Azure Databricks SSRF Vulnerability (CVE-2026-33107) Allows Privilege Escalation

CVE-2026-33107 describes a critical server-side request forgery (SSRF) vulnerability affecting Azure Databricks. This vulnerability allows an unauthenticated attacker to potentially elevate their privileges within the network. Successful exploitation could allow an attacker to access sensitive data, modify configurations, or potentially gain complete control over the Databricks environment. The vulnerability was published on April 2nd, 2026. Due to the nature of SSRF, this vulnerability could be exploited remotely, making it a high-risk issue for organizations utilizing Azure Databricks. This vulnerability matters because it can lead to significant data breaches, service disruption, and compromise of sensitive resources managed within the Azure Databricks environment.

Attack Chain

1. The attacker identifies an endpoint within the Azure Databricks environment vulnerable to SSRF.
2. The attacker crafts a malicious HTTP request targeting an internal resource. The request is designed to exploit the SSRF vulnerability.
3. The Databricks server, processing the crafted request, unwittingly sends it to the specified internal resource.
4. The internal resource responds to the Databricks server with data intended only for internal consumption.
5. The attacker leverages the SSRF vulnerability to bypass authentication or authorization checks, gaining access to the internal resource.
6. The attacker escalates privileges by abusing the compromised internal resource or service. This may involve modifying configurations, accessing restricted data, or executing privileged commands.
7. The attacker uses the elevated privileges to move laterally within the network, compromising additional resources.
8. The attacker achieves their final objective, such as data exfiltration, denial of service, or complete control of the Azure Databricks environment.

Impact

Successful exploitation of CVE-2026-33107 could lead to significant privilege escalation within an Azure Databricks environment. An attacker could potentially gain unauthorized access to sensitive data, modify critical system configurations, or even achieve complete control over the Databricks cluster. This could result in data breaches, service disruptions, and substantial financial losses. The exact number of potential victims and the scope of the impact would depend on the specific configurations and data stored within the targeted Azure Databricks environment. Given the critical nature of Databricks for data analytics, the impact on organizations relying on this service can be substantial.

Recommendation

• Apply the security update provided by Microsoft to patch CVE-2026-33107 immediately on all Azure Databricks instances.
• Implement network segmentation to limit the impact of potential SSRF exploits.
• Deploy the Sigma rule Detect Suspicious Databricks Outbound Connections to identify potential SSRF attempts.
• Monitor webserver logs for unusual outbound connections originating from Azure Databricks servers.
• Review and restrict access to internal resources within the Azure Databricks environment.
• Implement strict input validation and sanitization on all user-supplied data to prevent SSRF attacks.