CVE-2026-100673 (GCVE-0-2026-100673)
Vulnerability from cvelistv5 – Published: 2026-09-26 13:23 – Updated: 2026-09-30 20:11
VLAI
EPSS
VEX
Title
Grav Data Manager before 1.4.5 Stored XSS via item-detail view
Summary
The Grav Data Manager plugin (getgrav/grav-plugin-datamanager) versions 1.0.1 through 1.4.4 render stored data entries in the item-detail view (admin/templates/partials/item.html.twig) without escaping, applying Twig's `raw` filter — in some cases after a striptags('<br>') call that PHP's strip_tags() bypasses by preserving allowed tags together with their attributes. An unauthenticated visitor who submits a front-end form whose submissions are saved to user/data can store an HTML payload that executes as JavaScript in the session and origin of an administrator who later opens that entry in the classic admin panel, running with that administrator's privileges and CSRF token. Execution occurs without further interaction for list values (such as checkbox or multi-select fields) and on hover for ordinary text fields. Sites using the Grav 2.0 Admin Next interface are not affected, because it renders the same data through a separate, correctly escaping code path. The issue is fixed in Data Manager 1.4.5.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-30 18:43 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/getgrav/grav/security/advisori… | vendor-advisory |
| https://www.vulncheck.com/advisories/grav-data-ma… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| getgrav | grav-plugin-datamanager |
Affected:
1.0.1 , < 1.4.5
(semver)
Unaffected: 1.4.5 (semver) |
guessed |
Date Public
2026-09-10 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.
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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