PT-2025-27016 · Microsoft · Edge

Name of the Vulnerable Software and Affected Versions: Microsoft Edge Chromium-based affected versions not specified Description: The issue is related to improper input validation, allowing an authorized attacker to bypass a security feature locally. This is a security-feature bypass vulnerabilit...

Microsoft Edge (Chromium) < 138.0.3351.55 Multiple Vulnerabilities

The version of Microsoft Edge installed on the remote Windows host is prior to 138.0.3351.55. It is, therefore, affected by multiple vulnerabilities as referenced in the June 26, 2025 advisory. - Insufficient data validation in DevTools in Google Chrome on Windows prior to 138.0.7204.49 allowed a...

PT-2025-27017 · Microsoft · Edge

Name of the Vulnerable Software and Affected Versions: Microsoft Edge Chromium-based affected versions not specified Description: A spoofing issue allows unauthorized attackers to perform spoofing over a network, potentially affecting the system. Recommendations: At the moment, there is no...

Microsoft Edge 安全漏洞

Microsoft Edge is a web browser from the American company Microsoft that comes with systems after Windows 10. A spoofing vulnerability exists in Microsoft Edge Chromium-based, which can be exploited by attackers to perform spoofing attacks...

PT-2025-27018 · Microsoft · Edge

Name of the Vulnerable Software and Affected Versions: Microsoft Edge Chromium-based affected versions not specified Description: A spoofing issue allows attackers to affect the system. Recommendations: At the moment, there is no information about a newer version that contains a fix for this...

Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions

The rapid advancement of 6G wireless networks, IoT, and edge computing has significantly expanded the cyberattack surface, necessitating more intelligent and adaptive vulnerability detection mechanisms. Traditional security methods, while foundational, struggle with zero-day exploits, adversarial...

E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification Via MLLMs

The rapid spread of misinformation in mobile and wireless networks presents critical security challenges. This study introduces a training-free, retrieval-based multimodal fact verification system that leverages pretrained vision-language models and large language models for credibility assessmen...

Verifiable Unlearning on Edge

Machine learning providers commonly distribute global models to edge devices, which subsequently personalize these models using local data. However, issues such as copyright infringements, biases, or regulatory requirements may require the verifiable removal of certain data samples across all edg...

Intelligent ARP Spoofing Detection Using Multi-Layered Machine Learning (ML) Techniques for IoT Networks

Address Resolution Protocol ARP spoofing remains a critical threat to IoT networks, enabling attackers to intercept, modify, or disrupt data transmission by exploiting ARP's lack of authentication. The decentralized and resource-constrained nature of IoT environments amplifies this vulnerability,...

Microsoft Edge (Chromium-Based) < 137.0.3296.93 Multiple Vulnerabilities (Jun 2025)

Microsoft Edge Chromium-Based is prone to multiple vulnerabilities. SPDX-FileCopyrightText: 2025 Greenbone AG Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-only CPE =...

KCES: Training-Free Defense for Robust Graph Neural Networks Via Kernel Complexity

Graph Neural Networks GNNs have achieved impressive success across a wide range of graph-based tasks, yet they remain highly vulnerable to small, imperceptible perturbations and adversarial attacks. Although numerous defense methods have been proposed to address these vulnerabilities, many rely o...

Real-Time Agile Software Management for Edge and Fog Computing Based Smart City Infrastructure

The evolution of smart cities demands scalable, secure, and energy-efficient architectures for real-time data processing. With the number of IoT devices expected to exceed 40 billion by 2030, traditional cloud-based systems are increasingly constrained by bandwidth, latency, and energy limitation...

Federated Learning-Based Data Collaboration Method for Enhancing Edge Cloud AI System Security Using Large Language Models

With the widespread application of edge computing and cloud systems in AI-driven applications, how to maintain efficient performance while ensuring data privacy has become an urgent security issue. This paper proposes a federated learning-based data collaboration method to improve the security of...

Real-Time, Low-Latency Surveillance Using Entropy-Based Adaptive Buffering and MobileNetV2 on Edge Devices

This paper describes a high-performance, low-latency video surveillance system designed for resource-constrained environments. We have proposed a formal entropy-based adaptive frame buffering algorithm and integrated that with MobileNetV2 to achieve high throughput with low latency. The system is...

Toward a Lightweight, Scalable, and Parallel Secure Encryption Engine

The exponential growth of Internet of Things IoT applications has intensified the demand for efficient, high-throughput, and energy-efficient data processing at the edge. Conventional CPU-centric encryption methods suffer from performance bottlenecks and excessive data movement, especially in...

Optimizing System Latency for Blockchain-Encrypted Edge Computing in Internet of Vehicles

As Internet of Vehicles IoV technology continues to advance, edge computing has become an important tool for assisting vehicles in handling complex tasks. However, the process of offloading tasks to edge servers may expose vehicles to malicious external attacks, resulting in information loss or...

Secret Sharing in 5G-MEC: Applicability for Joint Security and Dependability

Multi-access Edge Computing MEC, an enhancement of 5G, processes data closer to its generation point, reducing latency and network load. However, the distributed and edge-based nature of 5G-MEC presents privacy and security challenges, including data exposure risks. Ensuring efficient manipulatio...

Chromium: CVE-2025-6192 Use after free in Profiler

This CVE was assigned by Chrome. Microsoft Edge Chromium-based ingests Chromium, which addresses this vulnerability. Please see Google Chrome Releases for more information...

Chromium: CVE-2025-6191 Integer overflow in V8

This CVE was assigned by Chrome. Microsoft Edge Chromium-based ingests Chromium, which addresses this vulnerability. Please see Google Chrome Releases for more information...

Security Bulletin: IBM Edge Data Collector is vulnerable to axios-1.7.7.tgz, axios-1.7.9.tgz CVE-2025-27152

Summary IBM Edge Data Collector is vulnerable to axios-1.7.7.tgz, axios-1.7.9.tgz CVE-2025-27152. This bulletin identifies the steps to take to address the vulnerabilities. Vulnerability Details CVEID:CVE-2025-27152 DESCRIPTION: axios is a promise based HTTP client for the browser and node.js. Th...