BREW-BORGBACKUP-CVE-2017-15914 (CVE-2017-15914)
Vulnerability from osv_homebrew – Published: 2026-08-13 16:38 – Updated: 2026-09-10 18:57 – Source website
VLAI
Details
Incorrect implementation of access controls allows remote users to override repository restrictions in Borg servers 1.1.x before 1.1.3.
Severity
8.8 (High)
References
| URL | Type | |
|---|---|---|
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"upstream_fixed_in": "1.1.3"
},
"package": {
"ecosystem": "Homebrew",
"name": "borgbackup",
"purl": "pkg:brew/borgbackup"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.4.5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "git",
"upstream_evidence": [
{
"ecosystem": "GIT",
"key": "https://github.com/borgbackup/borg",
"name": "https://github.com/borgbackup/borg",
"strategy": "git",
"subject_version": "1.4.5"
},
{
"ecosystem": "PyPI",
"key": "pkg:pypi/borgbackup@1.4.5",
"name": "borgbackup",
"strategy": "registry",
"subject_version": "1.4.5"
},
{
"ecosystem": "Debian",
"key": "Debian/borgbackup",
"name": "borgbackup",
"strategy": "distro"
},
{
"ecosystem": "GIT",
"key": "upstream:https://github.com/borgbackup/borg",
"name": "https://github.com/borgbackup/borg",
"strategy": "distro",
"subject_version": "1.4.5"
},
{
"ecosystem": "PyPI",
"key": "upstream:pkg:pypi/borgbackup@1.4.5",
"name": "borgbackup",
"strategy": "distro",
"subject_version": "1.4.5"
}
]
},
"details": "Incorrect implementation of access controls allows remote users to override repository restrictions in Borg servers 1.1.x before 1.1.3.",
"id": "BREW-borgbackup-CVE-2017-15914",
"modified": "2026-09-10T18:57:15Z",
"published": "2026-08-13T16:38:22Z",
"references": [
{
"type": "ADVISORY",
"url": "http://borgbackup.readthedocs.io/en/stable/changes.html#version-1-1-3-2017-11-27"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"upstream": [
"CVE-2017-15914",
"GHSA-8q8v-28rm-qw4w",
"PYSEC-2018-105"
]
}
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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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