Malicious code in multyproccess (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 7938a109a642dfe8b161e9568d6373a038c3413c0fd1f2b01702f4f173348553 The package's setup.py overrides the install and develop cmdclass to base64-decode a bundled request/.payload file and launch it via...

MAL-2026-14401 Malicious code in multyproccess (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 7938a109a642dfe8b161e9568d6373a038c3413c0fd1f2b01702f4f173348553 The package's setup.py overrides the install and develop cmdclass to base64-decode a bundled request/.payload file and launch it via...

Closing the Gap Between Detection and Protection with AI-Assisted Custom Rules

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WPProbe Plugin Enumeration Tool 0.12.9

A fast WordPress plugin and theme scanner that detects installed plugins via REST API enumeration and themes from HTML discovery, then maps them to known vulnerabilities. Over 5,000 plugins detectable without brute-force, thousands more with it...

Robustness of Anomaly Detection Models for Industrial Control Systems under Training-Time Data Contamination

Machine-learning-based anomaly detection is increasingly used in industrial control systems ICS, yet most studies assume that detector training data is trustworthy. In practice, training data may be corrupted through compromised logs, labeling errors, manipulated historian records, or unsafe...

Adapter-Based Few-Shot Continual Learning for Malicious Packet Recognition

The continual evolution of malware variants necessitates detection systems that can adapt to new threats without retraining from scratch. However, continually updating models on new data often leads to catastrophic forgetting, where previously learned knowledge is overwritten. While continual...

RAD: Rule-Augmented Relational Anomaly Detection

Anomaly detection is often applied to data stored in relational databases, yet most existing methods require flattening multiple tables into a single feature matrix. This flattening can obscure entity identity, schema structure, and multi-hop dependencies, limiting the detection of anomalies that...

Effective Pivot Attack Detection Via System and Network Information

Perimeter-based security appliances, such as firewalls or Intrusion Detection Systems, are ineffective against modern attacks that use pivoting, wherein attackers "pivot" traffic through compromised hosts to gain access to additional targets that would otherwise be inaccessible. Due to the...

The Surprising Effectiveness of LLMs in BGP Security: Mining an Unprecedented Amount of Incidents and Boosting Anomaly Detection

Border Gateway Protocol BGP security is critical to Internet infrastructure, yet progress in routing anomaly detection has been limited by the scarcity of publicly available incident datasets, which contain only 18 recorded cases. We observe that public operator mailing lists, e.g., NANOG and...

nginx-log-analyzer

nginxloganalyzer Nginx Access Log Security Analysis Tool —...

ids-traffic-analysis

Network Intrusion Detection and Traffic Analysis Platform Thi...

chainsaw v2.16.4

Rapidly Search and Hunt through Windows Forensic Artefacts Chainsaw provides a powerful ‘first-response’ capability to quickly identify threats within Windows forensic artefacts such as Event Logs and the MFT file. Chainsaw offers a generic and fast method of searching through event logs for...

Kestrel v.1.1.0

Kestrel BloodHound shows you the path. Kestrel shows you what's already inside. Everyone maps the same thing: the attack path - who can reach Domain Admin. It's the right question, and the tools that answer it are excellent. But a graph of "who can reach whom" is blind to an entire class of...

detection-rules dev-v2.1.0

Detection Rules Detection Rules is the home for rules used by Elastic Security. This repository is used for the development, maintenance, testing, validation, and release of rules for Elastic Security’s Detection Engine. This repository was first announced on Elastic's blog post, Elastic Security...

Mitigating Explanation Leakage in Financial Fraud Detection Systems

Financial fraud detection relies heavily on centralized machine learning models. This creates serious data privacy risks. Federated Learning FL decentralizes data processing, but financial regulations still require models to be transparent. This means using Explainable AI XAI tools such as...

CVE-2026-74686

In the Linux kernel, the following vulnerability has been resolved: rqspinlock: Reset tail when preserving queue on deadlock Currently, the destruction of the waiter queue is suppressed for rqspinlock in cases where a deadlock is detected. Deadlock checks happen relatively frequently on entry for...

phpstan v2.2.9

PHPStan - PHP Static Analysis Tool PHPStan focuses on finding errors in your code without actually running it. It catches whole classes of bugs even before you write tests for the code. It moves PHP closer to compiled languages in the sense that the correctness of each line of the code can be...

CVE-2026-74686 rqspinlock: Reset tail when preserving queue on deadlock

In the Linux kernel, the following vulnerability has been resolved: rqspinlock: Reset tail when preserving queue on deadlock Currently, the destruction of the waiter queue is suppressed for rqspinlock in cases where a deadlock is detected. Deadlock checks happen relatively frequently on entry for...

CVE-2026-74686

This vulnerability affects the Linux kernel 's rqspinlock (queued read-copy spinlock) implementation. When an ABBA deadlock is detected, the waiter queue's tail is not reset, causing the detecting CPU to wait indefinitely for a next waiter that may never arrive. This leads to intermittent stalls ...

EUVD-2026-64373

In the Linux kernel, the following vulnerability has been resolved: rqspinlock: Reset tail when preserving queue on deadlock Currently, the destruction of the waiter queue is suppressed for rqspinlock in cases where a deadlock is detected. Deadlock checks happen relatively frequently on entry for...