CVE-2026-33833: Azure Machine Learning Notebook Spoofing Vulnerability
CVE-2026-33833 is a spoofing vulnerability in Azure Machine Learning Notebook, rated Important by Microsoft, with a CVSS 3.1 base score of 8.2 (High). An attacker can exploit it remotely over the network, without any privileges and only if a user takes an action. Microsoft has not reported exploitation in the wild and rates exploitation as less likely. The EPSS model estimates a 0.50% probability of exploitation activity in the next 30 days, higher than 43% of all scored vulnerabilities. Microsoft released the fix on 12 May 2026 in the May 2026 Patch Tuesday. It affects 1 product in 1 product family (Azure).
Key facts
- CVE ID
- CVE-2026-33833
- Severity
- High CVSS 8.2
- Microsoft severity
- Important
- Impact
- Spoofing
- Exploited in the wild
- No
- Publicly disclosed
- No
- Exploitation likelihood
- Less Likely
- Weakness
- CWE-74
- EPSS
- 0.50% (percentile 43%)
- CISA KEV
- Not listed
- Released
- Last updated
- Patch Tuesday
- May 2026 Patch Tuesday
- Product families
- Azure
CVSS score and vector
Microsoft scores CVE-2026-33833 at 8.2 (temporal 7.1) using CVSS 3.1. Vector: 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
| Metric | Value |
|---|---|
| Attack vector | Network |
| Attack complexity | Low |
| Privileges required | None |
| User interaction | Required |
| Scope | Changed |
| Confidentiality impact | High |
| Integrity impact | Low |
| Availability impact | None |
| Exploit code maturity | Unproven |
| Remediation level | Official fix |
| Report confidence | Confirmed |
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.
Frequently asked questions (Microsoft)
According to the CVSS metrics, successful exploitation of this vulnerability could lead to major loss of confidentiality (C:H), and some loss of integrity (I:L), but no loss of availability (A:N). What does that mean for this vulnerability?
An attacker who successfully exploited this vulnerability could view sensitive information, (Confidentiality), and make some changes to disclosed information (Integrity), but they would not be able to affect Availability.
According to the CVSS metric, user interaction is required (UI:R). What interaction would the user have to do?
Exploitation would require a user to open or view a maliciously crafted notebook so that the affected content is rendered.
According to the CVSS metric, a successful exploitation could lead to a scope change (S:C). What does this mean for this vulnerability?
An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities.
How could an attacker exploit this vulnerability?
An attacker could create or import a specially crafted Azure ML notebook containing malicious styling content in a Markdown cell, which may be rendered when the notebook is viewed and could expose sensitive information displayed within the Azure ML web interface.
Affected products (1)
Azure
| Product | Security update | Type | Fixed build | Restart |
|---|---|---|---|---|
| Azure Machine Learning | Release Notes | Security Update | 1.7.6 | No |
NIST NVD data
- NVD status
- Analyzed
- NVD CVSS
- 8.2 (HIGH)
- NVD weakness
- CWE-74
- Published to NVD
- NVD last modified
Affected configurations (CPE)
| Product | Vulnerable versions |
|---|---|
| azure machine learning 3.0.0 | all listed versions |
References
- https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833 (Vendor Advisory)
Acknowledgments
- Jianyang Song
Revision history
| Version | Date | Description |
|---|---|---|
| 1.0 | Information published. |