CVE-2026-52983

A flaw was found in the Linux kernel's airoha network driver. This vulnerability stems from an inconsistent accounting of inflight packets in the transmit TX path, leading to a Byte Queue Limit BQL imbalance. This issue could potentially result in network performance degradation or a denial of...

CVE-2026-53128

A flaw was found in the Linux kernel's drbd component. Specifically, an imbalance in RCU Read-Copy Update calls within the drbdadmdumpdevices function could occur, where rcureadlock was not properly invoked before rcureadunlock. This concurrency issue, identified by a thread-safety analyzer, may...

CVE-2026-52983

In the Linux kernel, the following vulnerability has been resolved: net: airoha: fix BQL imbalance in TX path Fix a possible BQL imbalance in airohadevxmit, where inflight packets are accounted only for the AIROHANUMTXRING netdev TX queues. The queue index is computed as: qid =...

CVE-2026-52983

The CVE-2026-52983 issue concerns the Linux kernel airoha network driver where inflight packets were counted only for the AIROHA_NUM_TX_RING TX queues in airoha_dev_xmit(), while airoha_qdma_tx_napi_poll() aggregated completions across all netdev TX queues (num_tx_queues). This mismatch creates a...

PT-2026-51877

Name of the Vulnerable Software and Affected Versions Linux kernel affected versions not specified Description An issue exists in the network transmission path where a Byte Queue Limit BQL imbalance occurs. In the airoha dev xmit function, inflight packets are only accounted for the AIROHA NUM TX...

Improving IoT Intrusion Detection through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

The detection of intrusions in IoT-based networks poses challenges that cannot be overcome using traditional machine learning methods. Perhaps the biggest of them is related to the presence of a class imbalance in the side-channel dataset, where the number of samples in the normal class compared ...

Protecting On-Device AI Inference: A Systematic Review of Attacks and Defence Mechanisms

The need for secure and private Artificial Intelligence AI and Machine Learning ML on edge and mobile devices has increased the necessity of protecting the architecture of these systems from threats to both security and privacy. With an ever-increasing number of pre-trained AI models being used o...

Astra Linux – Vulnerability in Linux 5.10, Linux

In the Linux kernel, the following vulnerability has been resolved: Regulator: Core – Fix for unbalanced node refcount in regulatordevlookup The following report was received: ERROR: Memory leak; expected refcount 1 instead of 2. Unbalanced in ofnodeget/ofnodeput – destroyed cset entry: Attaching...

Astra Linux – Vulnerability in Linux 6.1, Linux, Linux 5.15

In the Linux kernel, the following vulnerabilities have been resolved: ax25: Fixed the imbalance in reference counts for inbound connections. When releasing a socket in ax25release, we call netdevput to decrease the reference count of the associated ax.25 device. However, the execution path for...

kernel: net: vlan: fix VLAN 0 refcount imbalance of toggling filtering during runtime

In the Linux kernel, the following vulnerability has been resolved: net: vlan: fix VLAN 0 refcount imbalance of toggling filtering during runtime Assuming the "rx-vlan-filter" feature is enabled on a net device, the 8021q module will automatically add or remove VLAN 0 when the net device is put...

ALSA-2026:18587 Moderate: kernel security update

The kernel packages contain the Linux kernel, the core of any Linux operating system. Security Fixes: kernel: bonding: check xdp prog when set bond mode CVE-2025-22105 kernel: block: fix resource leak in blkregisterqueue error path CVE-2025-37980 kernel: dmaengine: idxd: fix memory leak in error...

A Systematic Literature Review for Transformer-Based Software Vulnerability Detection

Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based models have demonstrated promising results in automatic...

We Are Currently Clean on OPSEC: Why JD Can't Encrypt

We analyse the 2025 Signalgate leak of sensitive US military information by the Trump administration, addressing why confidentiality was violated messages leaked to the press in spite of encryption Signal, to deepen the socio-technical considerations when designing and deploying encryption. First...

kernel: Linux kernel: Use-After-Free vulnerability in ATM subsystem

A flaw was found in the Linux kernel's Asynchronous Transfer Mode ATM subsystem. An authenticated local attacker could exploit a Use-After-Free UAF vulnerability in the /proc/net/atm/lec handling. This flaw occurs due to improper devput calls without prior devhold calls, leading to an imbalance i...

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,...

An Empirical Study of the Imbalance Issue in Software Vulnerability Detection

Vulnerability detection is crucial to protect software security. Nowadays, deep learning DL is the most promising technique to automate this detection task, leveraging its superior ability to extract patterns and representations within extensive code volumes. Despite its promise, DL-based...

Empirical Evaluation of SMOTE in Android Malware Detection with Machine Learning: Challenges and Performance in CICMalDroid 2020

Malware, malicious software designed to damage computer systems and perpetrate scams, is proliferating at an alarming rate, with thousands of new threats emerging daily. Android devices, prevalent in smartphones, smartwatches, tablets, and IoTs, represent a vast attack surface, making malware...

RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance

Deep neural networks are highly susceptible to backdoor attacks, yet most defense methods to date rely on balanced data, overlooking the pervasive class imbalance in real-world scenarios that can amplify backdoor threats. This paper presents the first in-depth investigation of how the dataset...

CVE-2025-71145

CVE-2025-71145 (Linux kernel) fixes a use-after-free-like race by correcting usb: phy: isp1301 to increment the I2C device reference count for non-OF (Open Firmware) paths as well as OF paths. The bug was a device reference imbalance in isp1301_get_client() where non-OF callers could not reliably...

Threat Detection in Social Media Networks Using Machine Learning Based Network Analysis

The accelerated development of social media websites has posed intricate security issues in cyberspace, where these sites have increasingly become victims of criminal activities including attempts to intrude into them, abnormal traffic patterns, and organized attacks. The conventional rule-based...