CVE-2026-100104 (GCVE-0-2026-100104)
Vulnerability from cvelistv5 – Published: 2026-10-13 01:05 – Updated: 2026-10-13 01:05
VLAI
EPSS
VEX
Title
Server-Side Request Forgery (SSRF) in GitLab
Summary
GitLab has remediated an issue in GitLab CE/EE affecting all versions from 10.3 before 19.2.8, 19.3 before 19.3.5, and 19.4 before 19.4.2 that, under certain conditions, could have allowed an authenticated user to perform server-side request forgery and reach internal network resources due to a time-of-check to time-of-use race condition in URL validation during repository import operations.
Severity
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
Impacted products
{
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"cpes": [
"cpe:2.3:a:gitlab:gitlab:*:*:*:*:*:*:*:*"
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"repo": "https://gitlab.com/gitlab-org/gitlab",
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}
],
"metrics": [
{
"cvssV3_1": {
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"attackVector": "NETWORK",
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"baseScore": 3.5,
"baseSeverity": "LOW",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
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"scope": "CHANGED",
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],
"providerMetadata": {
"dateUpdated": "2026-10-13T01:05:36.165Z",
"orgId": "ceab7361-8a18-47b1-92ba-4d7d25f6715a",
"shortName": "GitLab"
},
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},
{
"url": "https://docs.gitlab.com/releases/patches/patch-release-gitlab-19-4-2-released/"
}
],
"solutions": [
{
"lang": "en",
"value": "Upgrade to versions 19.2.8, 19.3.5, 19.4.2 or above."
}
],
"title": "Server-Side Request Forgery (SSRF) in GitLab"
}
},
"cveMetadata": {
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"cveId": "CVE-2026-100104",
"datePublished": "2026-10-13T01:05:36.165Z",
"dateReserved": "2026-09-25T10:34:25.697Z",
"dateUpdated": "2026-10-13T01:05:36.165Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
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"epss": "0.00188",
"percentile": "0.07787"
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"nvd": {
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{
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"status": "affected",
"version": "19.3",
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{
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"version": "19.4",
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"cveTags": [],
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}
],
"id": "CVE-2026-100104",
"lastModified": "2026-10-13T16:17:14.080",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
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"confidentialityImpact": "LOW",
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}
}
}
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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