompts and generat

历史摘要 · 未重新核验 · arXiv cs.CR

Regular Syndrome Decoding Is Easier Than Previously Estimated

The Regular Syndrome Decoding (RSD) problem is a structured variant of classical Syndrome Decoding and underlies a growi

历史摘要 · 未重新核验 · arXiv cs.CR

Context-Aware Prompt Injection Detection via Small Language Models in RAG Pipelines: nokast-secureRAG

Local Retrieval-Augmented Generation (RAG) systems are vulnerable to indirect prompt injection and retrieval poisoning,

历史摘要 · 未重新核验 · arXiv cs.CR

Latency-Neutral Passive Cyber Monitoring for Grid-Edge Operational Technology Networks

Deterministic industrial networks often present an operational trade-off between maintaining microsecond timing of prima

历史摘要 · 未重新核验 · arXiv cs.CR

Testing TLS 1.3 PQC on constrained devices and microcontrollers

The UK, EU and US governments have set timelines for post-quantum cryptography migration of critical systems, with deadl

历史摘要 · 未重新核验 · arXiv cs.CR

Make the Adversary Spend More Energy: Generative Deception against Language-Model Attackers in Critical Infrastructure

Language-model attackers consume computational resources as they explore and interact with a target, creating an opportu

历史摘要 · 未重新核验 · arXiv cs.CR

Privacy Accounting for Empirical Denoisers

Diffusion models have emerged as the foundation of modern generative systems, yet their high memorization capacity raise

历史摘要 · 未重新核验 · arXiv cs.CR

Privacy-Preserving Personalized Federated Learning (PPP-FL) for Medical Imaging

Federated learning (FL) is a distributed machine learning paradigm that reduces transmission costs, mitigates cross-bord

历史摘要 · 未重新核验 · arXiv cs.CR

SRE: Accelerating Zero-Knowledge Proofs via Scalar Redundancy Elimination in Multi-Scalar Multiplication

Multi-Scalar Multiplication (MSM) is a fundamental cryptographic operation used in Elliptic Curve Cryptography (ECC) acr

历史摘要 · 未重新核验 · arXiv cs.CR

Interflow: Breaking the Offline-Online Barrier for Private AI at the Edge

Privacy-preserving machine learning (PPML) offers a promising path toward bringing powerful AI services to the edge with

历史摘要 · 未重新核验 · arXiv cs.CR

A Hybrid Information Flow Analysis Framework for Android Hybrid Apps

The WebView interface in Android (hybrid) applications enables the native side (e.g., Java) to exchange data with the We

历史摘要 · 未重新核验 · arXiv cs.CR

A Combined Streaming FPGA Architecture for Client-Side CKKS Encoding and Encryption

Homomorphic encryption allows a computing service to process encrypted data, but the client must first encode and encryp

历史摘要 · 未重新核验 · arXiv cs.CR

Model Exposure on One Device Endangers Others: Rethinking Edge Neural Network Security across Devices

Neural networks (NNs) are increasingly deployed on edge devices such as mobile and IoT platforms, offering low latency a

历史摘要 · 未重新核验 · arXiv cs.CR

Mind Your Boundaries: Boundary-Aware Model Obfuscation against Cross-node Attack

With the advancement of powerful AI chips, on-device machine learning is gaining traction for its low latency and privac

历史摘要 · 未重新核验 · arXiv cs.CR