Malicious code in models-frontend (npm)

The package models-frontend was found to contain malicious code...

Malicious code in elprices-models (npm)

The package elprices-models was found to contain malicious code...

Malicious code in humanapi-models (npm)

The package humanapi-models was found to contain malicious code...

Malicious code in priv-models (npm)

The package priv-models was found to contain malicious code...

MAL-2025-19539 Malicious code in elprices-models (npm)

The package elprices-models was found to contain malicious code...

Malicious code in gp-db-models (npm)

The package gp-db-models was found to contain malicious code...

MAL-2025-29659 Malicious code in priv-models (npm)

The package priv-models was found to contain malicious code...

Malicious code in inventory-models (npm)

The package inventory-models was found to contain malicious code...

MAL-2025-32958 Malicious code in sequelize-models-version-history (npm)

The package sequelize-models-version-history was found to contain malicious code...

MAL-2025-22792 Malicious code in humanapi-models (npm)

The package humanapi-models was found to contain malicious code...

MAL-2025-23295 Malicious code in inventory-models (npm)

The package inventory-models was found to contain malicious code...

MAL-2025-21781 Malicious code in gp-db-models (npm)

The package gp-db-models was found to contain malicious code...

Deserialization Of Untrusted Data

ms-swift is vulnerable to Deserialization Of Untrusted Data. The vulnerability is due to unsafe deserialization due to malicious pickle deserialization in adapter model files, allowing arbitrary command execution when loading specially crafted adapter models from ModelScope...

Apple Security Update: iOS 18.6.1

Apple recommends to install security update iOS 18.6.1 on devices iPhone XS and later...

Code Vulnerability Detection across Different Programming Languages with AI Models

Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do not work well at detecting the context-dependent bugs and...

REFN: a Reinforcement-Learning-From-Network Framework against 1-Day/N-Day Exploitations

The exploitation of 1 day or n day vulnerabilities poses severe threats to networked devices due to massive deployment scales and delayed patching average Mean Time To Patch exceeds 60 days. Existing defenses, including host based patching and network based filtering, are inadequate due to limite...

Enhancing GraphQL Security by Detecting Malicious Queries Using Large Language Models, Sentence Transformers, and Convolutional Neural Networks

GraphQL's flexibility, while beneficial for efficient data fetching, introduces unique security vulnerabilities that traditional API security mechanisms often fail to address. Malicious GraphQL queries can exploit the language's dynamic nature, leading to denial-of-service attacks, data...

Can Multi-Modal (Reasoning) LLMs Detect Document Manipulation?

Document fraud poses a significant threat to industries reliant on secure and verifiable documentation, necessitating robust detection mechanisms. This study investigates the efficacy of state-of-the-art multi-modal large language models LLMs-including OpenAI O1, OpenAI 4o, Gemini Flash thinking,...

Advancing Autonomous Incident Response: Leveraging LLMs and Cyber Threat Intelligence

Effective incident response IR is critical for mitigating cyber threats, yet security teams are overwhelmed by alert fatigue, high false-positive rates, and the vast volume of unstructured Cyber Threat Intelligence CTI documents. While CTI holds immense potential for enriching security operations...

CVE-2025-8828

A vulnerability was determined in Linksys RE6250, RE6300, RE6350, RE6500, RE7000 and RE9000 up to 20250801. Affected is the function ipv6cmd of the file /goform/setIpv6. The manipulation of the argument...