3137 matches found
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...
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,...
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...
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...
Generative AI for Critical Infrastructure in Smart Grids: a Unified Framework for Synthetic Data Generation and Anomaly Detection
In digital substations, security events pose significant challenges to the sustained operation of power systems. To mitigate these challenges, the implementation of robust defense strategies is critically important. A thorough process of anomaly identification and detection in information and...
Security Bulletin: Multiple vulnerabilities in IBM Business Automation Workflow Machine Learning Server are addressed with 24.0.0-IF006
Summary In addition to updates to operating system level packages, IBM Business Automation Workflow Machine Learning Server 24.0.0-IF006 addresses the following vulnerabilities. Vulnerability Details CVEID:CVE-2024-47081 DESCRIPTION: Requests is a HTTP library. Due to a URL parsing issue, Request...
Measuring the Carbon Footprint of Cryptographic Privacy-Enhancing Technologies
Privacy-enhancing technologies PETs have attracted significant attention in response to privacy regulations, driving the development of applications that prioritize user data protection. At the same time, the information and communication technology ICT sector faces growing pressure to reduce its...
Leveraging Machine Learning for Botnet Attack Detection in Edge-Computing Assisted IoT Networks
The increase of IoT devices, driven by advancements in hardware technologies, has led to widespread deployment in large-scale networks that process massive amounts of data daily. However, the reliance on Edge Computing to manage these devices has introduced significant security vulnerabilities, a...
CVE-2025-54430
dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on structured data. Before commit 3f61e79, a critical severity vulnerability has been identified within the .github/workflows/benchmark-bot.yml workflow, where a issuecomme...
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
Despite outstanding results, machine learning-based Android malware detection models struggle with concept drift, where rapidly evolving malware characteristics degrade model effectiveness. This study examines the impact of concept drift on Android malware detection, evaluating two datasets and...
PT-2025-31382 · Dedupe · Dedupe
Name of the Vulnerable Software and Affected Versions: dedupe versions prior to commit 3f61e79 Description: dedupe is a Python library used for fuzzy matching, deduplication, and entity resolution on structured data. A critical severity issue exists in the .github/workflows/benchmark-bot.yml...
BentoML SSRF Vulnerability in File Upload Processing
Description There's an SSRF in the file upload processing system that allows remote attackers to make arbitrary HTTP requests from the server without authentication. The vulnerability exists in the serialization/deserialization handlers for multipart form data and JSON requests, which automatical...
Programmable Data Planes for Network Security
The emergence of programmable data planes, and particularly switches supporting the P4 language, has transformed network security by enabling customized, line-rate packet processing. These switches, originally intended for flexible forwarding, now play a broader role: detecting and mitigating...
The vulnerability of the gateway_proxy_handler component in the machine learning lifecycle management platform allows a attacker to compromise the confidentiality, integrity, and accessibility of the protected information.
The vulnerability of the gatewayproxyhandler component in the Machine Learning Lifecycle Management platform is related to insufficient validation of requests at the server side. Exploiting this vulnerability could allow an attacker to compromise the confidentiality, integrity, and accessibility ...
GyoiThon
This is an offensive tool for penetration testing using machine learning. It is called GyoiThon. The tool is designed to perform penetration testing using machine learning algorithms and can be used to identify vulnerabilities in web applications and services. The tool uses a variety of technique...
Microsoft Azure Machine Learning Elevation of Privilege Vulnerability
Microsoft Azure Machine Learning is a machine learning services platform from Microsoft USA. Microsoft Azure Machine Learning has a security vulnerability that can be exploited by an attacker to potentially cause elevation of privilege...
Microsoft Azure Machine Learning elevation of privilege vulnerability (CNVD-2025-17136)
Microsoft Azure Machine Learning is a machine learning services platform from Microsoft USA. Microsoft Azure Machine Learning has a security vulnerability that can be exploited by an attacker to potentially cause elevation of privilege...
Microsoft Azure Machine Learning elevation of privilege vulnerability (CNVD-2025-17135)
Microsoft Azure Machine Learning is a machine learning services platform from Microsoft USA. Microsoft Azure Machine Learning has a security vulnerability that can be exploited by an attacker to potentially cause elevation of privilege...
Leveraging Trustworthy AI for Automotive Security in Multi-Domain Operations: Towards a Responsive Human-AI Multi-Domain Task Force for Cyber Social Security
Multi-Domain Operations MDOs emphasize cross-domain defense against complex and synergistic threats, with civilian infrastructures like smart cities and Connected Autonomous Vehicles CAVs emerging as primary targets. As dual-use assets, CAVs are vulnerable to Multi-Surface Threats MSTs,...
