BREW-KRANE-CVE-2026-33210 (GHSA-3M6G-2423-7CP3)
Vulnerability from osv_homebrew – Published: 2026-08-13 17:01 – Updated: 2026-08-13 17:01 – Source website
VLAI
Summary
Ruby JSON has a format string injection vulnerability
Details
Impact
A format string injection vulnerability than that lead to denial of service attacks or information disclosure, when the allow_duplicate_key: false parsing option is used to parse user supplied documents.
This option isn't the default, if you didn't opt-in to use it, you are not impacted.
Patches
Patched in 2.19.2.
Workarounds
The issue can be avoided by not using the allow_duplicate_key: false parsing option.
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": null,
"range_state": "affected",
"resource": "json",
"resource_purl": "pkg:gem/json@2.18.0",
"upstream_fixed_in": "2.19.2"
},
"package": {
"ecosystem": "Homebrew",
"name": "krane",
"purl": "pkg:brew/krane"
},
"ranges": [
{
"events": [
{
"introduced": "0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "RubyGems",
"key": "pkg:gem/json@2.18.0",
"name": "json",
"resource": "json",
"strategy": "registry",
"subject_version": "2.18.0"
}
]
},
"details": "### Impact\n\nA format string injection vulnerability than that lead to denial of service attacks or information disclosure, when the `allow_duplicate_key: false` parsing option is used to parse user supplied documents. \n\nThis option isn\u0027t the default, if you didn\u0027t opt-in to use it, you are not impacted.\n\n### Patches\n\nPatched in `2.19.2`.\n\n### Workarounds\n\nThe issue can be avoided by not using the `allow_duplicate_key: false` parsing option.",
"id": "BREW-krane-CVE-2026-33210",
"modified": "2026-08-13T17:01:45Z",
"published": "2026-08-13T17:01:45Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/ruby/json/security/advisories/GHSA-3m6g-2423-7cp3"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-33210"
},
{
"type": "PACKAGE",
"url": "https://github.com/ruby/json"
},
{
"type": "WEB",
"url": "https://github.com/rubysec/ruby-advisory-db/blob/master/gems/json/CVE-2026-33210.yml"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:L/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Ruby JSON has a format string injection vulnerability",
"upstream": [
"GHSA-3m6g-2423-7cp3",
"CVE-2026-33210"
]
}
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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
- 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.
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- 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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