UBUNTU-CVE-2026-47242 (CVE-2026-47242)
Vulnerability from osv_ubuntu – Published: 2026-06-22 21:16 – Updated: 2026-07-16 18:27 – Source website
VLAI
Details
Net::IMAP implements Internet Message Access Protocol (IMAP) client functionality in Ruby. Prior to 0.6.5 and 0.5.15, when Net::IMAP#id is called with a hash argument, although the ID field value strings are correctly quoted (escaping quoted specials), they were not validated to prohibit CRLF sequences. While Net::IMAP#enable does process its arguments for aliases, it does not validate them as valid atoms (or as a list of valid atoms). The #to_s value is sent verbatim. Arguments to either command could be used by an attacker to inject arbitrary IMAP commands. This vulnerability is fixed in 0.6.5 and 0.5.15.
Severity
N/A (UNKNOWN)
References
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"aliases": [],
"details": "Net::IMAP implements Internet Message Access Protocol (IMAP) client functionality in Ruby. Prior to 0.6.5 and 0.5.15, when Net::IMAP#id is called with a hash argument, although the ID field value strings are correctly quoted (escaping quoted specials), they were not validated to prohibit CRLF sequences. While Net::IMAP#enable does process its arguments for aliases, it does not validate them as valid atoms (or as a list of valid atoms). The #to_s value is sent verbatim. Arguments to either command could be used by an attacker to inject arbitrary IMAP commands. This vulnerability is fixed in 0.6.5 and 0.5.15.",
"id": "UBUNTU-CVE-2026-47242",
"modified": "2026-07-16T18:27:47Z",
"published": "2026-06-22T21:16:00Z",
"references": [
{
"type": "REPORT",
"url": "https://ubuntu.com/security/CVE-2026-47242"
},
{
"type": "REPORT",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-47242"
},
{
"type": "REPORT",
"url": "https://github.com/ruby/net-imap/security/advisories/GHSA-46q3-7gv7-qmgg"
}
],
"related": [],
"schema_version": "1.7.0",
"severity": [
{
"score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:P/VC:N/VI:H/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
},
{
"score": "medium",
"type": "Ubuntu"
}
],
"upstream": [
"CVE-2026-47242"
]
}
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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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