GHSA-XGHW-P77P-3R7X
Vulnerability from github – Published: 2026-08-14 19:24 – Updated: 2026-08-14 19:24
VLAI
Summary
Fabric CA Developer's Guide: LDAP Injection via Unescaped Username in GetUser Filter
Details
When fabric-ca is configured with an LDAP backend, the username from HTTP Basic authentication is included in an LDAP uid search filter without proper escaping. An unauthenticated attacker with network access to the CA enrollment endpoint could exploit this to perform LDAP injection before password validation, and potentially steer authentication attempts toward a victim account.
Recommendation
- All users of fabric-ca with an LDAP backend should update to a fixed version.
- For users not using an LDAP backend, no action is required.
Severity
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 1.5.20"
},
"package": {
"ecosystem": "Go",
"name": "github.com/hyperledger/fabric-ca"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.5.21"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-53658"
],
"database_specific": {
"cwe_ids": [
"CWE-90"
],
"github_reviewed": true,
"github_reviewed_at": "2026-08-14T19:24:57Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "When fabric-ca is configured with an LDAP backend, the username from HTTP Basic authentication is included in an LDAP uid search filter without proper escaping. An unauthenticated attacker with network access to the CA enrollment endpoint could exploit this to perform LDAP injection before password validation, and potentially steer authentication attempts toward a victim account.\n\n### Recommendation\n\n- All users of fabric-ca with an LDAP backend should update to a fixed version.\n- For users not using an LDAP backend, no action is required.",
"id": "GHSA-xghw-p77p-3r7x",
"modified": "2026-08-14T19:24:57Z",
"published": "2026-08-14T19:24:57Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/hyperledger/fabric-ca/security/advisories/GHSA-xghw-p77p-3r7x"
},
{
"type": "WEB",
"url": "https://github.com/hyperledger/fabric-ca/commit/d379df823534d56dec0166a6da8f0415e3beee24"
},
{
"type": "PACKAGE",
"url": "https://github.com/hyperledger/fabric-ca"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Fabric CA Developer\u0027s Guide: LDAP Injection via Unescaped Username in GetUser Filter"
}
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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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