ProvX: Generating Counterfactual-Driven Attack Explanations for Provenance-Based Detection

Provenance graph-based intrusion detection systems are deployed on hosts to defend against increasingly severe Advanced Persistent Threat. Using Graph Neural Networks to detect these threats has become a research focus and has demonstrated exceptional performance. However, the widespread adoption...

[SECURITY] Fedora 42 Update: polymake-4.14-2.fc42

Polymake is a tool to study the combinatorics and the geometry of convex polytopes and polyhedra. It is also capable of dealing with simplicial complexes, matroids, polyhedral fans, graphs, tropical objects, and so forth. Polymake can use various computational packages if they are installed. Thos...

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...

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...

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...

LLMxCPG: Context-Aware Vulnerability Detection through Code Property Graph-Guided Large Language Models

Software vulnerabilities present a persistent security challenge, with over 25,000 new vulnerabilities reported in the Common Vulnerabilities and Exposures CVE database in 2024 alone. While deep learning based approaches show promise for vulnerability detection, recent studies reveal critical...

WATCHDOG: an Ontology-AWare Risk AssessmenT ApproaCH Via Object-Oriented DisruptiOn Graphs

When considering risky events or actions, we must not downplay the role of involved objects: a charged battery in our phone averts the risk of being stranded in the desert after a flat tyre, and a functional firewall mitigates the risk of a hacker intruding the network. The Common Ontology of Val...

Cut Tracing with E-Graphs for Boolean FHE Circuit Synthesis

Fully Homomorphic Encryption FHE is a promising privacy-preserving technology enabling secure computation over encrypted data. A major limitation of current FHE schemes is their high runtime overhead. As a result, automatic optimization of circuits describing FHE computation has garnered...

Version-Level Third-Party Library Detection in Android Applications Via Class Structural Similarity

Android applications apps integrate reusable and well-tested third-party libraries TPLs to enhance functionality and shorten development cycles. However, recent research reveals that TPLs have become the largest attack surface for Android apps, where the use of insecure TPLs can compromise both...

KGMark: a Diffusion Watermark for Knowledge Graphs

Knowledge graphs KGs are ubiquitous in numerous real-world applications, and watermarking facilitates protecting intellectual property and preventing potential harm from AI-generated content. Existing watermarking methods mainly focus on static plain text or image data, while they can hardly be...

FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks

Graph Convolutional Neural Networks GCNs have gained widespread popularity in various fields like personal healthcare and financial systems, due to their remarkable performance. Despite the growing demand for cloud-based GCN services, privacy concerns over sensitive graph data remain significant...

DEBIAN-CVE-2025-22874

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon...

AZL-63872 CVE-2025-22874 affecting package msft-golang for versions less than 1.24.1-3

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon...

AZL-78986 CVE-2025-22874 affecting package golang 1.25.7-1

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon...

AZL-72104 CVE-2025-22874 affecting package golang for versions less than 1.24.4-1

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon...

UBUNTU-CVE-2025-22874

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon...

[SECURITY] Fedora 42 Update: qt6-qtgraphs-6.9.1-1.fc42

The Qt Graphs module enables you to visualize data in 3D as bar, scatter, and surface graphs. It's especially useful for visualizing depth maps and large quantities of rapidly changing data, such as data received from multiple sensors. The look and feel of graphs can be customized by using themes...

SUSE CVE-2025-22874

Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon...

PROVSYN: Synthesizing Provenance Graphs for Data Augmentation in Intrusion Detection Systems

Provenance graph analysis plays a vital role in intrusion detection, particularly against Advanced Persistent Threats APTs, by exposing complex attack patterns. While recent systems combine graph neural networks GNNs with natural language processing NLP to capture structural and semantic features...

Attack Effect Model Based Malicious Behavior Detection

Traditional security detection methods face three key challenges: inadequate data collection that misses critical security events, resource-intensive monitoring systems, and poor detection algorithms with high false positive rates. We present FEAD Focus-Enhanced Attack Detection, a framework that...