Unity Linux 20.1070a Security Update: kernel (UTSA-2026-005675)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2026-005675 advisory. In the Linux kernel, the following vulnerability has been resolved: iouring: wait interruptibly for request completions on exit WHen the ring exits, cleanup is done...

Multi-Agent Honeypot-Based Request-Response Context Dataset for Improved SQL Injection Detection Performance

SQL injection remains a major threat to web applications, as existing defenses often fail against obfuscation and evolving attacks because of neglecting the request-response context. This paper presents a context-enriched SQL injection detection framework, focusing on constructing a high-quality...

Unity Linux 20.1070e Security Update: kernel (UTSA-2026-005459)

"The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2026-005459 advisory. In the Linux kernel, the following vulnerability has been resolved: ip6mr: Fix skbunderpanic in ip6mrcachereport skbuff: skbunderpanic: text:ffffffff88771f69 len:56...

Exploit for Uncontrolled Resource Consumption in Siemens 6Bk1602-0Aa12-0Tp0_Firmware

SBOM CVE Scanner - Enhanced Edition A comprehensive Python to...

CVE-2026-3409

creationtimestamp| type| source ---|---|--- 2026-03-02 04:19:34+00:00| seen| https://infosec.exchange/users/vuldb/statuses/116157656223119395 2026-03-02 08:01:03+00:00| seen| https://bsky.app/profile/postac001.bsky.social/post/3mg2ryism3p2n 2026-03-02 08:09:45+00:00| seen|...

Extending Adaptive Cruise Control with Machine Learning Intrusion Detection Systems

An Adaptive Cruise Control ACC system automatically adjusts the host vehicle's speed to maintain a safe following distance from a lead vehicle. In typical implementations, a feedback controller e.g., a Proportional-Integral-Derivative PID controller computes the host vehicle's acceleration using ...

AMDS: Attack-Aware Multi-Stage Defense System for Network Intrusion Detection with Two-Stage Adaptive Weight Learning

Machine learning based network intrusion detection systems are vulnerable to adversarial attacks that degrade classification performance under both gradient-based and distribution shift threat models. Existing defenses typically apply uniform detection strategies, which may not account for...

How the Graph Construction Technique Shapes Performance in IoT Botnet Detection

The increasing incidence of IoT-based botnet attacks has driven interest in advanced learning models for detection. Recent efforts have focused on leveraging attention mechanisms to model long-range feature dependencies and Graph Neural Networks GNNs to capture relationships between data instance...

cipher-xbow-benchmark

Cipher XBOW Benchmark Results Black-box assessment results fr...

honeypot-server

ReportedIP Honeypot Server !License: BSL 1.1https://img.s...

Vulnerability fixed in Juniper Junos OS Evolved

Juniper has fixed a vulnerability in Junos OS Evolved Specifically for PTX Series devices. The vulnerability is in the On-Box Anomaly detection framework of Junos OS Evolved that runs on PTX Series devices. The cause is an incorrect assignment of permissions that allows unauthenticated remote...

Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection

Cross-domain intrusion detection remains a critical challenge due to significant variability in network traffic characteristics and feature distributions across environments. This study evaluates the transferability of three widely used flow-based feature sets Argus, Zeek and CICFlowMeter across...

Neurosymbolic Learning for Advanced Persistent Threat Detection under Extreme Class Imbalance

The growing deployment of Internet of Things IoT devices in smart cities and industrial environments increases vulnerability to stealthy, multi-stage advanced persistent threats APTs that exploit wireless communication. Detection is challenging due to severe class imbalance in network traffic,...

Empowering Future Cybersecurity Leaders: Advancing Students through FINDS Education for Digital Forensic Excellence

The Forensics Investigations Network in Digital Sciences FINDS Research Center of Excellence CoE, funded by the U.S. Army Research Laboratory, advances Digital Forensic Engineering Education DFEE through an integrated research education framework for AI enabled cybersecurity workforce development...

Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems

Distribution shifts in attack patterns within RPL-based IoT networks pose a critical threat to the reliability and security of large-scale connected systems. Intrusion Detection Systems IDS trained on static datasets often fail to generalize to unseen threats and suffer from catastrophic forgetti...

GHSA-62CR-6WP5-Q43H Copyparty vulnerable to reflected XSS via setck parameter

Summary An XSS allows for reflected cross-site scripting via URL-parameter ?setck=... Details A reflected cross-site scripting XSS vulnerability could allow an attacker to execute malicious javascript by tricking users into accessing a malicious link. The worst-case outcome of this is being able ...

CVE-2026-27494

creationtimestamp| type| source ---|---|--- 2026-02-26 11:50:14+00:00| seen| https://www.acn.gov.it/portale/w/rilevate-vulnerabilita-in-n8n-2...

EV Energy ev.energy

RISK EVALUATION Successful exploitation of these vulnerabilities could enable attackers to gain unauthorized administrative control over vulnerable charging stations or disrupt charging services through denial-of-service attacks. 2. RECOMMENDED PRACTICES CISA recommends users take defensive...

ThreatFormer-IDS: Robust Transformer Intrusion Detection with Zero-Day Generalization and Explainable Attribution

Intrusion detection in IoT and industrial networks requires models that can detect rare attacks at low false-positive rates while remaining reliable under evolving traffic and limited labels. Existing IDS solutions often report strong in-distribution accuracy, but they may degrade when evaluated ...

📄 OpenBabel 3.1.1 Parsing Issues

This Metasploit auxiliary module generates specially crafted proof of concept files targeting potential parsing vulnerabilities in OpenBabel version 3.1.1 such as NULL pointer dereference and out-of-bounds read conditions...