CVE-2026-75831 (GCVE-0-2026-75831)
Vulnerability from cvelistv5 – Published: 2026-08-18 11:19 – Updated: 2026-08-18 13:55
VLAI
EPSS
VEX
Title
Grav before 2.0.15 Stored XSS via audio/video source URL
Summary
Grav before 2.0.15 contains a stored cross-site scripting vulnerability in the audio and video media rendering through the sourceParsedownElement method. The media URL fragment is concatenated unescaped into rawHtml source elements, allowing attackers to inject arbitrary HTML and JavaScript that executes in viewers' sessions.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-18 13:55 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/getgrav/grav/security/advisori… | vendor-advisory |
| https://github.com/getgrav/grav/commit/aba291a59c… | patch |
| https://www.vulncheck.com/advisories/grav-before-… | third-party-advisory |
Impacted products
Date Public
2026-08-03 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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