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...

ATAG: AI-Agent Application Threat Assessment with Attack Graphs

Evaluating the security of multi-agent systems MASs powered by large language models LLMs is challenging, primarily because of the systems' complex internal dynamics and the evolving nature of LLM vulnerabilities. Traditional attack graph AG methods often lack the specific capabilities to model...

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection

Money laundering is a financial crime that poses a serious threat to financial integrity and social security. The growing number of transactions makes it necessary to use automatic tools that help law enforcement agencies detect such criminal activity. In this work, we present Amatriciana, a nove...

PackHero: a Scalable Graph-Based Approach for Efficient Packer Identification

Anti-analysis techniques, particularly packing, challenge malware analysts, making packer identification fundamental. Existing packer identifiers have significant limitations: signature-based methods lack flexibility and struggle against dynamic evasion, while Machine Learning approaches require...

Heterogeneous Graph Backdoor Attack

Heterogeneous Graph Neural Networks HGNNs excel in modeling complex, multi-typed relationships across diverse domains, yet their vulnerability to backdoor attacks remains unexplored. To address this gap, we conduct the first investigation into the susceptibility of HGNNs to existing graph backdoo...

CVE-2023-28482

An issue was discovered in Tigergraph Enterprise 3.7.0. A single TigerGraph instance can host multiple graphs that are accessed by multiple different users. The TigerGraph platform does not protect the confidentiality of any data uploaded to the remote server. In this scenario, any user that has...

CVE-2022-41444

Cross Site Scripting XSS vulnerability in Cacti 1.2.21 via crafted POST request to graphsnew.php...

Source Anonymity for Private Random Walk Decentralized Learning

This paper considers random walk-based decentralized learning, where at each iteration of the learning process, one user updates the model and sends it to a randomly chosen neighbor until a convergence criterion is met. Preserving data privacy is a central concern and open problem in decentralize...

CVE-2025-47533: Cross-Site Request Forgery (CSRF)

Cross-Site Request Forgery CSRF vulnerability in Iqonic Design Graphina graphina-elementor-charts-and-graphs allows PHP Local File Inclusion.This issue affects Graphina: from n/a through = 3.0.4...

CVE-2025-47480: Missing Authorization

Missing Authorization vulnerability in Iqonic Design Graphina graphina-elementor-charts-and-graphs allows Exploiting Incorrectly Configured Access Control Security Levels.This issue affects Graphina: from n/a through = 3.0.4...

Dynamic Graph-Based Fingerprinting of In-Browser Cryptomining

The decentralized and unregulated nature of cryptocurrencies, combined with their monetary value, has made them a vehicle for various illicit activities. One such activity is cryptojacking, an attack that uses stolen computing resources to mine cryptocurrencies without consent for profit...

SUSE CVE-2023-53093

In the Linux kernel, the following vulnerability has been resolved: tracing: Do not let histogram values have some modifiers Histogram values can not be strings, stacktraces, graphs, symbols, syscalls, or grouped in buckets or log. Give an error if a value is set to do so. Note, the histogram cod...

New Capacity Bounds for PIR on Graph and Multigraph-Based Replicated Storage

In this paper, we study the problem of private information retrieval PIR in both graph-based and multigraph-based replication systems, where each file is stored on exactly two servers, and any pair of servers shares at most $r$ files. We derive upper bounds on the PIR capacity for such systems an...

Hybrid Privacy Policy-Code Consistency Check Using Knowledge Graphs and LLMs

The increasing concern in user privacy misuse has accelerated research into checking consistencies between smartphone apps' declared privacy policies and their actual behaviors. Recent advances in Large Language Models LLMs have introduced promising techniques for semantic comparison, but these...

FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection

Graph-based detection methods leveraging Function Call Graphs FCGs have shown promise for Android malware detection AMD due to their semantic insights. However, the deployment of malware detectors in dynamic and hostile environments raises significant concerns about their robustness. While recent...