# CVE-2026-33833: Microsoft Azure Machine Learning injection vulnerability

Source: https://junglewise.ai/threats/cve-2026-33833-microsoft-azure-machine-learning-injection-vulnerability  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2026-05-12. Updated: 2026-06-18  
License: CC BY 4.0 with a link back

CVE-2026-33833 · Severity: high · CVSS 8.2 · Published 2026-05-12

A vulnerability in Microsoft Azure Machine Learning could allow an attacker to trick users into interacting with malicious content. Azure Machine Learning is a cloud service used by data scientists and developers to build, train, and deploy machine learning models. If exploited, an attacker could spoof legitimate communications or interfaces, potentially leading to the theft of sensitive information or unauthorized access to user accounts.

Technologies: [Microsoft Azure Machine Learning](https://junglewise.ai/threats/technologies/azure-machine-learning). Vendors: [Microsoft](https://junglewise.ai/threats/vendors/microsoft).

## Quick answers

**Is CVE-2026-33833 exploited in the wild?** No. Junglewise Threat Intelligence has no report of CVE-2026-33833 being exploited in the wild.

**How severe is CVE-2026-33833?** High severity, with a CVSS score of 8.2, published 12 May 2026.

**Which products and versions are affected?** Microsoft Azure Machine Learning 3.0.0 up to (but not including) 1.7.6.

**Is there a fix for CVE-2026-33833?** No fixed version is recorded yet. Check the vendor's advisory in the references below. If you run it, Junglewise drafts a mitigation that fits your setup and applies it once you approve, with senior security engineers behind it.

**How is CVE-2026-33833 attacked?** It is attacked over the network, in a hosted service.

**Am I affected by CVE-2026-33833?** Check whether you run Microsoft Azure Machine Learning at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

## Technical details

An injection vulnerability (CWE-74) exists in Microsoft Azure Machine Learning due to improper neutralization of special elements in output passed to downstream components. An unauthenticated attacker can exploit this over the network by sending specially crafted data that results in spoofing. While the attack vector is network-based, it requires user interaction (UI:R) and results in a scope change (S:C), indicating the vulnerability may allow the attacker to impact components beyond the immediate security scope of the application. Successful exploitation primarily impacts confidentiality (C:H) and integrity (I:L). Microsoft has addressed this in version 1.7.6.

## Affected products

- Microsoft Azure Machine Learning 3.0.0 up to (but not including) 1.7.6

## Timeline

- 2026-05-12: advisory: Initial publication by Microsoft and NVD
- 2026-06-18: other: NIST initial analysis and CPE configuration added

## References

- [https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833](https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833)

## Related threats

- [Microsoft Azure Machine Learning incorrect authorization](https://junglewise.ai/threats/cve-2026-68791-microsoft-azure-machine-learning-incorrect-authorization)
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