CVE-2025-20367 Reflected Cross-site Scripting (XSS) in '/app/search/table' endpoint through the 'dataset.command' parameter on Splunk Enterprise

In Splunk Enterprise versions below 9.4.4, 9.3.6 and 9.2.8, and Splunk Cloud Platform versions below 9.3.2411.109, 9.3.2408.119 and 9.2.2406.122, a low-privileged user that does not hold the 'admin' or 'power' Splunk roles could craft a malicious payload through the dataset.command parameter of t...

CVE-2025-20367 Reflected Cross-site Scripting (XSS) in '/app/search/table' endpoint through the 'dataset.command' parameter on Splunk Enterprise

In Splunk Enterprise versions below 9.4.4, 9.3.6 and 9.2.8, and Splunk Cloud Platform versions below 9.3.2411.109, 9.3.2408.119 and 9.2.2406.122, a low-privileged user that does not hold the 'admin' or 'power' Splunk roles could craft a malicious payload through the dataset.command parameter of t...

CVE-2025-20367

Affected software: Splunk Enterprise (versions below 9.4.4, 9.3.6, 9.2.8) and Splunk Cloud Platform (below 9.3.2411.109, 9.3.2408.119, 9.2.2406.122). Vulnerability: a low-privileged user can craft a malicious payload via the dataset.command parameter of the /app/search/table endpoint, resulting i...

Splunk Cloud Platform和Splunk Enterprise 跨站脚本漏洞

Splunk Cloud Platform and Splunk Enterprise are both products of Splunk Corporation, U.S.A. Splunk Cloud Platform is a powerful data collection, processing, and analytics service.Splunk Enterprise is a suite of data collection and analytics software. A cross-site scripting vulnerability exists in...

PT-2025-40270

Name of the Vulnerable Software and Affected Versions Splunk Enterprise versions prior to 9.4.4 Splunk Enterprise versions prior to 9.3.6 Splunk Enterprise versions prior to 9.2.8 Splunk Cloud Platform versions prior to 9.3.2411.109 Splunk Cloud Platform versions prior to 9.3.2408.119 Splunk Clou...

ICS-SimLab: A Containerized Approach for Simulating Industrial Control Systems for Cyber Security Research

Industrial Control Systems ICSs are complex interconnected systems used to manage process control within industrial environments, such as chemical processing plants and water treatment facilities. As the modern industrial environment moves towards Internet-facing services, ICSs face an increased...

The Impact of Audio Watermarking on Audio Anti-Spoofing Countermeasures

This paper presents the first study on the impact of audio watermarking on spoofing countermeasures. While anti-spoofing systems are essential for securing speech-based applications, the influence of widely used audio watermarking, originally designed for copyright protection, remains largely...

Vision Transformers: the Threat of Realistic Adversarial Patches

The increasing reliance on machine learning systems has made their security a critical concern. Evasion attacks enable adversaries to manipulate the decision-making processes of AI systems, potentially causing security breaches or misclassification of targets. Vision Transformers ViTs have gained...

AEAS: Actionable Exploit Assessment System

Security practitioners face growing challenges in exploit assessment, as public vulnerability repositories are increasingly populated with inconsistent and low-quality exploit artifacts. Existing scoring systems, such as CVSS and EPSS, offer limited support for this task. They either rely on...

LLaVul: a Multimodal LLM for Interpretable Vulnerability Reasoning about Source Code

Increasing complexity in software systems places a growing demand on reasoning tools that unlock vulnerabilities manifest in source code. Many current approaches focus on vulnerability analysis as a classifying task, oversimplifying the nuanced and context-dependent real-world scenarios. Even...

CVE-2024-43745

creationtimestamp| type| source ---|---|--- 2025-09-16 23:16:38+00:00| seen| MISP/be792712-f638-4d7d-b62d-4f5032e86764 2025-09-18 16:44:33+00:00| seen| MISP/be792712-f638-4d7d-b62d-4f5032e86764...

ExploitRemotingService

This is a .NET Remoting Service exploit tool. It is a proof-of-concept PoC exploit for a vulnerability in the .NET Remoting Service. The tool is designed to demonstrate the exploitation of this vulnerability, which allows an attacker to execute arbitrary code on a remote system. The tool consists...

DMLDroid: Deep Multimodal Fusion Framework for Android Malware Detection with Resilience to Code Obfuscation and Adversarial Perturbations

In recent years, learning-based Android malware detection has seen significant advancements, with detectors generally falling into three categories: string-based, image-based, and graph-based approaches. While these methods have shown strong detection performance, they often struggle to sustain...

Bridging the Gap in Phishing Detection: a Comprehensive Phishing Dataset Collector

To combat phishing attacks -- aimed at luring web users to divulge their sensitive information -- various phishing detection approaches have been proposed. As attackers focus on devising new tactics to bypass existing detection solutions, researchers have adapted by integrating machine learning a...

Fraud Detection and Risk Assessment of Online Payment Transactions on E-Commerce Platforms Based on LLM and GCN Frameworks

With the rapid growth of e-commerce, online payment fraud has become increasingly complex, posing serious threats to financial security and consumer trust. Traditional detection methods often struggle to capture the intricate relational structures inherent in transactional data. This study presen...

PARROT: Portable Android Reproducible Traffic Observation Tool

The rapid evolution of mobile security protocols and limited availability of current datasets constrains research in app traffic analysis. This paper presents PARROT, a reproducible and portable traffic capture system for systematic app traffic collection using Android Virtual Devices. The system...

Phish-Blitz: Advancing Phishing Detection with Comprehensive Webpage Resource Collection and Visual Integrity Preservation

Phishing attacks are increasingly prevalent, with adversaries creating deceptive webpages to steal sensitive information. Despite advancements in machine learning and deep learning for phishing detection, attackers constantly develop new tactics to bypass detection models. As a result, phishing...

Backdoor Attacks and Defenses in Computer Vision Domain: a Survey

Backdoor trojan attacks embed hidden, controllable behaviors into machine-learning models so that models behave normally on benign inputs but produce attacker-chosen outputs when a trigger is present. This survey reviews the rapidly growing literature on backdoor attacks and defenses in the...

PatchSeeker: Mapping NVD Records to Their Vulnerability-Fixing Commits with LLM Generated Commits and Embeddings

Software vulnerabilities pose serious risks to modern software ecosystems. While the National Vulnerability Database NVD is the authoritative source for cataloging these vulnerabilities, it often lacks explicit links to the corresponding Vulnerability-Fixing Commits VFCs. VFCs encode precise code...

Contrastive Self-Supervised Network Intrusion Detection Using Augmented Negative Pairs

Network intrusion detection remains a critical challenge in cybersecurity. While supervised machine learning models achieve state-of-the-art performance, their reliance on large labelled datasets makes them impractical for many real-world applications. Anomaly detection methods, which train...