CVE-2025-54699 WordPress Masteriyo - LMS Plugin plugin <= 1.18.3 - Cross Site Scripting (XSS) Vulnerability

Improper Neutralization of Input During Web Page Generation 'Cross-site Scripting' vulnerability in masteriyo Masteriyo - LMS allows Stored XSS. This issue affects Masteriyo - LMS: from n/a through 1.18.3...

CVE-2025-54699

CVE-2025-54699 is an XSS vulnerability in Masteriyo LMS Plugin for WordPress, caused by improper input neutralization during web page generation and enabling stored XSS on pages served to users. Affected range: Masteriyo LMS up to version 1.18.3 (inclusive). Exploitation details are not provided ...

A Hierarchical IDS for Zero-Day Attack Detection in Internet of Medical Things Networks

The Internet of Medical Things IoMT is driving a healthcare revolution but remains vulnerable to cyberattacks such as denial of service, ransomware, data hijacking, and spoofing. These networks comprise resource constrained, heterogeneous devices e.g., wearable sensors, smart pills, implantables,...

MirGuard: Towards a Robust Provenance-Based Intrusion Detection System against Graph Manipulation Attacks

Learning-based Provenance-based Intrusion Detection Systems PIDSes have become essential tools for anomaly detection in host systems due to their ability to capture rich contextual and structural information, as well as their potential to detect unknown attacks. However, recent studies have shown...

REFN: a Reinforcement-Learning-From-Network Framework against 1-Day/N-Day Exploitations

The exploitation of 1 day or n day vulnerabilities poses severe threats to networked devices due to massive deployment scales and delayed patching average Mean Time To Patch exceeds 60 days. Existing defenses, including host based patching and network based filtering, are inadequate due to limite...

Code Vulnerability Detection across Different Programming Languages with AI Models

Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do not work well at detecting the context-dependent bugs and...

PT-2025-33251 · Unknown · Masteriyo - Lms

Name of the Vulnerable Software and Affected Versions: Masteriyo - LMS versions through 1.18.3 Description: The software contains a Stored Cross-Site Scripting XSS flaw due to improper neutralization of input during web page generation. This allows for the injection of malicious scripts into web...

Enhancing GraphQL Security by Detecting Malicious Queries Using Large Language Models, Sentence Transformers, and Convolutional Neural Networks

GraphQL's flexibility, while beneficial for efficient data fetching, introduces unique security vulnerabilities that traditional API security mechanisms often fail to address. Malicious GraphQL queries can exploit the language's dynamic nature, leading to denial-of-service attacks, data...

CVE-2025-6184 Tutor LMS Pro – eLearning and online course solution <= 3.7.0 - Authenticated (Tutor Instructor+) SQL Injection

The Tutor LMS Pro – eLearning and online course solution plugin for WordPress is vulnerable to time-based SQL Injection via the ‘order’ parameter used in the getsubmittedassignments function in all versions up to, and including, 3.7.0 due to insufficient escaping on the user supplied parameter an...

Demystifying the Role of Rule-Based Detection in AI Systems for Windows Malware Detection

Malware detection increasingly relies on AI systems that integrate signature-based detection with machine learning. However, these components are typically developed and combined in isolation, missing opportunities to reduce data complexity and strengthen defenses against adversarial EXEmples,...

Explainable Ensemble Learning for Graph-Based Malware Detection

Malware detection in modern computing environments demands models that are not only accurate but also interpretable and robust to evasive techniques. Graph neural networks GNNs have shown promise in this domain by modeling rich structural dependencies in graph-based program representations such a...

WordPress Tutor LMS Pro plugin <= 3.7.0 - Authenticated (Tutor Instructor+) SQL Injection vulnerability

Authenticated Tutor Instructor+ SQL Injection vulnerability discovered by sergioframi in WordPress Plugin Tutor LMS Pro versions = 3.7.0...

Exploring Cross-Stage Adversarial Transferability in Class-Incremental Continual Learning

Class-incremental continual learning addresses catastrophic forgetting by enabling classification models to preserve knowledge of previously learned classes while acquiring new ones. However, the vulnerability of the models against adversarial attacks during this process has not been investigated...

Enhance the Machine Learning Algorithm Performance in Phishing Detection with Keyword Features

Recently, we can observe a significant increase of the phishing attacks in the Internet. In a typical phishing attack, the attacker sets up a malicious website that looks similar to the legitimate website in order to obtain the end-users' information. This may cause the leakage of the sensitive...

Developing a Transferable Federated Network Intrusion Detection System

Intrusion Detection Systems IDS are a vital part of a network-connected device. In this paper, we develop a deep learning based intrusion detection system that is deployed in a distributed setup across devices connected to a network. Our aim is to better equip deep learning models against unknown...

FetFIDS: a Feature Embedding Attention Based Federated Network Intrusion Detection Algorithm

Intrusion Detection Systems IDS have an increasingly important role in preventing exploitation of network vulnerabilities by malicious actors. Recent deep learning based developments have resulted in significant improvements in the performance of IDS systems. In this paper, we present FetFIDS,...

Attacks and Defenses against LLM Fingerprinting

As large language models are increasingly deployed in sensitive environments, fingerprinting attacks pose significant privacy and security risks. We present a study of LLM fingerprinting from both offensive and defensive perspectives. Our attack methodology uses reinforcement learning to...

INE Named to Training Industry’s 2025 Top 20 Online Learning Library List

Cary, United States, 11th August 2025, CyberNewsWire...

Designing with Deception: ML- and Covert Gate-Enhanced Camouflaging to Thwart IC Reverse Engineering

Integrated circuits ICs are essential to modern electronic systems, yet they face significant risks from physical reverse engineering RE attacks that compromise intellectual property IP and overall system security. While IC camouflage techniques have emerged to mitigate these risks, existing...

BlindGuard: Safeguarding LLM-Based Multi-Agent Systems under Unknown Attacks

The security of LLM-based multi-agent systems MAS is critically threatened by propagation vulnerability, where malicious agents can distort collective decision-making through inter-agent message interactions. While existing supervised defense methods demonstrate promising performance, they may be...