CVE-2021-29438 (GCVE-0-2021-29438)
Vulnerability from cvelistv5 – Published: 2021-04-13 18:40 – Updated: 2024-08-03 22:02
VLAI
EPSS
VEX
Title
Improper Neutralization of Script-Related HTML Tags in a Web Page (Basic XSS) in @nextcloud/dialogs
Summary
The Nextcloud dialogs library (npm package @nextcloud/dialogs) before 3.1.2 insufficiently escaped text input passed to a toast. If your application displays toasts with user-supplied input, this could lead to a XSS vulnerability. The vulnerability has been patched in version 3.1.2 If you need to display HTML in the toast, explicitly pass the `options.isHTML` config flag.
Severity
4.6 (Medium)
CWE
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/nextcloud/nextcloud-dialogs/se… | x_refsource_CONFIRM |
| https://www.npmjs.com/package/%40nextcloud/dialogs | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| nextcloud | nextcloud-dialogs |
Affected:
< 3.1.2
|
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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