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CVE-2026-33833 is a Markdown injection vulnerability in Microsoft Azure Machine Learning notebooks caused by improper neutralization of special elements in output used by a downstream component. The issue affects the notebook rendering path in the Azure ML web interface, where user-supplied Markdown cell content is not sufficiently sanitized or encoded before browser rendering. A remote, unauthenticated attacker can craft a malicious notebook containing injected markup or styling content and induce a victim to open or view it. When rendered in the victim's Azure ML session, the injected content can spoof interface elements and expose sensitive information visible within that session. The vulnerability is classified as CWE-74 and has been described by Microsoft as a spoofing issue with changed scope due to impact extending beyond the rendering component into the broader web session context.
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A spoofing vulnerability in Azure Machine Learning notebooks caused by improper neutralization of special elements in output used by a downstream component, allowing an unauthorized network attacker to perform spoofing when a user views a maliciously crafted notebook.
A Markdown injection vulnerability in Microsoft Azure Machine Learning Notebooks that allows unauthenticated attackers to spoof content and exfiltrate sensitive information from the Azure ML web interface when a user opens a crafted notebook.
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Every observed campaign linking this CVE to a named adversary.
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Cross-references every affected SKU, including bundled OEM variants.
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