Linux kernel 安全漏洞

Linux kernel is the kernel used by Linux, the open source operating system of the Linux Foundation in the United States. A security vulnerability exists in Linux kernel, which stems from insufficient checking of the graphutilparselinkdirection pointer in simple-card-utils...

@jamietanna/patch-testing (>=0.1.0 <=0.2.28), @jamietanna/renovate-graph (>=0.24.0 <=0.30.0) +5 more potentially affected by CVE-2025-47934 via openpgp (>=6.0.0 <=6.1.0)

openpgp NPM version =6.0.0, =0.1.0, =0.24.0, =0.5.2, =7.2.5, =0.40.0, =2.0.0, =39.15.1, =41.0.0-next.22 Source cves: CVE-2025-47934 Source advisory: OSV:GHSA-8QFF-QR5Q-5PR8...

VulCPE: Context-Aware Cybersecurity Vulnerability Retrieval and Management

The dynamic landscape of cybersecurity demands precise and scalable solutions for vulnerability management in heterogeneous systems, where configuration-specific vulnerabilities are often misidentified due to inconsistent data in databases like the National Vulnerability Database NVD. Inaccurate...

@adpt/testutils (>=0.1.0-next.1 <=0.4.0-next.6), @lavamoat/git-safe-dependencies (>=0.1.1 <=0.2.1) +6 more potentially affected by CVE-2025-4759 via lockfile-lint-api (>=1.0.7 <=5.9.1)

lockfile-lint-api NPM version =1.0.7, =0.1.0-next.1, =0.1.1, =1.0.0, =4.3.1-test1, =1.3.0, =1.0.1, =4.2.2, =4.3.1, =4.7.0 Source cves: CVE-2025-4759 Source advisory: OSV:GHSA-7CFR-5CJF-32P4...

Co-Evolutionary Defence of Active Directory Attack Graphs Via GNN-Approximated Dynamic Programming

Modern enterprise networks increasingly rely on Active Directory AD for identity and access management. However, this centralization exposes a single point of failure, allowing adversaries to compromise high-value assets. Existing AD defense approaches often assume static attacker behavior, but...

kernel: arm64: set __exception_irq_entry with __irq_entry as a default

A stack trace handling issue was found in ARM64 kernels. Without CONFIGFUNCTIONGRAPHTRACER, the IRQ entry function is not properly marked, causing filterirqstacks to fail and potentially causing stack depot overflow warnings under KASAN...

kernel: coresight: Fix memory leak in acpi_buffer->pointer

In the Linux kernel, the following vulnerability has been resolved: coresight: Fix memory leak in acpibuffer-pointer There are memory leaks reported by kmemleak: ... unreferenced object 0xffff00213c141000 size 1024: comm "systemd-udevd", pid 2123, jiffies 4294909467 age 6062.160s hex dump first 3...

LibVulnWatch: a Deep Assessment Agent System and Leaderboard for Uncovering Hidden Vulnerabilities in Open-Source AI Libraries

Open-source AI libraries are foundational to modern AI systems but pose significant, underexamined risks across security, licensing, maintenance, supply chain integrity, and regulatory compliance. We present LibVulnWatch, a graph-based agentic assessment framework that performs deep,...

GPML: Graph Processing for Machine Learning

The dramatic increase of complex, multi-step, and rapidly evolving attacks in dynamic networks involves advanced cyber-threat detectors. The GPML Graph Processing for Machine Learning library addresses this need by transforming raw network traffic traces into graph representations, enabling...

tracing: Fix use-after-free in print_graph_function_flags during tracer switching

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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...

Adaptive Wizard for Removing Cross-Tier Misconfigurations in Active Directory

Security vulnerabilities in Windows Active Directory AD systems are typically modeled using an attack graph and hardening AD systems involves an iterative workflow: security teams propose an edge to remove, and IT operations teams manually review these fixes before implementing the removal. As...

AI-Driven IRM: Transforming Insider Risk Management with Adaptive Scoring and LLM-Based Threat Detection

Insider threats pose a significant challenge to organizational security, often evading traditional rule-based detection systems due to their subtlety and contextual nature. This paper presents an AI-powered Insider Risk Management IRM system that integrates behavioral analytics, dynamic risk...

Addressing Noise and Stochasticity in Fraud Detection for Service Networks

Fraud detection is crucial in social service networks to maintain user trust and improve service network security. Existing spectral graph-based methods address this challenge by leveraging different graph filters to capture signals with different frequencies in service networks. However, most...

Graph Privacy: a Heterogeneous Federated GNN for Trans-Border Financial Data Circulation

The sharing of external data has become a strong demand of financial institutions, but the privacy issue has led to the difficulty of interconnecting different platforms and the low degree of data openness. To effectively solve the privacy problem of financial data in trans-border flow and sharin...

Quantifying the Noise of Structural Perturbations on Graph Adversarial Attacks

Graph neural networks have been widely utilized to solve graph-related tasks because of their strong learning power in utilizing the local information of neighbors. However, recent studies on graph adversarial attacks have proven that current graph neural networks are not robust against malicious...

Mitigating the Structural Bias in Graph Adversarial Defenses

In recent years, graph neural networks GNNs have shown great potential in addressing various graph structure-related downstream tasks. However, recent studies have found that current GNNs are susceptible to malicious adversarial attacks. Given the inevitable presence of adversarial attacks in the...

Federated One-Shot Learning with Data Privacy and Objective-Hiding

Privacy in federated learning is crucial, encompassing two key aspects: safeguarding the privacy of clients' data and maintaining the privacy of the federator's objective from the clients. While the first aspect has been extensively studied, the second has received much less attention. We present...

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...

Dual Explanations Via Subgraph Matching for Malware Detection

Interpretable malware detection is crucial for understanding harmful behaviors and building trust in automated security systems. Traditional explainable methods for Graph Neural Networks GNNs often highlight important regions within a graph but fail to associate them with known benign or maliciou...