MAL-2025-47048 Malicious code in @team-event/models (npm)

The package @team-event/models was found to contain malicious code. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 6769b5703bfb1b74cb1db2c7bf3e87a4abfcc35e4e3fd588c284080cb96583e2 Any computer that has this package installed or running should be considered fully...

Malicious code in @team-event/models (npm)

The package @team-event/models was found to contain malicious code. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 6769b5703bfb1b74cb1db2c7bf3e87a4abfcc35e4e3fd588c284080cb96583e2 Any computer that has this package installed or running should be considered fully...

Malware in @team-event/models

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outsid...

Malicious Package

Overview @liquid-web/models 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 organization and this package...

Malware in @liquid-web/models

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outsid...

Malicious code in @liquid-web/models (npm)

The package @liquid-web/models was found to contain malicious code. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 94c4dab8510635c784a7216857ef9d389224b338150feaf297bbb75eb824bdcf Any computer that has this package installed or running should be considered fully...

MAL-2025-47038 Malicious code in @liquid-web/models (npm)

The package @liquid-web/models was found to contain malicious code. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 94c4dab8510635c784a7216857ef9d389224b338150feaf297bbb75eb824bdcf Any computer that has this package installed or running should be considered fully...

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection

The application layer of Bluetooth Low Energy BLE is a growing source of security vulnerabilities, as developers often neglect to implement critical protections such as encryption, authentication, and freshness. While formal verification offers a principled way to check these properties, the manu...

Fraud Detection and Risk Assessment of Online Payment Transactions on E-Commerce Platforms Based on LLM and GCN Frameworks

With the rapid growth of e-commerce, online payment fraud has become increasingly complex, posing serious threats to financial security and consumer trust. Traditional detection methods often struggle to capture the intricate relational structures inherent in transactional data. This study presen...

Picklescan is Vulnerable to Unsafe Globals Check Bypass through Subclass Imports

Summary The vulnerability allows malicious actors to bypass PickleScan's unsafe globals check, leading to potential arbitrary code execution. The issue stems from PickleScan's strict check for full module names against its list of unsafe globals. By using subclasses of dangerous imports instead o...

Flow-Based Detection and Identification of Zero-Day IoT Cameras

The majority of consumer IoT devices lack mechanisms for administrators to monitor and control them, hindering tailored security policies. A key challenge is identifying whether a new device, especially a streaming IoT camera, has joined the network. We present zCamInspector, a system for...

Efficient Decoding Methods for Language Models on Encrypted Data

Large language models LLMs power modern AI applications, but processing sensitive data on untrusted servers raises privacy concerns. Homomorphic encryption HE enables computation on encrypted data for secure inference. However, neural text generation requires decoding methods like argmax and...

GHSA-6VM5-6JV9-RJPJ MONAI: Unsafe torch usage may lead to arbitrary code execution

Summary In modeldict = torch.loadfullpath, maplocation=torch.devicedevice, weightsonly=True in monai/bundle/scripts.py , weightsonly=True is loaded securely. However, insecure loading methods still exist elsewhere in the project, such as when loading checkpoints. This is a common practice when...

CVE-2025-54084

OS Command 'OS Command Injection' vulnerability in Calix GigaCenter ONT Quantenna SoC modules allows authenticated attackers with 'super' user credentials to execute arbitrary OS commands through improper input validation, potentially leading to full system compromise.This issue affects GigaCente...

CVE-2025-54084 Calix Gigacenter ONT - Command Injection

OS Command 'OS Command Injection' vulnerability in Calix GigaCenter ONT Quantenna SoC modules allows authenticated attackers with 'super' user credentials to execute arbitrary OS commands through improper input validation, potentially leading to full system compromise.This issue affects GigaCente...

CVE-2025-53913 Calix GigaCenter ONT (Quantenna SoC) - Excessive Privileges

Excessive Privileges vulnerability in Calix GigaCenter ONT Quantenna SoC modules allows Privilege Abuse.This issue affects GigaCenter ONT: 844E, 844G, 844GE, 854GE, 812G, 813G, 818G...

CVE-2025-53913

CVE-2025-53913 affects Calix GigaCenter ONT (Quantenna SoC modules). Affected models: 844E, 844G, 844GE, 854GE, 812G, 813G, 818G. Issue: Excessive privileges enabling privilege abuse in base system. Documented impact includes high confidentiality, integrity, and availability implications, with ph...

PYSEC-2025-141

MONAI Medical Open Network for AI is an AI toolkit for health care imaging. In versions up to and including 1.5.0, in modeldict = torch.loadfullpath, maplocation=torch.devicedevice, weightsonly=True in monai/bundle/scripts.py , weightsonly=True is loaded securely. However, insecure loading method...

Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees

Recent advances in Large Language Models LLMs have driven interest in automating cybersecurity penetration testing workflows, offering the promise of faster and more consistent vulnerability assessment for enterprise systems. Existing LLM agents for penetration testing primarily rely on self-guid...

Baicells多款产品 信息泄露漏洞

Baicells Nova 436Q and others are products of Baicells, Inc.Baicells Nova 436Q is an advanced dual-carrier outdoor eNodeB eNB. Baicells Nova 243 and others are products of the company.Baicells Nova 243 is a miniature base station.Baicells NEUTRINO430 is an LTE base station. An information...