brew-bbot-cve-2026-12566
Vulnerability from osv_homebrew
Published
2026-08-13 16:37
Modified
2026-09-09 23:43
Summary
Details
The docker_pull module uses the realm parameter from a Docker registry's WWW-Authenticate response header as the authentication endpoint without validation. An attacker in a man-in-the-middle position between bbot and a Docker registry could modify this header to redirect the authentication request to an arbitrary endpoint, potentially leaking authentication tokens.
Severity
References
| URL | Type | |
|---|---|---|
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"upstream_fixed_in": "2.8.5"
},
"package": {
"ecosystem": "Homebrew",
"name": "bbot",
"purl": "pkg:brew/bbot"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.0.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "git",
"upstream_evidence": [
{
"ecosystem": "GIT",
"key": "https://github.com/blacklanternsecurity/bbot",
"name": "https://github.com/blacklanternsecurity/bbot",
"strategy": "git",
"subject_version": "3.0.2"
},
{
"ecosystem": "PyPI",
"key": "pkg:pypi/bbot@3.0.2",
"name": "bbot",
"strategy": "registry",
"subject_version": "3.0.2"
}
]
},
"details": "The docker_pull module uses the realm parameter from a Docker registry\u0027s WWW-Authenticate response header as the authentication endpoint without validation. An attacker in a man-in-the-middle position between bbot and a Docker registry could modify this header to redirect the authentication request to an arbitrary endpoint, potentially leaking authentication tokens.",
"id": "BREW-bbot-CVE-2026-12566",
"modified": "2026-09-09T23:43:32Z",
"published": "2026-08-13T16:37:10Z",
"references": [
{
"type": "FIX",
"url": "https://github.com/blacklanternsecurity/bbot/commit/c2f4bc0f4"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:N/A:N",
"type": "CVSS_V3"
}
],
"upstream": [
"CVE-2026-12566",
"GHSA-3mp7-vp6j-2mxx",
"PYSEC-2026-2391"
]
}
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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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