Comparative Analysis of Machine Learning Based Intrusion Detection in Realistic IoT Networks

The Internet of Things IoT is rapidly growing and expanding into various sectors, such as healthcare, transportation, smart homes, and more. Despite the benefits of using IoT devices, they present several challenges. Given the significant role these devices play in our lives, it is crucial to...

DEBIAN-CVE-2026-53434

Detection of Error Condition Without Action vulnerability in Apache Tomcat when configuring CRLs for a FFM based connector. This issue affects Apache Tomcat: from 11.0.0-M1 through 11.0.22, from 10.1.0-M7 through 10.1.55, from 9.0.83 through 9.0.118. Users are recommended to upgrade to version...

CVE-2026-53434

Detection of Error Condition Without Action vulnerability in Apache Tomcat when configuring CRLs for a FFM based connector. This issue affects Apache Tomcat: from 11.0.0-M1 through 11.0.22, from 10.1.0-M7 through 10.1.55, from 9.0.83 through 9.0.118. Users are recommended to upgrade to version...

CVE-2026-53434 Apache Tomcat: Invalid CRL configuration doesn't trigger failure for FFM Connector

Detection of Error Condition Without Action vulnerability in Apache Tomcat when configuring CRLs for a FFM based connector. This issue affects Apache Tomcat: from 11.0.0-M1 through 11.0.22, from 10.1.0-M7 through 10.1.55, from 9.0.83 through 9.0.118. Users are recommended to upgrade to version...

CVE-2026-53434

Detection of Error Condition Without Action vulnerability in Apache Tomcat when configuring CRLs for a FFM based connector. This issue affects Apache Tomcat: from 11.0.0-M1 through 11.0.22, from 10.1.0-M7 through 10.1.55, from 9.0.83 through 9.0.118. Users are recommended to upgrade to version...

kernel: wifi: mac80211: use safe list iteration in radar detect work

A flaw was found in the Linux kernel's mac80211 wireless subsystem. This vulnerability arises from unsafe list iteration during radar detection work, where a channel context can be freed while still being processed. This can lead to a use-after-free memory error. A successful exploit could result...

IKEv1 / IPsec endpoint detection (ike-scan)

Detects IKEv1 ISAKMP VPN endpoints on UDP 500/4500. Sends Main Mode and Aggressive Mode probes similar to ike-scan, parses SA transforms, vendor IDs XAUTH, DPD, Cisco Unity, and reports whether Aggressive Mode PSK capture may be possible. !/usr/bin/env python3 -- coding: utf-8 -- from kittysploit...

hbac-bias-detection (>=0.1.7, <=0.2.6) potentially affected by CVE-2026-44727 via jupyter-server (1.16.0)

jupyter-server PYPI version 1.16.0 is affected by a known vulnerability. The following packages have a transitive dependency on jupyter-server and may be impacted: - hbac-bias-detection =0.1.7, =0.2.6 Source cves: CVE-2026-44727 Source advisory: OSV:PYSEC-2026-366...

bounthunt

Bountyhunt !CIhttps://github.com/bess1lie/bountyhunt/acti...

Bluekit Phishing Kit Uses Browser-in-the-Middle Attacks to Evade Detection

A new phishing-as-a-service PHaaS platform called Bluekit is letting cybercriminals steal user accounts using a tricky method. While…...

CVE-2026-53291

A flaw was found in the Advanced Linux Sound Architecture ALSA hda/conexant driver within the Linux kernel. A missing error check for the sndhdajackdetectenablecallback function's return value in cxprobe can lead to a kernel crash. If the registration of the jack detection callback fails, the...

ShieldPatch

🛡️ ShieldPatch Predict . Protect . Prevail AI-driven vuln...

Multi-Level Distributional Entropy for Explainable Network Intrusion Detection

Machine learning network intrusion detection systems IDS rely on aggregate flow statistics that discard distributional structure, while established entropy measures require raw packet sequences unavailable in pre-aggregated flow datasets. We propose Multi-Level Distributional Entropy MDE, an...

A Hybrid Framework for Crypto-Ransomware Detection in Enterprise Shared Storage

Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequently, ransomware operators have evolved variants that expand their attack surface from local systems to network drives and shared storage resources. ...

CAN We Trust Your Results? A Cross-Dataset Study of Automotive IDS Evaluation

The increasing connectivity of modern vehicles has made securing in-vehicle communication networks a critical challenge. Intrusion Detection Systems IDS have been widely studied as a defense mechanism for detecting malicious activities on the Controller Area Network CAN bus. However, the evaluati...

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

Researchers and practitioners increasingly apply Large Language Models LLMs for automated vulnerability detection. Recent work has shown that LLMs are susceptible to the same cognitive heuristics that bias human judgment. Yet, no work has investigated whether these heuristics affect a model's...

MAL-2026-6597 Malicious code in @longzy/react-native-polyfill (npm)

This npm package is purpose-built malware that exfiltrates host information and environment secrets. It runs as a postinstall hook the keyword "postinstall" is obfuscated in the code and bails immediately if npmpackagename is unset, confirming it only fires during npm install. After a randomized...

MAL-2026-6595 Malicious code in @digitalcnzz/commonmodule (npm)

This npm package is purpose-built malware that exfiltrates host information and environment secrets. It runs as a postinstall hook the keyword "postinstall" is obfuscated in the code and bails immediately if npmpackagename is unset, confirming it only fires during npm install. After a randomized...

MAL-2026-6596 Malicious code in @digitalcnzz/embedded-sdk (npm)

This npm package is purpose-built malware that exfiltrates host information and environment secrets. It runs as a postinstall hook the keyword "postinstall" is obfuscated in the code and bails immediately if npmpackagename is unset, confirming it only fires during npm install. After a randomized...

A Multi-Task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution

Malware classification remains a challenging problem due to its inherent heterogeneity, the presence of packed binaries, and the diverse distribution of malware families. Traditional single-model detection mechanisms often fail to generalize across such diverse data, leading to degraded...