Azure Machine Learning Notebook Spoofing Vulnerability

Improper neutralization of special elements in output used by a downstream component 'injection' in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network...

PT-2026-40141

Name of the Vulnerable Software and Affected Versions Azure Machine Learning affected versions not specified Description Improper neutralization of special elements in output used by a downstream component allows an unauthorized attacker to perform spoofing over a network. This issue can lead to...

KLA91034 Multiple vulnerabilities in Microsoft Azure

Multiple vulnerabilities were found in Microsoft Azure. Malicious users can exploit these vulnerabilities to spoof user interface, bypass security restrictions, gain privileges. Below is a complete list of vulnerabilities: 1. A spoofing vulnerability in Azure Machine Learning Notebook can be...

Convolutional-Neural-Networks for Deanonymisation of I2P Traffic

This study investigates the potential for deanonymizing services within the Invisible Internet Project I2P network through passive traffic analysis and machine learning techniques. The primary objective is to identify distinctive patterns in I2P traffic despite the encryption of its payload. To...

Machine Learning Engineering Open Book 安全漏洞

Machine Learning Engineering Open Book is a collection of methodologies for training and fine-tuning large language models developed by Stas Bekman. There is a security vulnerability in Machine Learning Engineering Open Book. This vulnerability arises from the use of the torch-checkpoint-shrink.p...

Microsoft Azure Machine Learning 注入漏洞

Microsoft Azure Machine Learning is a machine learning service provided by Microsoft Corporation in the United States. There is an injection vulnerability present in Microsoft Azure Machine Learning. Attackers utilize this vulnerability to carry out phishing attacks...

CVE-2026-32207

Improper neutralization of input during web page generation 'cross-site scripting' in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network...

EUVD-2026-28447

Improper neutralization of input during web page generation 'cross-site scripting' in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network...

CVE-2026-32207

Improper neutralization of input during web page generation 'cross-site scripting' in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network...

CVE-2026-32207 Azure Machine Learning Notebook Spoofing Vulnerability

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CVE-2026-32207

Improper neutralization of input during web page generation 'cross-site scripting' in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network...

CVE-2026-32207

CVE-2026-32207 concerns an XSS vulnerability in Azure Machine Learning Notebook/Notebook UI where improper neutralization of input during web page generation enables an unauthenticated attacker to spoof content over the network. Underlying cause: improper sanitization of user-controlled input in ...

CVE-2026-32207 Azure Machine Learning Notebook Spoofing Vulnerability

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Azure Machine Learning Notebook Spoofing Vulnerability

Improper neutralization of input during web page generation 'cross-site scripting' in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network...

KLA91030 Multiple vulnerabilities in Microsoft Azure

Multiple vulnerabilities were found in Microsoft Azure. Malicious users can exploit these vulnerabilities to gain privileges, execute arbitrary code, bypass security restrictions, spoof user interface. Below is a complete list of vulnerabilities: 1. An elevation of privilege vulnerability in Azur...

Microsoft Azure Machine Learning 跨站脚本漏洞

Microsoft Azure Machine Learning is a machine learning service provided by Microsoft Corporation in the United States. Microsoft Azure Machine Learning has a cross-site scripting vulnerability, which stems from improper input during the web page generation process. This vulnerability could allow...

TUANDROMD-X: Advanced Entropy and Visual Analytics Dataset for Enhanced Malware Detection and Classification

Malware and malware-based attacks are becoming more prevalent and complex. Attackers regularly come up with new techniques that have the ability to evade conventional and signature-based malware defense. In order to address such threats, there is an increasing demand for advanced and better defen...

PT-2026-38576

Name of the Vulnerable Software and Affected Versions Azure Machine Learning affected versions not specified Description Improper neutralization of input during web page generation in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network. This issue is a form o...

Zero Day Attacks: Novel Behaviour or Novel Vulnerability?

Zero-day attacks pose severe cybersecurity risks due to their high success rates and stealth. Because signature-based approaches struggle to detect such attacks, building Intrusion Detection Systems IDSs for detecting zero-day attacks is essential. We contend that for an IDS to be effective it mu...

CVE-2026-7213 ef10007 MLOps_MCP save_file Tool fastmcp_server.py path traversal

A vulnerability was detected in ef10007 MLOpsMCP 1.0.0. This impacts an unknown function of the file fastmcpserver.py of the component savefile Tool. The manipulation of the argument filename/destination results in path traversal. The attack may be performed from remote. The exploit is now public...