CVE-2026-72743 (GCVE-0-2026-72743)
Vulnerability from cvelistv5 – Published: 2026-08-10 20:06 – Updated: 2026-08-10 20:06 X_Open Source
VLAI
EPSS
VEX
Title
SQLBot 1.10.0 SQText Dashboard Component Stored XSS via v-html
Summary
SQLBot through 1.10.0, fixed in commit c3f40a5, contains a stored cross-site scripting vulnerability in the SQText dashboard component that renders TinyMCE output via v-html without sanitization. Attackers who can modify dashboard text widget content can inject arbitrary HTML and JavaScript that executes for all users viewing the dashboard.
Severity
5.4 (Medium)
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/dataease/SQLBot/issues/1308 | technical-descriptionexploit |
| https://github.com/dataease/SQLBot/pull/1309 | issue-tracking |
| https://github.com/dataease/SQLBot/commit/c3f40a5… | patch |
| https://www.vulncheck.com/advisories/sqlbot-sqtex… | third-party-advisory |
Impacted products
Date Public
2026-08-05 00:00
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}
}
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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.
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.
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