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CVE Vulnerability Database
Vulnerability Database/CVE-2026-33107

CVE-2026-33107: Azure Databricks SSRF Vulnerability

CVE-2026-33107 is a server-side request forgery flaw in Microsoft Azure Databricks that enables unauthorized attackers to elevate privileges over a network. This article covers technical details, affected versions, and mitigation.

Published: April 10, 2026

CVE-2026-33107 Overview

CVE-2026-33107 is a critical Server-Side Request Forgery (SSRF) vulnerability affecting Microsoft Azure Databricks. This vulnerability allows an unauthorized attacker to craft malicious requests that the server processes on behalf of the attacker, potentially leading to privilege escalation over a network. SSRF vulnerabilities in cloud environments are particularly dangerous as they can be leveraged to access internal metadata services, cloud credentials, and other sensitive resources that should not be externally accessible.

Critical Impact

Unauthorized attackers can exploit this SSRF vulnerability to elevate privileges over a network, potentially gaining access to sensitive cloud resources, internal services, and metadata endpoints within the Azure Databricks environment.

Affected Products

  • Microsoft Azure Databricks
  • Azure Databricks (all versions prior to patch)
  • Cloud deployments utilizing Azure Databricks services

Discovery Timeline

  • April 3, 2026 - CVE-2026-33107 published to NVD
  • April 6, 2026 - Last updated in NVD database

Technical Details for CVE-2026-33107

Vulnerability Analysis

This vulnerability is classified under CWE-918 (Server-Side Request Forgery), which occurs when a web application fetches remote resources without properly validating the user-supplied URL. In the context of Azure Databricks, this SSRF flaw enables attackers to manipulate server-side requests to access internal resources that would otherwise be protected by network boundaries.

The vulnerability allows unauthenticated attackers to submit specially crafted requests to the Azure Databricks service. When processed, these requests cause the server to make HTTP requests to attacker-controlled or internal destinations. In cloud environments like Azure, this can be particularly devastating as attackers may target the Instance Metadata Service (IMDS) at 169.254.169.254 to retrieve cloud credentials, access tokens, and configuration data.

Root Cause

The root cause of CVE-2026-33107 lies in insufficient validation and sanitization of user-supplied URLs or parameters that influence server-side HTTP requests within Azure Databricks. The application fails to properly restrict the destinations that the server can connect to, allowing attackers to redirect requests to arbitrary internal or external endpoints. This lack of URL allowlisting or proper input validation enables the SSRF attack vector.

Attack Vector

The attack is network-based and requires no authentication or user interaction, making it particularly dangerous. An attacker can exploit this vulnerability by:

  1. Identifying an endpoint in Azure Databricks that accepts user-controlled URL parameters
  2. Crafting a malicious request that specifies an internal target (such as cloud metadata endpoints or internal APIs)
  3. Submitting the request to the vulnerable Azure Databricks service
  4. The server processes the request and connects to the attacker-specified destination
  5. Response data from internal services is returned to the attacker or used for privilege escalation

This vulnerability mechanism involves manipulating server-side HTTP request destinations. The attacker exploits the lack of URL validation to force the server to make requests to internal cloud infrastructure endpoints. In Azure environments, this could potentially expose managed identity tokens, subscription metadata, and other sensitive cloud configuration details. For detailed technical information, refer to the Microsoft Security Update Guide.

Detection Methods for CVE-2026-33107

Indicators of Compromise

  • Unusual outbound HTTP requests from Azure Databricks instances to internal IP ranges (e.g., 169.254.169.254, 10.x.x.x, 172.16.x.x)
  • HTTP requests to cloud metadata endpoints originating from application servers
  • Unexpected access patterns to Azure Instance Metadata Service (IMDS)
  • Log entries showing server-side requests to localhost or private network addresses

Detection Strategies

  • Implement network monitoring to detect unusual traffic patterns from Azure Databricks workspaces to internal metadata endpoints
  • Configure Azure Monitor and Log Analytics to alert on suspicious API calls and privilege changes
  • Deploy web application firewalls (WAF) with SSRF detection rules to identify malicious request patterns
  • Enable audit logging for all Azure Databricks workspace activities and API interactions

Monitoring Recommendations

  • Monitor Azure Activity Logs for unexpected privilege escalation events or role assignments
  • Set up alerts for HTTP requests targeting the Azure IMDS endpoint (169.254.169.254)
  • Review network security group (NSG) flow logs for anomalous outbound connection attempts
  • Implement continuous monitoring of Azure Databricks workspace access patterns and authentication events

How to Mitigate CVE-2026-33107

Immediate Actions Required

  • Review the Microsoft Security Update Guide for CVE-2026-33107 and apply any available patches
  • Audit Azure Databricks workspace configurations and access controls
  • Implement network segmentation to restrict outbound traffic from Databricks instances
  • Enable Azure Defender for cloud workloads to detect potential exploitation attempts

Patch Information

Microsoft has published security guidance for this vulnerability. Organizations using Azure Databricks should consult the Microsoft CVE-2026-33107 Update Guide for specific remediation steps and any available patches. As Azure Databricks is a managed cloud service, Microsoft may apply fixes automatically, but organizations should verify their deployment status and configuration.

Workarounds

  • Implement strict network egress controls using Azure Network Security Groups to block outbound requests to sensitive internal addresses
  • Configure Azure Private Link for Azure Databricks to limit network exposure
  • Enable managed identity restrictions and limit the permissions associated with Databricks workspace identities
  • Deploy Azure Firewall or a third-party firewall to inspect and filter outbound traffic from Databricks clusters

Organizations should contact Microsoft support for environment-specific mitigation guidance while awaiting comprehensive patches.

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

  • Vulnerability Details
  • TypeSSRF

  • Vendor/TechMicrosoft Azure Databricks

  • SeverityCRITICAL

  • CVSS Score9.8

  • EPSS Probability0.05%

  • Known ExploitedNo
  • CVSS Vector
  • CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
  • Impact Assessment
  • ConfidentialityLow
  • IntegrityNone
  • AvailabilityHigh
  • CWE References
  • CWE-918
  • Vendor Resources
  • Microsoft CVE-2026-33107 Update Guide
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