CVE-2025-38327

In the Linux kernel, the following vulnerability has been resolved: fgraph: Do not enable functiongraph tracer when setting funcgraph-args When setting the funcgraph-args option when function graph tracer is net enabled, it incorrectly enables it. Worse, it unregisters itself when it was never...

UBUNTU-CVE-2025-38327

In the Linux kernel, the following vulnerability has been resolved: fgraph: Do not enable functiongraph tracer when setting funcgraph-args When setting the funcgraph-args option when function graph tracer is net enabled, it incorrectly enables it. Worse, it unregisters itself when it was never...

CVE-2025-38327

In the Linux kernel, the following vulnerability has been resolved: fgraph: Do not enable functiongraph tracer when setting funcgraph-args When setting the funcgraph-args option when function graph tracer is net enabled, it incorrectly enables it. Worse, it unregisters itself when it was never...

CVE-2025-38327 fgraph: Do not enable function_graph tracer when setting funcgraph-args

In the Linux kernel, the following vulnerability has been resolved: fgraph: Do not enable functiongraph tracer when setting funcgraph-args When setting the funcgraph-args option when function graph tracer is net enabled, it incorrectly enables it. Worse, it unregisters itself when it was never...

PT-2025-29049

Name of the Vulnerable Software and Affected Versions: Linux kernel affected versions not specified Description: The Linux kernel contained a flaw in the function graph tracer where enabling the funcgraph-args option incorrectly enabled the tracer, potentially leading to a warning in the accounti...

Parse Server 安全漏洞

Parse Server is an open source backend from Parse Platform Open Source that can be deployed to any infrastructure that can run Node.js. A security vulnerability exists in Parse Server versions prior to 5.3.0 through 7.5.3 and prior to 8.2.2, which stems from the GraphQL API not validating a sessi...

Disa: Accurate Learning-Based Static Disassembly with Attentions

For reverse engineering related security domains, such as vulnerability detection, malware analysis, and binary hardening, disassembly is crucial yet challenging. The fundamental challenge of disassembly is to identify instruction and function boundaries. Classic approaches rely on file-format...

RAG Safety: Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation

Retrieval-Augmented Generation RAG enhances large language models LLMs by retrieving external data to mitigate hallucinations and outdated knowledge issues. Benefiting from the strong ability in facilitating diverse data sources and supporting faithful reasoning, knowledge graphs KGs have been...

PotentRegion4MalDetect: Advanced Features from Potential Malicious Regions for Malware Detection

Malware developers exploit the fact that most detection models focus on the entire binary to extract the feature rather than on the regions of potential maliciousness. Therefore, they reverse engineer a benign binary and inject malicious code into it. This obfuscation technique circumvents the...

Malicious code in graphprotocol-tools-monorepo (npm)

The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware d2da3e0dc947efefeb72ffd27d949465798a6e39af182b4634c40e9dc4bed764 Any computer that has this package installed or running should be considered...

CVE-2025-40741

A vulnerability has been identified in Solid Edge SE2025 All versions V225.0 Update 5. The affected applications contain a stack based overflow vulnerability while parsing specially crafted CFG files. This could allow an attacker to execute code in the context of the current process...

Bullshark on Narwhal: Implementation-Level Workflow Analysis of Round-Based DAG Consensus in Theory and Practice

Round-based DAGs enable high-performance Byzantine fault-tolerant consensus, yet their technical advantages remain underutilized due to their short history. While research on consensus protocols is active in both academia and industry, many studies overlook implementation-level algorithms, leavin...

VOLTRON: Detecting Unknown Malware Using Graph-Based Zero-Shot Learning

The persistent threat of Android malware presents a serious challenge to the security of millions of users globally. While many machine learning-based methods have been developed to detect these threats, their reliance on large labeled datasets limits their effectiveness against emerging,...

Understand your software’s supply chain with GitHub’s dependency graph

What if you could spot the weakest link in your software supply chain before it breaks? With GitHub's dependency graph, you can. By providing a clear, complete view of the external packages your code depends on, both directly and indirectly, it allows you to understand, secure, and manage your...

Practical and Accurate Local Edge Differentially Private Graph Algorithms

Whitepaper called Practical And Accurate Local Edge Differentially Private Graph Algorithms...

Poster: Enhancing GNN Robustness for Network Intrusion Detection Via Agent-Based Analysis

Graph Neural Networks GNNs show great promise for Network Intrusion Detection Systems NIDS, particularly in IoT environments, but suffer performance degradation due to distribution drift and lack robustness against realistic adversarial attacks. Current robustness evaluations often rely on...

Perry: a High-Level Framework for Accelerating Cyber Deception Experimentation

Cyber deception aims to distract, delay, and detect network attackers with fake assets such as honeypots, decoy credentials, or decoy files. However, today, it is difficult for operators to experiment, explore, and evaluate deception approaches. Existing tools and platforms have non-portable and...

KnowML: Improving Generalization of ML-NIDS with Attack Knowledge Graphs

Despite extensive research on Machine Learning-based Network Intrusion Detection Systems ML-NIDS, their capability to detect diverse attack variants remains uncertain. Prior studies have largely relied on homogeneous datasets, which artificially inflate performance scores and offer a false sense ...

WebGuard++: Interpretable Malicious URL Detection Via Bidirectional Fusion of HTML Subgraphs and Multi-Scale Convolutional BERT

URL+HTML feature fusion shows promise for robust malicious URL detection, since attacker artifacts persist in DOM structures. However, prior work suffers from four critical shortcomings: 1 incomplete URL modeling, failing to jointly capture lexical patterns and semantic context; 2 HTML graph...

FuncVul: an Effective Function Level Vulnerability Detection Model Using LLM and Code Chunk

Software supply chain vulnerabilities arise when attackers exploit weaknesses by injecting vulnerable code into widely used packages or libraries within software repositories. While most existing approaches focus on identifying vulnerable packages or libraries, they often overlook the specific...