MSRC_CVE-2026-33833
Vulnerability from csaf_microsoft - Published: 2026-05-12 07:00 - Updated: 2026-05-12 07:00Summary
Azure Machine Learning Notebook Spoofing Vulnerability
Severity
Important
Notes
Additional Resources: To determine the support lifecycle for your software, see the Microsoft Support Lifecycle: https://support.microsoft.com/lifecycle
Disclaimer: The information provided in the Microsoft Knowledge Base is provided \"as is\" without warranty of any kind. Microsoft disclaims all warranties, either express or implied, including the warranties of merchantability and fitness for a particular purpose. In no event shall Microsoft Corporation or its suppliers be liable for any damages whatsoever including direct, indirect, incidental, consequential, loss of business profits or special damages, even if Microsoft Corporation or its suppliers have been advised of the possibility of such damages. Some states do not allow the exclusion or limitation of liability for consequential or incidental damages so the foregoing limitation may not apply.
Customer Action: Required. The vulnerability documented by this CVE requires customer action to resolve.
CWE-74
- Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')
Affected products
Fixed
1 product
| Product | Identifier | Version | Remediation |
|---|---|---|---|
|
Azure Machine Learning 1.7.6
Azure Machine Learning
|
1.7.6 |
Known affected
1 product
| Product | Identifier | Version | Remediation |
|---|---|---|---|
|
Azure Machine Learning <1.7.6
Azure Machine Learning
|
<1.7.6 |
Vendor Fix
fix
|
Threats
Impact
Spoofing
Exploit Status
Publicly Disclosed:No;Exploited:No;Latest Software Release:Exploitation Less Likely
References
7 references
Acknowledgments
Jianyang Song
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"title": "Additional Resources"
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{
"category": "legal_disclaimer",
"text": "The information provided in the Microsoft Knowledge Base is provided \\\"as is\\\" without warranty of any kind. Microsoft disclaims all warranties, either express or implied, including the warranties of merchantability and fitness for a particular purpose. In no event shall Microsoft Corporation or its suppliers be liable for any damages whatsoever including direct, indirect, incidental, consequential, loss of business profits or special damages, even if Microsoft Corporation or its suppliers have been advised of the possibility of such damages. Some states do not allow the exclusion or limitation of liability for consequential or incidental damages so the foregoing limitation may not apply.",
"title": "Disclaimer"
},
{
"category": "general",
"text": "Required. The vulnerability documented by this CVE requires customer action to resolve.",
"title": "Customer Action"
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"publisher": {
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"contact_details": "secure@microsoft.com",
"name": "Microsoft Security Response Center",
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"references": [
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"category": "self",
"summary": "CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability - HTML",
"url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833"
},
{
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"summary": "CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability - CSAF",
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"url": "https://support.microsoft.com/lifecycle"
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{
"category": "external",
"summary": "Common Vulnerability Scoring System",
"url": "https://www.first.org/cvss"
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"title": "Azure Machine Learning Notebook Spoofing Vulnerability",
"tracking": {
"current_release_date": "2026-05-12T07:00:00.000Z",
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"summary": "Information published."
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"product_tree": {
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"name": "\u003c1.7.6",
"product": {
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},
{
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"product_id": "12152"
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"vulnerabilities": [
{
"cve": "CVE-2026-33833",
"cwe": {
"id": "CWE-74",
"name": "Improper Neutralization of Special Elements in Output Used by a Downstream Component (\u0027Injection\u0027)"
},
"notes": [
{
"category": "general",
"text": "Microsoft",
"title": "Assigning CNA"
},
{
"category": "faq",
"text": "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.",
"title": "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?"
},
{
"category": "faq",
"text": "Exploitation would require a user to open or view a maliciously crafted notebook so that the affected content is rendered.",
"title": "According to the CVSS metric, user interaction is required (UI:R). What interaction would the user have to do?"
},
{
"category": "faq",
"text": "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.",
"title": "According to the CVSS metric, a successful exploitation could lead to a scope change (S:C). What does this mean for this vulnerability?"
},
{
"category": "faq",
"text": "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.",
"title": "How could an attacker exploit this vulnerability?"
}
],
"product_status": {
"fixed": [
"12152"
],
"known_affected": [
"1"
]
},
"references": [
{
"category": "self",
"summary": "CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability - HTML",
"url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833"
},
{
"category": "self",
"summary": "CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability - CSAF",
"url": "https://msrc.microsoft.com/csaf/advisories/2026/msrc_cve-2026-33833.json"
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],
"remediations": [
{
"category": "vendor_fix",
"date": "2026-05-12T07:00:00.000Z",
"details": "1.7.6:Security Update:https://dev.azure.com/devdiv/OnlineServices/_artifacts/feed/AzureNotebooksEntry@Local/Npm/@azure-notebooks/versions/overview",
"product_ids": [
"1"
],
"url": "https://dev.azure.com/devdiv/OnlineServices/_artifacts/feed/AzureNotebooksEntry@Local/Npm/@azure-notebooks/versions/overview"
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"environmentalsScore": 0.0,
"exploitCodeMaturity": "UNPROVEN",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"remediationLevel": "OFFICIAL_FIX",
"reportConfidence": "CONFIRMED",
"scope": "CHANGED",
"temporalScore": 7.1,
"userInteraction": "REQUIRED",
"vectorString": "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",
"version": "3.1"
},
"products": [
"1"
]
}
],
"threats": [
{
"category": "impact",
"details": "Spoofing"
},
{
"category": "exploit_status",
"details": "Publicly Disclosed:No;Exploited:No;Latest Software Release:Exploitation Less Likely"
}
],
"title": "Azure Machine Learning Notebook Spoofing Vulnerability"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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