# CVE-2026-33833: Azure Machine Learning Notebook Spoofing Vulnerability

> An attacker can spoof content in Azure Machine Learning Notebooks via injection, potentially misleading users.

- **Severity:** High 8.2 (`CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:N/E:U/RL:O/RC:C`)
- **Exploited in the wild:** Not known
- **Login needed:** Not needed
- **Attackable:** Over the internet
- **Victim action needed:** A user has to click or open something
- **Fix available:** No
- **Published:** 12 May 2026
- **Updated:** 10 Aug 2026
- **Also known as:** GHSA-mq64-7vwv-8j4j

## What is CVE-2026-33833?

CVE-2026-33833 is a high-severity cross-site scripting vulnerability in Microsoft Azure Machine Learning, published on 12 May 2026. An attacker can exploit it over the internet without logging in, and only if a user opens a file or follows a link.

### Official description

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.

Weakness: CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component)

## Which versions are affected by CVE-2026-33833?

It affects 1 product.


Products: Microsoft Azure Machine Learning.

## How do I fix CVE-2026-33833?

No fix has been published for CVE-2026-33833 yet. Limit exposure of the affected software until one is available.

## Is CVE-2026-33833 being exploited?

There is no known exploitation of CVE-2026-33833 in the wild and no public exploit code.

## Other vulnerabilities in Microsoft Azure Machine Learning

- [CVE-2025-49746](https://insights.sbomify.com/CVE-2025-49746/): Azure Machine Learning Elevation of Privilege Vulnerability (critical 9.9)
- [CVE-2025-49747](https://insights.sbomify.com/CVE-2025-49747/): Azure Machine Learning Elevation of Privilege Vulnerability (critical 9.9)
- [CVE-2025-30390](https://insights.sbomify.com/CVE-2025-30390/): Azure ML Compute Elevation of Privilege Vulnerability (critical 9.9)
- [CVE-2026-32207](https://insights.sbomify.com/CVE-2026-32207/): Azure Machine Learning Notebook Spoofing Vulnerability (high 8.8)
- [CVE-2026-68791](https://insights.sbomify.com/CVE-2026-68791/): Azure Machine Learning Information Disclosure Vulnerability (high 8.6)

## Fix prompt for AI coding agents

```text
Check this codebase for CVE-2026-33833 and fix it if it is affected.

What it is: CVE-2026-33833 is a high-severity cross-site scripting vulnerability in Microsoft Azure Machine Learning, published on 12 May 2026. An attacker can exploit it over the internet without logging in, and only if a user opens a file or follows a link.
Exploitation: There is no known exploitation of CVE-2026-33833 in the wild and no public exploit code.

Affected product: Microsoft Azure Machine Learning. No package-level version data is available, so check the vendor advisory linked from the reference page.

Task:
1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies.
2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it.
3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead.
4. Run the tests and summarise what changed and why.
5. If nothing in the project is affected, say so and change nothing.

Reference: https://insights.sbomify.com/CVE-2026-33833/ (Markdown: https://insights.sbomify.com/CVE-2026-33833/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2026-33833
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2026-33833
- OSV: https://osv.dev/vulnerability/CVE-2026-33833

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From sbomify Insights: https://insights.sbomify.com/CVE-2026-33833/
Summaries are generated and may contain mistakes; the official description above is the record.