PT-2026-3891

Name of the Vulnerable Software and Affected Versions CoreShop versions prior to 4.1.9 Description An error-based SQL Injection issue exists in the CustomerTransformerController within the CoreShop admin panel. The affected endpoint improperly incorporates user-supplied input into a SQL query,...

MiracleLinux 8 : java-1.8.0-openjdk-1.8.0.322.b06-2.el8 (AXSA:2022-3023:02)

The remote MiracleLinux 8 host has packages installed that are affected by multiple vulnerabilities as referenced in the AXSA:2022-3023:02 advisory. OpenJDK: Incomplete deserialization class filtering in ObjectInputStream Serialization, 8264934 CVE-2022-21248 OpenJDK: Insufficient URI checks in t...

mariadb: MariaDB Server Crash via Item_direct_view_ref

A flaw was found in MariaDB Server. This vulnerability may allow an attacker to crash the database via Itemdirectviewref::derivedfieldtransformerforwhere...

mariadb: MariaDB Server Crash via Item_direct_view_ref

A flaw was found in MariaDB Server. This vulnerability may allow an attacker to crash the database via Itemdirectviewref::derivedfieldtransformerforwhere...

mariadb: MariaDB Server Crash via Item_direct_view_ref

A flaw was found in MariaDB Server. This vulnerability may allow an attacker to crash the database via Itemdirectviewref::derivedfieldtransformerforwhere...

Large Language Models for Detecting Cyberattacks on Smart Grid Protective Relays

This paper presents a large language model LLM-based framework for detecting cyberattacks on transformer current differential relays TCDRs, which, if undetected, may trigger false tripping of critical transformers. The proposed approach adapts and fine-tunes compact LLMs such as DistilBERT to...

mariadb: MariaDB Server Crash via Item_direct_view_ref

A flaw was found in MariaDB Server. This vulnerability may allow an attacker to crash the database via Itemdirectviewref::derivedfieldtransformerforwhere...

Improving Router Security Using BERT

Previous work on home router security has shown that using system calls to train a transformer-based language model built on a BERT-style encoder using contrastive learning is effective in detecting several types of malware, but the performance remains limited at low false positive rates. In this...

Engineering Attack Vectors and Detecting Anomalies in Additive Manufacturing

Additive manufacturing AM is rapidly integrating into critical sectors such as aerospace, automotive, and healthcare. However, this cyber-physical convergence introduces new attack surfaces, especially at the interface between computer-aided design CAD and machine execution layers. In this work, ...

Malicious code in @vietmoney/react-native-image-transformer (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector a5d6e41bb857d4ed96776b54551e25a97efccd98d763659d945f9c969c7981cf The package @vietmoney/react-native-image-transformer was found to contain malicious code. Source: ghsa-malware...

MAL-2025-192997 Malicious code in @vietmoney/react-native-image-transformer (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector a5d6e41bb857d4ed96776b54551e25a97efccd98d763659d945f9c969c7981cf The package @vietmoney/react-native-image-transformer was found to contain malicious code. Source: ghsa-malware...

Malicious Package

Overview @vietmoney/react-native-image-transformer is a malicious package. This package contains malicious code, and its content was removed from the official package manager. While this package might be attempting to impersonate a valid organization, there is no connection between that...

EUVD-2025-205934

Malicious code in @vietmoney/react-native-image-transformer npm...

FedLiTeCAN : A Federated Lightweight Transformer for Fast and Robust CAN Bus Intrusion Detection

This work implements a lightweight Transformer model for IDS in the domain of Connected and Autonomous Vehicles...

CVE-2025-14921

A flaw was found in the Hugging Face Transformers library. The parsing of model files fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious Transformer-XL model, resulting in arbitrary code execution in the...

CVE-2025-14921 Hugging Face Transformers Transformer-XL Model Deserialization of Untrusted Data Remote Code Execution Vulnerability

Hugging Face Transformers Transformer-XL Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this...

CVE-2025-14921 Hugging Face Transformers Transformer-XL Model Deserialization of Untrusted Data Remote Code Execution Vulnerability

Hugging Face Transformers Transformer-XL Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this...

CVE-2025-14921

CVE-2025-14921 affects Hugging Face Transformers (Transformer-XL) with a flaw in parsing Transformer-XL model files that fails to validate untrusted input, enabling deserialization of untrusted data and remote code execution. The underlying cause is insufficient validation during model-file parsi...

Hugging Face Transformers 代码问题漏洞

Hugging Face Transformers is a Hugging Face open source framework for defining state-of-the-art machine learning models covering textual, visual, audio, and multimodal models for inference and training. A code issue vulnerability exists in Hugging Face Transformers that stems from a lack of...

PT-2025-52379

Name of the Vulnerable Software and Affected Versions Hugging Face Transformers affected versions not specified Description A flaw exists in Hugging Face Transformers due to insufficient validation of user-supplied data during the parsing of model files. This can lead to the deserialization of...