Path Traversal via Unsanitized Version String in Versioned Dataset Loading

This report is not public...

CVE-2026-25887

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

Reality Check for Tor Website Fingerprinting in the Open World

Website fingerprinting WF attacks on Tor can infer user destinations from encrypted traffic metadata. However, their real-world effectiveness remains debated due to laboratory settings that fail to capture network fluctuations, evaluate noise, and create a representative open world. In this work,...

CVE-2026-25887

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

EUVD-2026-9976

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

CVE-2026-25887

Chartbrew is affected prior to version 4.8.1 with a remote code execution vulnerability via the MongoDB dataset Query. The issue, classified as CVSS 3.1 Base Score 7.2 (HIGH), has been patched in version 4.8.1. Affected: Chartbrew

CVE-2026-25887 Chartbrew: Remote Code Execution (RCE) via MongoDB Dataset Query

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

CVE-2026-25887 Chartbrew: Remote Code Execution (RCE) via MongoDB Dataset Query

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

CVE-2026-25887 Chartbrew: Remote Code Execution (RCE) via MongoDB Dataset Query

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

PT-2026-23636

Name of the Vulnerable Software and Affected Versions Chartbrew versions prior to 4.8.1 Description Chartbrew is a web application that connects to databases and APIs to create charts. Versions of the software prior to 4.8.1 contain a remote code execution issue stemming from the MongoDB dataset...

chartbrew 代码注入漏洞

Chartbrew is an open-source data visualization and dashboard building tool developed by Chartbrew. Versions of Chartbrew prior to 4.8.1 contained a code injection vulnerability, which was caused by remote code execution vulnerabilities in MongoDB dataset queries...

Before You Hand over the Wheel: Evaluating LLMs for Security Incident Analysis

Security incident analysis SIA poses a major challenge for security operations centers, which must manage overwhelming alert volumes, large and diverse data sources, complex toolchains, and limited analyst expertise. These difficulties intensify because incidents evolve dynamically and require...

CVE-2026-25887: Improper Control of Generation of Code

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. Prior to version 4.8.1, there is a remote code execution vulnerability via the MongoDB dataset Query. This issue has been patched in version 4.8.1...

SecureRAG-RTL: A Retrieval-Augmented, Multi-Agent, Zero-Shot LLM-Driven Framework for Hardware Vulnerability Detection

Large language models LLMs have shown remarkable capabilities in natural language processing tasks, yet their application in hardware security verification remains limited due to scarcity of publicly available hardware description language HDL datasets. This knowledge gap constrains LLM performan...

Integer Overflow Bypasses Memory Safety Checks in H5 Dataset Loading

This report is not public...

DKD-KAN: A Lightweight Knowledge-Distilled KAN Intrusion Detection Framework, Based on MLP and KAN

Cyber-security systems often operate in resource-constrained environments, such as edge environments and real-time monitoring systems, where model size and inference time are crucial. A light-weight intrusion detection framework is proposed that utilizes the Kolmogorov-Arnold Network KAN to captu...

Multi-Agent Honeypot-Based Request-Response Context Dataset for Improved SQL Injection Detection Performance

SQL injection remains a major threat to web applications, as existing defenses often fail against obfuscation and evolving attacks because of neglecting the request-response context. This paper presents a context-enriched SQL injection detection framework, focusing on constructing a high-quality...

Gravity Falls: A Comparative Analysis of Domain-Generation Algorithm (DGA) Detection Methods for Mobile Device Spearphishing

Mobile devices are frequent targets of eCrime threat actors through SMS spearphishing smishing links that leverage Domain Generation Algorithms DGA to rotate hostile infrastructure. Despite this, DGA research and evaluation largely emphasize malware C2 and email phishing datasets, leaving limited...

Internet Malware Propagation: Dynamics and Control through SEIRV Epidemic Model with Relapse and Intervention

Malware attacks in today's vast digital ecosystem pose a serious threat. Understanding malware propagation dynamics and designing effective control strategies are therefore essential. In this work, we propose a generic SEIRV model formulated using ordinary differential equations to study malware...

How the Graph Construction Technique Shapes Performance in IoT Botnet Detection

The increasing incidence of IoT-based botnet attacks has driven interest in advanced learning models for detection. Recent efforts have focused on leveraging attention mechanisms to model long-range feature dependencies and Graph Neural Networks GNNs to capture relationships between data instance...