Vulnerability in Elastic Kibana (CVE-2026-72671)
Summary
Vulnerability in Elastic Kibana (CVE-2026-72671). Risk of unauthorized operations or information disclosure.
Original description
The description as published by the source.
A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jobs and data frame analytics jobs without the trained model privilege can therefore remove a trained model from a space. The model itself is not deleted and remains available in its other spaces, and the change can be reversed by a suitably privileged user.
Source: NIST National Vulnerability Database NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2026-72671 has been found in Elastic Kibana.
Risk of unauthorized operations or information disclosure. CVSS score: 4.3/10.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "Elastic Kibana CVE-2026-72671" on the vendor's site.
CVE-2026-72671 (Elastic Kibana) — CWE-862 / CVSS v3 4.3
Attack vector: remote (network-reachable) / no user interaction
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
A vulnerability (CWE-862) exists in Elastic Kibana.
Check the vendor advisory for the affected versions of Elastic Kibana.
Severity: Medium (CVSS 4.3/10). Risk of unauthorized operations or information disclosure.
Update to the patched release per vendor advisory.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'Kibana' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
-
1Identify exposure identify
grep -r 'Kibana' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
Kibanaを grep し、稼働しているサービス・バージョンを把握する。 -
2Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
References
- advisory discuss.elastic.co
- web nvd.nist.gov
- web github.com