GHSA-Q7CG-457F-VX79
Vulnerability from github – Published: 2026-06-11 13:27 – Updated: 2026-06-12 19:28
VLAI
Summary
joi has an uncaught RangeError on deeply nested input through recursive `link()` schemas
Details
Impact
Denial of service via untrapped exception in services validating user-supplied JSON / object input with recursive link schemas.
The blast radius depends on how the application invokes joi:
- Highest impact: validate() called without try/catch in a request handler would cause an unhandled exception, potentially crashing the process.
- Lower impact: validateAsync() or validate() inside a try/catch, the validation fails, but the error type is RangeError rather than a structured ValidationError, complicating error handling.
Patches
Upgrade to version >= 18.2.1.
Workarounds
Try/catch the validation to avoid uncaught exceptions.
References
- Pull request: hapijs/joi#3113
Severity
5.3 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "npm",
"name": "joi"
},
"ranges": [
{
"events": [
{
"introduced": "18.0.0"
},
{
"fixed": "18.2.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "npm",
"name": "joi"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "17.13.4"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-48038"
],
"database_specific": {
"cwe_ids": [
"CWE-248",
"CWE-400"
],
"github_reviewed": true,
"github_reviewed_at": "2026-06-11T13:27:32Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "### Impact\nDenial of service via untrapped exception in services validating user-supplied JSON / object input with recursive link schemas. \n\nThe blast radius depends on how the application invokes joi:\n- Highest impact: `validate()` called without `try/catch` in a request handler would cause an unhandled exception, potentially crashing the process.\n- Lower impact: `validateAsync()` or `validate()` inside a `try/catch`, the validation fails, but the error type is `RangeError` rather than a structured `ValidationError`, complicating error handling.\n\n### Patches\nUpgrade to version \u003e= 18.2.1.\n\n### Workarounds\nTry/catch the validation to avoid uncaught exceptions.\n\n### References\n- Pull request: hapijs/joi#3113",
"id": "GHSA-q7cg-457f-vx79",
"modified": "2026-06-12T19:28:27Z",
"published": "2026-06-11T13:27:32Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/hapijs/joi/security/advisories/GHSA-q7cg-457f-vx79"
},
{
"type": "WEB",
"url": "https://github.com/hapijs/joi/pull/3113"
},
{
"type": "WEB",
"url": "https://github.com/hapijs/joi/commit/2392713d3e9dd91ba752ac0c96e0eaf3d24b9a11"
},
{
"type": "PACKAGE",
"url": "https://github.com/hapijs/joi"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "joi has an uncaught RangeError on deeply nested input through recursive `link()` schemas"
}
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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
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- Not confirmed: The user expressed doubt about the validity of the vulnerability.
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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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