ROLoad-PMP: Securing Sensitive Operations for Kernels and Bare-Metal Firmware

A common way for attackers to compromise victim systems is hijacking sensitive operations e.g., control-flow transfers with attacker-controlled inputs. Existing solutions in general only protect parts of these targets and have high performance overheads, which are impractical and hard to deploy o...

Generative AI and Federated Learning for Intrusion Detection Systems: A Survey

Intrusion Detection Systems IDSs are essential for monitoring network traffic and identifying malicious activities in modern cyber-physical, Internet of Things IoT, enterprise, and distributed network environments. However, developing reliable IDS models remains challenging because attack behavio...

A Predictive Neural Network Architecture for Early Detection of Low-Rate Cyberattacks

Low-Rate Denial of Service LDoS attacks pose a significant challenge to IoT networks due to their subtle and prolonged nature, often evading traditional intrusion detection systems. This paper presents IDQS Intrusion Detection via QoS Prediction, a lightweight and proactive framework for early LD...

CVE-2026-50108 Naxclow IoT Platform Missing Authorization

The Naxclow platform API that returns device relay registration details exposes a persistent credential without verifying that the requester is the legitimate device or owner. An actor able to present a platform-valid request signature can retrieve credentials for arbitrary devices and register o...

Exploit for CVE-2020-25078

ABYSS C2 — HiSilicon DVR Exploit Framework ⚠️ EDUCATIONAL...

Exploit for CVE-2020-25078

ABYSS C2 — HiSilicon DVR Exploit Framework ⚠️ EDUCATIONAL...

Meari IoT Cloud MQTT Broker EMQX 安全漏洞

Meari IoT Cloud MQTT Broker EMQX is a high-performance IoT messaging proxy service based on the MQTT protocol provided by Meari Corporation. A security vulnerability exists in the Meari IoT Cloud MQTT Broker EMQX 4.x version. This vulnerability stems from the lack of authorization for device-leve...

Converging Zero Trust and IoT Security: A Multivocal Literature Review

The convergence of Internet of Things IoT security and Zero Trust ZT principles is a trending topic, demanding a comprehensive, multi-perspective analysis. We present the first multivocal literature review MLR on this topic, combining 68 academic and 36 industrial studies. This comprehensive revi...

CVE-2026-21515

Technical details of CVE-2026-21515 are not publicly available in the provided documents. Monitor for updates from MSRC/NVD; no specifics on affected components, root cause, or fixes are included.

CVE-2026-23661

Cleartext transmission of sensitive information in Azure IoT Explorer allows an unauthorized attacker to disclose information over a network...

LoRA-Based Parameter-Efficient LLMs for Continuous Learning in Edge-Based Malware Detection

The proliferation of edge devices has created an urgent need for security solutions capable of detecting malware in real time while operating under strict computational and memory constraints. Recently, Large Language Models LLMs have demonstrated remarkable capabilities in recognizing complex...

CVE-2026-21528

CVE-2026-21528 affects the Azure IoT SDK with binding to an unrestricted IP address, enabling an unauthorized attacker to disclose information over a network. The CVSS v3.1 vector (AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N) yields a base score of 6.5 (Medium). Affected component is the Azure IoT SDK; t...

Think Fast: Real-Time IoT Intrusion Reasoning Using IDS and LLMs at the Edge Gateway

As the number of connected IoT devices continues to grow, securing these systems against cyber threats remains a major challenge, especially in environments with limited computational and energy resources. This paper presents an edge-centric Intrusion Detection System IDS framework that integrate...

EUVD-2017-2370

Malware in sbrugna...

EUVD-2022-27237

Malicious code in bioql PyPI...

EUVD-2022-7396

Malicious code in bioql PyPI...

A Systematic Review of Metaheuristics-Based and Machine Learning-Driven Intrusion Detection Systems in IoT

The widespread adoption of the Internet of Things IoT has raised a new challenge for developers since it is prone to known and unknown cyberattacks due to its heterogeneity, flexibility, and close connectivity. To defend against such security breaches, researchers have focused on building...

CVE-2019-10497

Use after free issue occurs If another instance of open for voicesvc node has been called from application without closing the previous one. in Snapdragon Auto, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in...

Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data

Due to the rapid growth in the number of Internet of Things IoT networks, the cyber risk has increased exponentially, and therefore, we have to develop effective IDS that can work well with highly imbalanced datasets. A high rate of missed threats can be the result, as traditional machine learnin...

DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-Based Intrusion Detection against Adversarial Attacks

The rapid proliferation of the Internet of Things IoT has introduced substantial security vulnerabilities, highlighting the need for robust Intrusion Detection Systems IDS. Machine learning-based intrusion detection systems ML-IDS have significantly improved threat detection capabilities; however...