EUVD-2026-18241

Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, specially crafted traffic can cause Suricata to slow down, affecting performance in IDS mode. This issue has been patched in versions 7.0.15 and 8.0.4...

CVE-2026-31933

Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, specially crafted traffic can cause Suricata to slow down, affecting performance in IDS mode. This issue has been patched in versions 7.0.15 and 8.0.4...

CVE-2026-31933

Suricata (network IDS/IPS/NSM) is affected by CVE-2026-31933 due to a quadratic/slowdown condition triggered by specially crafted traffic in IDS mode. The issue impacts versions prior to 7.0.15 and 8.0.4, and has been patched in 7.0.15 and 8.0.4. The vulnerability stems from the stream inspection...

CVE-2026-31933 Suricata stream: quadratic complexity in stream inspection

Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, specially crafted traffic can cause Suricata to slow down, affecting performance in IDS mode. This issue has been patched in versions 7.0.15 and 8.0.4...

EUVD-2026-18237

Suricata is a network IDS, IPS and NSM engine. From version 8.0.0 to before version 8.0.4, use of the "tls.alpn" rule keyword can cause Suricata to crash with a NULL dereference. This issue has been patched in version 8.0.4...

Suricata 安全漏洞

Suricata is a network IDS, IPS, and NSM engine developed by the Open Information Security Foundation. Vulnerabilities existed in versions prior to Suricata 7.0.15 and 8.0.4. These vulnerabilities were caused by specially crafted traffic, which could slow down Suricata’s operation in IDS mode,...

GMA-SAWGAN-GP: A Novel Data Generative Framework to Enhance IDS Detection Performance

Intrusion Detection System IDS is often calibrated to known attacks and generalizes poorly to unknown threats. This paper proposes GMA-SAWGAN-GP, a novel generative augmentation framework built on a Self-Attention-enhanced Wasserstein GAN with Gradient Penalty WGAN-GP. The generator employs...

Understanding AI Methods for Intrusion Detection and Cryptographic Leakage

We investigate the role of artificial intelligence in cybersecurity by evaluating how machine learning techniques can detect malicious network activity and identify potential information leakage in cryptographic implementations. We conduct a series of experiments using the NSL-KDD and CIC-IDS...

Targeted Adversarial Traffic Generation : Black-Box Approach to Evade Intrusion Detection Systems in IoT Networks

The integration of machine learning ML algorithms into Internet of Things IoT applications has introduced significant advantages alongside vulnerabilities to adversarial attacks, especially within IoT-based intrusion detection systems IDS. While theoretical adversarial attacks have been extensive...

A Novel Solution for Zero-Day Attack Detection in IDS Using Self-Attention and Jensen-Shannon Divergence in WGAN-GP

The increasing sophistication of cyber threats, especially zero-day attacks, poses a significant challenge to cybersecurity. Zero-day attacks exploit unknown vulnerabilities, making them difficult to detect and defend against. Existing approaches patch flaws and deploy an Intrusion Detection Syst...

Suricata IDPE 8.0.4

Suricata is a network intrusion detection and prevention engine developed by the Open Information Security Foundation and its supporting vendors. The engine is multi-threaded and has native IPv6 support. It's capable of loading existing Snort rules and signatures and supports the Barnyard and...

Huawei EulerOS: Security Advisory for aide (EulerOS-SA-2026-1415)

The remote host is missing an update for the Huawei EulerOS SPDX-FileCopyrightText: 2026 Greenbone AG Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-only ifdescription...

Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks

Adversarial examples can represent a serious threat to machine learning ML algorithms. If used to manipulate the behaviour of ML-based Network Intrusion Detection Systems NIDS, they can jeopardize network security. In this work, we aim to mitigate such risks by increasing the robustness of NIDS...

Incremental Federated Learning for Intrusion Detection in IoT Networks under Evolving Threat Landscape

The expansion of Internet of Things IoT devices has increased the attack surface of networks, necessitating a robust and adaptive intrusion detection systems. Machine learning based systems have been considered promising in enhancing the detection performance. Federated learning settings enabled ...

Game-Theoretic Modeling of Stealthy Intrusion Defense against MDP-Based Attackers

The rapid expansion of Internet use has increased system exposure to cyber threats, with advanced persistent threats APTs being especially challenging due to their stealth, prolonged duration, and multi-stage attacks targeting high-value assets. In this study, we model APT evolution as a strategi...

SoK: Harmonizing Attack Graphs and Intrusion Detection Systems

Detecting and responding to cyber attacks is increasingly difficult as high-volume, complex network traffic allows threats to remain concealed. While Intrusion Detection Systems IDSs identify anomalous behavior, Attack Graphs AGs serve as the primary threat model for analyzing attacker strategies...

A Comparative Study of Recent Advances in Internet of Intrusion Detection Things

The Internet of Things IoT has revolutionized the way devices communicate and interact with each other, but it has also created new challenges in terms of security. In this context, intrusion detection has become a crucial mechanism to ensure the safety of IoT systems. To address this issue, a...

CAM-LDS: Cyber Attack Manifestations for Automatic Interpretation of System Logs and Security Alerts

Log data are essential for intrusion detection and forensic investigations. However, manual log analysis is tedious due to high data volumes, heterogeneous event formats, and unstructured messages. Even though many automated methods for log analysis exist, they usually still rely on domain-specif...

DKD-KAN: A Lightweight Knowledge-Distilled KAN Intrusion Detection Framework, Based on MLP and KAN

Cyber-security systems often operate in resource-constrained environments, such as edge environments and real-time monitoring systems, where model size and inference time are crucial. A light-weight intrusion detection framework is proposed that utilizes the Kolmogorov-Arnold Network KAN to captu...

STARDIS: Strategic Scheduling and Deceptive Signaling for Satellite Intrusion Detection System Deployment

Satellite communication networks operate under stringent computational constraints and are susceptible to sophisticated cyberattacks. This paper introduces a novel defense framework that decouples security optimization into ground-based analysis and onboard real-time execution. In the long-term...