CVE-2026-33833
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedImproper 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.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · moderate confidenceThis is an injection vulnerability in Azure Machine Learning where special elements in output are not properly neutralized before being used by a downstream component, allowing an unauthorized attacker to perform spoofing attacks over a network.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data= 3.0.0CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Network
- Complexity
- Low
- Privileges
- None
- User interaction
- Required
- Scope
- Changed
- Confidentiality
- High
- Integrity
- Low
- Availability
- None
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:N
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Check Azure Machine Learning versionRun 'az ml version' or check the Azure portal under the Machine Learning workspace properties to confirm the installed Azure ML versionAffected if Version is exactly 3.0.0
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Identify ML pipelines in the workspaceRun 'az ml pipeline list' or use Azure ML studio to list all registered pipelines in the workspaceAffected if Any ML pipelines exist that process and output data to downstream components
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Review pipeline data sources for external inputInspect each pipeline's data inputs using 'az ml pipeline show' or examine pipeline JSON configuration files for data sources that accept user-controlled or external dataAffected if Pipelines use external data sources, user-provided inputs, or data from untrusted origins
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Examine output configuration and downstream integrationsCheck pipeline output settings and any configured downstream components (e.g., webhooks, APIs, storage sinks) that consume Azure ML outputsAffected if Pipeline outputs are passed to downstream components without explicit output encoding or validation documented
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Audit input validation settings in pipelinesReview pipeline code or YAML configuration for any input validation, sanitization, or encoding steps applied to data before output generationAffected if No input validation or encoding is implemented on data flowing through the pipeline to downstream components
You are affected if your Azure Machine Learning version is exactly 3.0.0 and you have ML pipelines that pass output to downstream components without encoding or validation on external/user-controlled inputs.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
From vendor dataImplement proper output encoding and validation for all data passed to downstream components; apply Azure security best practices and ensure ML pipelines sanitize any user-controlled or external inputs before processing.
- Consultation4.0 h
- Implementation8.0 h
- Testing6.0 h
- Review / QA4.0 h
An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $6,176.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2026-33833 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2026-33833 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Version or environment caveats, and links to real fixes
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