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CVE-2026-40920 – Privilege Escalation – Apache Ranger ≤ 2.8.0

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Summary

CVE-2026-40920 is a privilege escalation vulnerability in Apache Ranger, a data governance and access-control platform used to manage security policies across big-data ecosystems (e.g., Hadoop, Hive, Kafka). The flaw allows an attacker to elevate privileges by manipulating a URL parameter, and carries a Critical CVSS score of 9.8. It affects all Apache Ranger versions up to and including 2.8.0.

Technical details

  • Root cause: Apache Ranger fails to properly validate/authorize a URL parameter, allowing improper privilege management (CWE-269), improper input validation (CWE-20), and improper authentication (CWE-287).
  • Trigger condition: An attacker crafts a request containing a manipulated URL parameter against a reachable Ranger instance.
  • Attack vector: Network-based, requiring no authentication (PR:N) and no user interaction (UI:N).
  • Impact: Full compromise of confidentiality, integrity, and availability, consistent with unauthorized privilege elevation within Ranger’s access-control model.

Affected software

  • Apache Ranger versions 0 through 2.8.0 (inclusive)

Severity

  • CVSS v3.1 Base Score: 9.8 (Critical)
  • Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Mitigation and recommended actions

  • Immediate: Upgrade to Apache Ranger version 2.9.0, which resolves this vulnerability.
  • If upgrading is not immediately possible: restrict network exposure of the Ranger admin interface to trusted internal networks and monitor access logs for anomalous requests containing unexpected URL parameters until the upgrade can be applied.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Set-Cookie response header: RANGERADMINSESSIONID=
  • Rendered page title: Ranger - Sign In
  • Raw response body: scripts/prelogin/XAPrelogin.js, images/ranger_logo.png

References

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1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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