Detecting Quishing Attacks with Machine Learning Techniques through QR Code Analysis

The rise of QR code based phishing "Quishing" poses a growing cybersecurity threat, as attackers increasingly exploit QR codes to bypass traditional phishing defenses. Existing detection methods predominantly focus on URL analysis, which requires the extraction of the QR code payload, and may...

Understanding Zero Touch Certificate Management (ZTCM) in Citrix NetScaler

Summary: This article addresses frequently asked questions regarding the behavior of Zero Touch Certificate Management ZTCM in Citrix NetScaler, including how it handles certificate synchronization, SNI-based certificate selection, and coexistence with legacy configurations...

Secure Cluster-Based Hierarchical Federated Learning in Vehicular Networks

Hierarchical Federated Learning HFL has recently emerged as a promising solution for intelligent decision-making in vehicular networks, helping to address challenges such as limited communication resources, high vehicle mobility, and data heterogeneity. However, HFL remains vulnerable to...

CISA: Dams Sector Waterside Barriers Guide

This guide was developed to assist dam owners and operators in understanding the possible need for waterside barriers as part of their overall security plan. It provides them and security personnel with a cursory level of information on barriers and their use, maintenance considerations, and...

Bookgy SQL注入漏洞

Bookgy is an online reservation management and booking system for all types of small and medium-sized businesses from Bookgy, Inc. Bookgy has an SQL injection vulnerability that originates from SQL injection of the IDTIPO, IDPISTA, and IDSOCIO parameters in the /bkgseleccionarhoraajax.php file...

Stegano 1.0.0

Stegano is a basic Python Steganography module. Stegano implements two methods of hiding: using the red portion of a pixel to hide ASCII messages, and using the Least Significant Bit LSB technique. It is possible to use a more advanced LSB method based on integers sets. The sets Sieve of...

Optimized Approaches to Malware Detection: a Study of Machine Learning and Deep Learning Techniques

Digital systems find it challenging to keep up with cybersecurity threats. The daily emergence of more than 560,000 new malware strains poses significant hazards to the digital ecosystem. The traditional malware detection methods fail to operate properly and yield high false positive rates with l...

Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations

This paper explores the vulnerability of machine learning models to simple single-feature adversarial attacks in the context of Ethereum fraudulent transaction detection. Through comprehensive experimentation, we investigate the impact of various adversarial attack strategies on model performance...

Feature Selection Via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation

Distributed Denial of Service DDoS attacks represent a persistent and evolving threat to modern networked systems, capable of causing large-scale service disruptions. The complexity of such attacks, often hidden within high-dimensional and redundant network traffic data, necessitates robust and...

Benchmarking Differentially Private Tabular Data Synthesis

Differentially private DP tabular data synthesis generates artificial data that preserves the statistical properties of private data while safeguarding individual privacy. The emergence of diverse algorithms in recent years has introduced challenges in practical applications, such as inconsistent...

DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-Based Intrusion Detection against Adversarial Attacks

The rapid proliferation of the Internet of Things IoT has introduced substantial security vulnerabilities, highlighting the need for robust Intrusion Detection Systems IDS. Machine learning-based intrusion detection systems ML-IDS have significantly improved threat detection capabilities; however...

Security update for rubygem-bundler

This update for rubygem-bundler fixes the following issues: CVE-2020-36327: Fixed bundler choosing a dependency source based on the highest gem version number, which means that a rogue gem found at a public source may be chosen bsc1185842 Other fixes: - Updated to version 2.2.34 Patch...

Prompt Engineering Techniques with Spring AI

This blog post demonstrates practical implementations of Prompt Engineering techniques using Spring AI. The examples and patterns in this article are based on the comprehensive Prompt Engineering Guide that covers the theory, principles, and patterns of effective prompt engineering. The blog show...

BIT-JOOMLA-2024-21724 [20240203] - Core - XSS in media selection fields

Inadequate input validation for media selection fields lead to XSS vulnerabilities in various extensions...

CVE-2025-31464

Improper Neutralization of Input During Web Page Generation 'Cross-site Scripting' vulnerability in Nazmur Rahman Text Selection Color text-selection-color allows Stored XSS.This issue affects Text Selection Color: from n/a through = 1.6...

WordPress Text Selection Color plugin <= 1.6 - Cross Site Scripting (XSS) Vulnerability

Cross Site Scripting XSS Vulnerability discovered by Nabil Irawan in WordPress Plugin Text Selection Color versions = 1.6...

CVE-2025-31464

Improper Neutralization of Input During Web Page Generation 'Cross-site Scripting' vulnerability in Nazmur Rahman Text Selection Color text-selection-color allows Stored XSS.This issue affects Text Selection Color: from n/a through = 1.6...

CVE-2025-31464 WordPress Text Selection Color <= 1.6 - Cross Site Scripting (XSS) Vulnerability

Improper Neutralization of Input During Web Page Generation 'Cross-site Scripting' vulnerability in Nazmur Rahman Text Selection Color allows Stored XSS. This issue affects Text Selection Color: from n/a through 1.6...

CVE-2025-31464 WordPress Text Selection Color plugin <= 1.6 - Cross Site Scripting (XSS) Vulnerability

Improper Neutralization of Input During Web Page Generation 'Cross-site Scripting' vulnerability in Nazmur Rahman Text Selection Color text-selection-color allows Stored XSS.This issue affects Text Selection Color: from n/a through = 1.6...

CVE-2025-31464

CVE-2025-31464 affects Text Selection Color (WordPress) up to version 1.6. It is a Stored Cross-Site Scripting vulnerability caused by improper neutralization of input during web page generation. The issue requires an authenticated administrator to exploit. Public fixes/patch version are not desc...