FKIE_CVE-2026-49338
Vulnerability from fkie_nvd - Published: 2026-06-19 19:16 - Updated: 2026-06-23 15:42
Severity
Summary
gonic is a music streaming server / free-software subsonic server API implementation. Prior to version 0.21.0, the Subsonic API endpoints `/rest/deletePlaylist.view` and `/rest/getPlaylist.view` perform no per-resource authorization. Once authenticated as any user (admin or not), an attacker can delete any playlist owned by any other user (including admin) by passing its `id` and read the full contents (name, comment, song list) of any other user's **private** (non-public) playlist by passing its `id`. The Subsonic playlist `id` is `base64url("<userID>/<filename>.m3u")`. Because filenames are user-supplied or time-derived and the `userID` is a small integer, IDs are guessable and frequently exposed (e.g. a previously-public playlist that was later made private still has the same ID). This breaks the multi-user trust boundary of gonic: a low-privileged user can wipe an administrator's curated playlists, and a user can exfiltrate any private playlist they obtain an ID for. The issue was fixed in commit `6dd71e6a3c966867ef8c900d359a7df75789f410`, which is part of version 0.21.0.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "gonic",
"vendor": "sentriz",
"versions": [
{
"status": "affected",
"version": "\u003c 0.21.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "gonic is a music streaming server / free-software subsonic server API implementation. Prior to version 0.21.0, the Subsonic API endpoints `/rest/deletePlaylist.view` and `/rest/getPlaylist.view` perform no per-resource authorization. Once authenticated as any user (admin or not), an attacker can delete any playlist owned by any other user (including admin) by passing its `id` and read the full contents (name, comment, song list) of any other user\u0027s **private** (non-public) playlist by passing its `id`. The Subsonic playlist `id` is `base64url(\"\u003cuserID\u003e/\u003cfilename\u003e.m3u\")`. Because filenames are user-supplied or time-derived and the `userID` is a small integer, IDs are guessable and frequently exposed (e.g. a previously-public playlist that was later made private still has the same ID). This breaks the multi-user trust boundary of gonic: a low-privileged user can wipe an administrator\u0027s curated playlists, and a user can exfiltrate any private playlist they obtain an ID for. The issue was fixed in commit `6dd71e6a3c966867ef8c900d359a7df75789f410`, which is part of version 0.21.0."
}
],
"id": "CVE-2026-49338",
"lastModified": "2026-06-23T15:42:30.483",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 4.2,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-49338",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-06-23T02:20:58.415088Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-06-19T19:16:36.557",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/sentriz/gonic/commit/6dd71e6"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sentriz/gonic/security/advisories/GHSA-hmgp-w9jm-vp95"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-285"
},
{
"lang": "en",
"value": "CWE-639"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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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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