GHSA-G48R-38GH-835C
Vulnerability from github – Published: 2026-08-13 21:36 – Updated: 2026-08-13 21:36
VLAI
Details
Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A specially crafted, malformed payload submitted to a Kibana visualization feature by an authenticated user holding only low-privileged access is not correctly validated before use. Processing the request causes unbounded memory growth in the Kibana process, which is terminated by the host once available memory is exhausted. Kibana then becomes unavailable to all users until the service is restarted.
Severity
6.5 (Medium)
{
"affected": [],
"aliases": [
"CVE-2026-72659"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-13T20:17:26Z",
"severity": "MODERATE"
},
"details": "Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A specially crafted, malformed payload submitted to a Kibana visualization feature by an authenticated user holding only low-privileged access is not correctly validated before use. Processing the request causes unbounded memory growth in the Kibana process, which is terminated by the host once available memory is exhausted. Kibana then becomes unavailable to all users until the service is restarted.",
"id": "GHSA-g48r-38gh-835c",
"modified": "2026-08-13T21:36:09Z",
"published": "2026-08-13T21:36:09Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-72659"
},
{
"type": "WEB",
"url": "https://discuss.elastic.co/t/kibana-8-19-20-9-4-5-security-update-esa-2026-100/389519"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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