Kibana ML DoS

The vulnerability of the Machine Learning function of the Kibana data visualization service is related to an uncontrolled resource consumption. Exploiting this vulnerability could allow a malicious actor to cause service failures...

Unmasking Shortcut Learning in IoT Intrusion Detection: A Forensic, Multi-Paradigm Evaluation of Feature Dependence and Data Leakage

Machine learning-based Network Intrusion Detection Systems often report near-perfect performance on IoT benchmarks. However, whether these models learn generalizable attack behavior or exploit spurious dataset shortcuts- such as static testbed IP/MAC addresses and chronological recording...

Blockchain-Enabled Artificial Intelligence and AI Agents for Secure Data Sharing and Cybersecurity Applications

Blockchain and artificial intelligence AI are converging into a single infrastructural layer for securing data sharing, model integrity, and autonomous decision-making across distributed systems. This paper presents a meta-synthesis that draws together four constituent studies covering adversaria...

[SECURITY] Fedora 45 Update: mivisionx-7.2.1-5.fc45

MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized conformant open-source implementation of the Khronos OpenVX=E2=84=A2 and OpenVX=E2=84=A2 Extensions...

Multi-View Fusion for Encrypted C2 Detection: A Leakage-Controlled Measurement Study of Evaluation Pitfalls

Command-and-control C2 traffic increasingly hides within TLS, so defenders now apply machine learning to traffic metadata. Many studies assume that combining two metadata views, namely flow statistics and TLS handshake fingerprints, improves both accuracy and robustness. We tested this assumption...

HYDRA: Proactive Android Malware Drift Adaptation Via Hierarchical Graph Contrastive Learning

Concept drift, driven by the rapid evolution of Android malware, severely degrades the performance of machine learning detectors. Current adaptation strategies are often reactive, responding only after performance has dropped and imposing a significant manual annotation burden, or they are...

Comparative Evaluation of Static Embedding Models for HTTP Request Anomaly Detection

Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms. Traditional web application firewalls WAFs rely on rule-based approaches that often exhibit high false positive rates and limited adaptability. Recent studies have explored machine...

Reliable Federated TinyML Deployment for IoT Security

The growing deployment of Internet of Things IoT devices has increased the need for privacy-preserving intrusion detection systems that operate directly on resource-constrained hardware. Federated Learning enables collaborative model training without sharing raw data, but conventional federated...

Backdoors in Learning-Based Industrial Robotic Arm Manipulation: An Empirical Security Study

Learning-based models e.g., visuomotor and Vision-Language-Action VLA are increasingly explored for industrial robotic manipulation, where model predictions are directly translated into physical actions. This tight coupling between model behavior and physical execution makes hidden security...

SUSE CVE-2026-90179

In the Linux kernel, the following vulnerability has been resolved: apparmor: fix deadlock in complain-mode changehat The use of changehat when in complain mode can cause a deadlock when the hat doesn't exist and a new learning profile is created for the missing profile. This is because changehat...

owasp-ctf

OWASP CTF セキュリティ学習イベントのためのセルフホスト型コントロールプレーン — 1 台のマシン、1 つの無料 GitHub org で完結。 大学、高校、OWASP チャプター、ミートアップで運用できます。 キットでの作業 人間とエージェント コードを書く前に AGENTS.md を読んでください。これは運用マニュアルであり、 CI が実行する正確なコマンド、このリポジトリがすでに遭遇した障害モード、 そして docs/reviewing.md にあるレビュー不変条件が記載されています。 CLAUDE.md は同じファイルへのポインタです。 変更が準備完了となるのは、CI...

Argus

Argus — All-Seeing Vulnerability Intelligence Platform !CI...

EUVD-2026-82587

Incorrect authorization in Azure Machine Learning allows an unauthorized attacker to disclose information over a network...

CVE-2026-68791

Incorrect authorization in Azure Machine Learning allows an unauthorized attacker to disclose information over a network...

CVE-2026-68791

CVE-2026-68791 is an incorrect authorization vulnerability in Azure Machine Learning that allows an unauthenticated, network-based attacker to disclose information with HIGH severity (CVSS 3.1: 8.6). The attack requires no prior privileges or user interaction, and the scope is CHANGED , indicatin...

CVE-2026-54343

Frappe Learning Management System LMS is a learning system that helps users structure their content. Prior to version 2.52.1, a remote attacker can request a traversal path handled by SCORMRenderer.render in lms/pagerenderers.py. The renderer constructs and opens a server-side path without first...

CVE-2026-54343

Frappe LMS versions prior to 2.52.1 are affected by a path traversal vulnerability in the SCORMRenderer.render function within lms/page_renderers.py. The renderer constructs and opens a server-side file path without verifying that the resolved path remains within the public/scorm directory, allow...

CVE-2026-90179 apparmor: fix deadlock in complain-mode change_hat

In the Linux kernel, the following vulnerability has been resolved: apparmor: fix deadlock in complain-mode changehat The use of changehat when in complain mode can cause a deadlock when the hat doesn't exist and a new learning profile is created for the missing profile. This is because changehat...

Azure Machine Learning Information Disclosure Vulnerability

Incorrect authorization in Azure Machine Learning allows an unauthorized attacker to disclose information over a network...

Robust Workflow Generation Via Adversarial Learning for Audio Deepfake Detection

The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security risks in practical applications. While existing detection methods achieve strong performance under controlled conditions, they often fail to...