CVE-2025-53763: Azure Databricks Privilege Escalation and Mitigations

Microsoft Security Response Center (MSRC) now lists CVE-2025-53763 as an improper access control vulnerability in Azure Databricks that can be exploited to achieve elevation of privilege over the network, a finding that demands urgent attention from cloud and data platform administrators.

Background / Overview​

Azure Databricks is a managed data analytics platform built on Apache Spark and widely used for ETL, machine learning, model training, and data engineering workloads. Because Databricks frequently touches sensitive data stores, identity systems, and external services, any elevation-of-privilege bug in its control or API plane can produce high-impact outcomes for organizations that rely on it.
Microsoft’s Update Guide entry for CVE-2025-53763 describes the root cause simply as improper access control, and characterizes the impact as an attacker being able to elevate privileges over a network. The advisory is concise and appears primarily as a vendor advisory entry rather than a long technical write-up; administrators are therefore reliant on the vendor’s guidance to identify affected configurations and recommended fixes.
Because public technical detail is limited at the time of publication, defenders should treat the MSRC advisory as authoritative while also applying layered compensations consistent with Azure and Databricks best practices. Related past Databricks advisories (for example, prior JDBC driver fixes) and Microsoft’s ongoing Azure security advisories show a pattern where access-control flaws can be weaponized as part of privilege-escalation chains; those precedents are useful context when assessing impact and response priorities. (kb.databricks.com, tenable.com)

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Why this matters: risk model and likely attack scenarios​

Improper access control in a managed service like Azure Databricks typically falls into one of a few patterns:

• API endpoints or control-plane operations fail to validate authorization (what a principal is allowed to do), even when authentication (who the principal is) is correct.
• Service-to-service delegation or token exchange flows (for example, managed identities, short-lived tokens, or Unity Catalog integrations) contain logic that trusts an intermediate principal too broadly.
• Resource scoping or RBAC rules are misapplied, allowing a lower-privilege identity to perform actions reserved for higher-privilege roles.

When combined with Databricks’ role in modern data pipelines, those failures can be exploited to:

• Promote a low-privilege user or service principal to higher privileges in the workspace control plane.
• Access or modify notebooks, jobs, or runtime configurations that are normally protected.
• Retrieve secrets or access connectors (e.g., storage mount secrets, Key Vault-backed scopes) that lead to data exfiltration.
• Pivot from Databricks compute to customer-managed cloud resources (storage accounts, databases, or key vaults).

Because MSRC’s summary states the vulnerability allows privilege elevation over the network, defenders must assume that an attacker with network access and some valid identity (for example, a user account, service principal, or compromised token) could exploit the flaw remotely — making it materially more dangerous than purely local issues.

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What Microsoft’s advisory actually says (and what it omits)​

Microsoft’s Update Guide entry lists:

• The CVE identifier: CVE-2025-53763.
• A concise description: Improper access control in Azure Databricks allows an unauthorized attacker to elevate privileges over a network.

What is not present in the brief MSRC entry (or is not easily visible in the public advisory):

• No detailed exploitation steps or proof-of-concept code.
• No published CVSS score or explicit exploitability metrics on the MSRC page itself.
• No exhaustive list of affected product versions or configuration permutations in human-readable form within the short advisory.

Administrators should therefore treat the advisory as authoritative but incomplete; rely on Microsoft’s guidance for patching and on Databricks’ own security notices for product-specific remediation details where available. When Microsoft publishes brief advisories in the Security Update Guide, the page may be client-side rendered — and administrators should view it from a modern browser or patch-management tooling to see the full metadata.

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Cross-checks and independent context​

Independent public coverage specifically naming CVE-2025-53763 remains limited at the moment of writing. That is not unusual for recently published vendor advisories: NVD and other aggregators often lag, and specialist vendor pages may be client-side rendered or not immediately indexable. The following points provide important context and precedent:

• Databricks has previously published security bulletins addressing driver- and runtime-level vulnerabilities (for example, the Databricks JDBC vulnerability fixed under CVE-2024-49194), demonstrating the vendor’s process for issuing and patching product-specific advisories. These historical fixes show how a Databricks runtime/component issue can require both vendor action and customer remediation (for example restarting long-lived clusters or updating local drivers). Use those precedents when planning Databricks-specific remediation steps. (kb.databricks.com, tenable.com)
• Microsoft’s Azure ecosystem has seen a string of improper-authorization and elevation-of-privilege advisories across diverse services in 2024–2025. Many of those were network-exploitable when combined with an initial authentication foothold, underlining the real-world risk model for EoP defects in hosted cloud services. Responding to CVE-2025-53763 should therefore follow established Azure incident-response patterns. (darkreading.com, zeropath.com)
• If third-party feeds (for example, NVD, Tenable, or vendor advisory aggregators) have not yet populated the entry for CVE-2025-53763, that does not mean the vulnerability is unimportant — only that indexing is delayed. Security teams must treat the MSRC advisory as the primary source and verify patch identifiers through Microsoft’s Update Guide or databricks’ product notices.

Because independent corroboration for the exact technical details of CVE-2025-53763 is sparse, any claim about exploit technique beyond Microsoft’s short description should be flagged as tentative. The responsible approach is to base urgent defensive steps on the possibility of remote, authenticated privilege elevation and to assume the worst-case blast radius until proven otherwise.

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Immediate (0–24 hour) emergency checklist​

• Locate the MSRC advisory and confirm whether your tenant/Databricks workspaces are listed as affected in the Microsoft Update Guide. Use a modern browser to view the page (client-side rendering may hide content in older clients).
• Inventory Databricks workspaces, service principals, and user roles that can initiate or modify jobs, clusters, or workspace-level settings. Prioritize workspaces that have broad external connectivity or contain sensitive data.
• Restrict network and management-plane access to Databricks workspaces using IP restrictions, Private Link, or firewall rules. Reduce exposure of control-plane endpoints to the public internet.
• Enforce or tighten least privilege immediately: remove excessive role assignments and revoke or rotate any stale service principal secrets or personal access tokens (PATs). Databricks’ own guidance on token management and PAT monitoring is a useful operational control.
• Enable enhanced logging and telemetry: turn on audit logging for workspace operations, job activity, and cluster creation; stream these logs to a central SIEM or Azure Monitor Log Analytics workspace for retrospective hunting.
• If Microsoft or Databricks publishes an out-of-band mitigation or workaround (for example, disabling a vulnerable API or setting), apply it via tested change-control processes.

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24–72 hour remediation and hardening actions​

• Apply vendor patches: When Microsoft or Databricks publishes a code fix or a patched service rollout, schedule immediate deployment and test in staging first. Some Databricks runtime or driver updates require cluster restarts.
• Review service principal and managed identity assignments: ensure that any identity used by Databricks notebooks, jobs, or runtimes is scoped to the minimum privileges necessary, and avoid granting subscription-wide Owner roles to compute-creators or runtime identities. Consider replacing long-lived secrets with short-lived tokens and managed identities where possible.
• Harden Unity Catalog and storage access: if your organization uses Unity Catalog, Delta Sharing, or mounted storage, review mounting practices (avoid mounting blob containers to DBFS in ways that expose long-lived secrets) and adopt RBAC-based, Key Vault-backed secret scopes. Databricks has been moving toward more secure token- and OAuth-based patterns for data access; evaluate those options.
• Network segmentation and Private Link: place Databricks compute and any attached data stores into appropriately segmented VNets and use Private Link to remove public ingress paths to sensitive endpoints.

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Detection and hunting guidance​

Implement the following detection approaches in Azure Monitor, Sentinel, or your SIEM:

• Alert on unusual privilege escalations or role assignments for Databricks service principals, especially if they occur without corresponding change-control tickets.
• Monitor for unexpected cluster restarts, new cluster images, or job submissions outside typical maintenance windows.
• Identify data-access spikes from Databricks identities: large listings, unusual blob/container reads, or excessive Key Vault Get operations from runtime identities.
• Hunt for anomalous activity originating from notebooks or jobs that were recently created or modified by low-privilege users.

Provide sampling KQL patterns (adapt to environment):

• Look for unexpected role assignments:
  1.) AuditLogs
  | where OperationName contains "Add role assignment" and TargetResources contains "Databricks"
• Look for secret access from runtime identities:
  1.) AzureDiagnostics
  | where ResourceType == "KEYVAULTS" and OperationName == "SecretGet" and Caller contains "databricks"
  (Adjust queries to match your logging schema and retention windows.)

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Mitigations beyond patching: controls to reduce blast radius​

• Strict RBAC and identity hygiene: avoid wildcard permissions in Azure RBAC; ensure service principals used by Databricks have tightly scoped permissions and are rotated regularly. Research into Azure RBAC wildcard overreach demonstrates the practical risk of broad permissions in cloud RBAC systems.
• Principle of least privilege for developers and CI/CD pipelines: treat Databricks notebooks, job definitions, and workspace-level settings as code that must be reviewed and permissioned.
• Secrets management: prefer Key Vault-backed secret scopes and audit access; disallow embedding of long-lived credentials in notebooks or repositories.
• Immutable job/artifact execution: where feasible, use snapshots or packaged artifacts rather than executing code directly from mutable external storage to reduce the risk of code-modification attacks (Databricks and other cloud vendors have moved toward snapshot-based execution patterns in some services).

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Organizational response playbook (concise)​

• Triage: identify all Databricks workspaces and service principals. Prioritize those tied to critical data.
• Contain: reduce exposure (IP restrictions / Private Link), rotate tokens, and tighten RBAC.
• Patch: apply vendor updates as they are published; restart clusters or update drivers as required.
• Hunt: run focused hunts for signs of post‑compromise behavior and collect forensic artifacts (audit logs, cluster logs, job run history).
• Remediate: remove backdoors, revoke compromised identities, and update process controls to prevent recurrence.
• Report: coordinate with legal and compliance teams for any required disclosure, and follow regulatory guidance if sensitive data may have been exposed.

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Strengths and limitations of Microsoft’s advisory and vendor communications​

Strengths:

• MSRC publishes authoritative CVE entries and is the canonical source for Microsoft‑side remediation status; treat the Update Guide as primary for affected builds and official fixes.
• Microsoft’s advisory model is designed to notify tenants and push service-side fixes where possible for hosted services.

Limitations / Risks:

• Brief advisories may omit exploit technique, CVSS, or precise affected-version metadata in early publication; third-party aggregators can lag in indexing. That increases operational uncertainty and forces defenders to adopt conservative assumptions.
• If Databricks requires cluster/operator actions (for example a restart or driver update), customers must schedule those steps — vendor-managed services do not always push client-side updates automatically.

Because public independent corroboration of the specific technical details for CVE-2025-53763 remains limited at the time of this writing, any operational claim beyond Microsoft’s stated description should be labeled speculative and validated against vendor Q&As and subsequent MSRC updates.

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Practical examples of consequences — hypothetical but realistic​

• A low‑privilege data-ops user with rights to create simple jobs could, by exploiting an improper access control flaw, escalate to workspace admin and modify job definitions to exfiltrate datasets to an attacker-controlled storage endpoint.
• A compromised CI runner with write access to a workspace artifact store could inject malicious initialization scripts into clusters; if Databricks executes mutable code or reads runtime artifacts directly from storage, this could permit code execution under elevated workspace identities.
• Theft of short-lived tokens or misuse of a managed identity could enable lateral movement to storage accounts and Key Vaults, particularly if RBAC is overly permissive in subscription-scoped roles.

These are concrete risk paths seen in prior incidents involving access-control failures in cloud-hosted data services; they are the reason the vendor advisory should be prioritized even when technical details are light. (kb.databricks.com, zeropath.com)

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Final recommendations (quick reference)​

• Treat CVE-2025-53763 as a high-priority, network-exploitable elevation-of-privilege advisory until vendor guidance narrows the scope.
• Immediately inventory Databricks workspaces, service principals, and tokens; rotate and revoke unnecessary or stale credentials.
• Harden network access to Databricks control planes (Private Link, IP restrictions) and adopt least-privilege RBAC for all identities.
• Enable and centralize audit logging; prepare hunts for privilege escalation and suspect data access patterns.
• Apply vendor patches and follow Databricks’ runtime/driver update guidance (some fixes require cluster restarts).

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Conclusion​

CVE-2025-53763 is a vendor-reported improper access control defect in Azure Databricks that can enable privilege elevation across the network. Microsoft’s MSRC entry is the authoritative starting point for affected customers, but the advisory is terse; defenders must therefore combine rapid inventory and containment actions with vigilant logging and an expedited patch-and-restart plan. Historical Databricks advisories and broader Azure EoP patterns show that these flaws are commonly chained into larger incidents, so conservative, layered defenses — network segmentation, strict RBAC, secrets hygiene, and centralized monitoring — are imperative while vendors publish fuller technical details and patches. (msrc.microsoft.com, kb.databricks.com)

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Source: MSRC Security Update Guide - Microsoft Security Response Center