CVE-2026-41167 (GCVE-0-2026-41167)
Vulnerability from cvelistv5 – Published: 2026-04-22 20:39 – Updated: 2026-04-23 13:46
VLAI
EPSS
VEX
Title
Jellystat has SQL Injection that leads to to Remote Code Execution
Summary
Jellystat is a free and open source Statistics App for Jellyfin. Prior to version 1.1.10, multiple API endpoints in Jellystat build SQL queries by interpolating unsanitized request-body fields directly into raw SQL strings. An authenticated user can inject arbitrary SQL via `POST /api/getUserDetails` and `POST /api/getLibrary`, enabling full read of any table in the database - including `app_config`, which stores the Jellystat admin credentials, the Jellyfin API key, and the Jellyfin host URL. Because the vulnerable call site dispatches via `node-postgres`'s simple query protocol (no parameter array is passed), stacked queries are allowed, which escalates the injection from data disclosure to arbitrary command execution on the PostgreSQL host via `COPY ... TO PROGRAM`. Under the role shipped by the project's `docker-compose.yml` (a PostgreSQL superuser), no additional privileges are required to reach the RCE primitive. Version 1.1.10 contains a fix.
Severity
9.1 (Critical)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-23 13:45 UTC
CWE
- CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/CyferShepard/Jellystat/securit… | x_refsource_CONFIRM |
| https://github.com/CyferShepard/Jellystat/commit/… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| CyferShepard | Jellystat |
Affected:
< 1.1.10
|
guessed |
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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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