CVE-2026-105784 (GCVE-0-2026-105784)
Vulnerability from cvelistv5 – Published: 2026-10-05 23:11 – Updated: 2026-10-06 13:16
VLAI
EPSS
VEX
Title
Joplin whiteboard card rendering allows CSS injection into application chrome
Summary
Joplin is an open source note-taking and to-do application that organises notes and lists into notebooks. Prior to 3.7.13, selecting a note containing a jsoncanvas fence causes the whiteboard text and file-node components in packages/app-desktop/gui/NoteEditor/NoteBody/WhiteboardEditor/nodes/TextNode.tsx and packages/app-desktop/gui/NoteEditor/NoteBody/WhiteboardEditor/nodes/FileNode.tsx to render card content with the full Markdown renderer. The components insert the resulting HTML into the main application document through dangerouslySetInnerHTML. A malicious note can inject style elements and remote CSS imports that modify trusted application chrome, signal when the note is opened, and potentially disclose exposed attribute values. Content Security Policy blocks inline script execution, so the supported impact is CSS injection and UI redressing rather than code execution. This issue is fixed in version 3.7.13.
Severity
4.6 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-06 13:16 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/laurent22/joplin/security/advi… | x_refsource_CONFIRM |
| https://github.com/laurent22/joplin/pull/16275 | x_refsource_MISC |
| https://github.com/laurent22/joplin/commit/7fb9ec… | x_refsource_MISC |
| https://github.com/laurent22/joplin/releases/tag/… | x_refsource_MISC |
Impacted products
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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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