CVE-2026-76837 (GCVE-0-2026-76837)
Vulnerability from cvelistv5 – Published: 2026-08-24 17:36 – Updated: 2026-08-24 18:12
VLAI
EPSS
VEX
Title
Baserow before 2.3.0 Stored Cross-Site Scripting via Rich Text Mention Display Name
Summary
Baserow interpolates a user's display name into the rich-text mention markup without HTML encoding. PATCH /api/user/account/ stores the first_name value verbatim, and the mention renderer in web-frontend/modules/core/editor/mention.js builds its element with a template literal that places the name into a data-label attribute and the element body unescaped. A name containing a double quote closes that attribute and the opening tag, so following markup lands in the element content. The result is rendered through v-html by the rich-text field components, so any rich-text cell mentioning the account executes the stored script for every workspace member who views the table, without a click. Any workspace member, at the lowest permission level, can set the name and reach every other member of the workspace, and the payload persists until the name is changed or the mentioning row is removed. Version 2.3.0 escapes the value before interpolation.
Severity
6.4 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-24 18:11 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/baserow/baserow | product |
| https://github.com/baserow/baserow/pull/5618 | issue-tracking |
| https://github.com/baserow/baserow/commit/a870dc0d38c9 | patch |
| https://github.com/baserow/baserow/blob/2.2.2/web… | technical-description |
| https://www.vulncheck.com/advisories/baserow-befo… | third-party-advisory |
Impacted products
Date Public
2026-06-30 00:00
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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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