Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection

With the rapid expansion of web-based applications and cloud services, malicious JavaScript code continues to pose significant threats to user privacy, system integrity, and enterprise security. But, detecting such threats remains challenging due to sophisticated code obfuscation techniques and...

GUARD-CAN: Graph-Understanding and Recurrent Architecture for CAN Anomaly Detection

Modern in-vehicle networks face various cyber threats due to the lack of encryption and authentication in the Controller Area Network CAN. To address this security issue, this paper presents GUARD-CAN, an anomaly detection framework that combines graph-based representation learning with time-seri...

Hierarchical Graph Neural Network for Compressed Speech Steganalysis

Steganalysis methods based on deep learning DL often struggle with computational complexity and challenges in generalizing across different datasets. Incorporating a graph neural network GNN into steganalysis schemes enables the leveraging of relational data for improved detection accuracy and...

Benchmarking Fraud Detectors on Private Graph Data

We introduce the novel problem of benchmarking fraud detectors on private graph-structured data. Currently, many types of fraud are managed in part by automated detection algorithms that operate over graphs. We consider the scenario where a data holder wishes to outsource development of fraud...

CVE-2025-8279 Missing Authentication for Critical Function in GitLab Language Server

Insufficient input validation within GitLab Language Server 7.6.0 and later before 7.30.0 allows arbitrary GraphQL query execution...

CVE-2025-38468

In the Linux kernel, the following vulnerability has been resolved: net/sched: Return NULL when htblookupleaf encounters an empty rbtree htblookupleaf has a BUGON that can trigger with the following: tc qdisc del dev lo root tc qdisc add dev lo root handle 1: htb default 1 tc class add dev lo...

GitLab Language Server 访问控制错误漏洞

GitLab Language Server is a language server from GitLab USA. An access control error vulnerability exists in GitLab Language Server versions prior to 7.6.0 through 7.30.0 that stems from insufficient input validation and could lead to arbitrary GraphQL query execution...

JetBrains TeamCity 跨站请求伪造漏洞

JetBrains TeamCity is a set of distributed build management and continuous integration tools from the Czech company JetBrains. The tool provides features such as continuous unit testing, code quality analysis and build issue analysis reports. A cross-site request forgery vulnerability exists in...

PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python

Python software development heavily relies on third-party packages. Direct and transitive dependencies create a labyrinth of software supply chains. While it is convenient to reuse code, vulnerabilities within these dependency chains can propagate through dependencies, potentially affecting...

Learning-Based Privacy-Preserving Graph Publishing against Sensitive Link Inference Attacks

Publishing graph data is widely desired to enable a variety of structural analyses and downstream tasks. However, it also potentially poses severe privacy leakage, as attackers may leverage the released graph data to launch attacks and precisely infer private information such as the existence of...

Access of Resource Using Incompatible Type ('Type Confusion')

Overview org.webjars.npm:electron is a framework which lets you write cross-platform desktop applications using JavaScript, HTML and CSS. Affected versions of this package are vulnerable to Access of Resource Using Incompatible Type 'Type Confusion' via the lack of limitation on max inlining ids ...

Malware in nf-graph-examples

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outsid...

Malicious code in nf-graph-examples (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 68c85cb3b4e04f7e1368dde1be75808c76da67cc6c23f52ed008ac697722496a Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

MAL-2025-6187 Malicious code in nf-graph-examples (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 68c85cb3b4e04f7e1368dde1be75808c76da67cc6c23f52ed008ac697722496a Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Explainable Vulnerability Detection in C/C++ Using Edge-Aware Graph Attention Networks

Detecting security vulnerabilities in source code remains challenging, particularly due to class imbalance in real-world datasets where vulnerable functions are under-represented. Existing learning-based methods often optimise for recall, leading to high false positive rates and reduced usability...

SUSE-SU-2025:20483-1 Security update for the Linux Kernel

The SUSE Linux Enterprise Micro 6.0 and 6.1 RT kernel was updated to receive various security bugfixes. The following security bugs were fixed: - CVE-2024-57982: xfrm: state: fix out-of-bounds read during lookup bsc1237913. - CVE-2024-58053: rxrpc: Fix handling of received connection abort...

Architectural Backdoors in Deep Learning: a Survey of Vulnerabilities, Detection, and Defense

Architectural backdoors pose an under-examined but critical threat to deep neural networks, embedding malicious logic directly into a model's computational graph. Unlike traditional data poisoning or parameter manipulation, architectural backdoors evade standard mitigation techniques and persist...

REAL-IoT: Characterizing GNN Intrusion Detection Robustness under Practical Adversarial Attack

Graph Neural Network GNN-based network intrusion detection systems NIDS are often evaluated on single datasets, limiting their ability to generalize under distribution drift. Furthermore, their adversarial robustness is typically assessed using synthetic perturbations that lack realism. This...

Crypto-Assisted Graph Degree Sequence Release under Local Differential Privacy

Whitepaper called Crypto-Assisted Graph Degree Sequence Release Under Local Differential Privacy...

CAN-Trace Attack: Exploit CAN Messages to Uncover Driving Trajectories

Driving trajectory data remains vulnerable to privacy breaches despite existing mitigation measures. Traditional methods for detecting driving trajectories typically rely on map-matching the path using Global Positioning System GPS data, which is susceptible to GPS data outage. This paper...