GHSA-H877-95Q5-3R86
Vulnerability from github – Published: 2026-10-09 15:31 – Updated: 2026-10-09 15:31
VLAI
Details
The Affinity by Canva application before 3.3.1 (October 2026 release) did not correctly handle incomplete UTF-8 character sequences when parsing text in Affinity document files, leading to a heap buffer over-read. A threat actor could craft an Affinity document that, when opened by a user in Affinity, could disclose the contents of adjacent heap memory in the document's text or result in an application crash.
Severity
{
"affected": [],
"aliases": [
"CVE-2026-101094"
],
"database_specific": {
"cwe_ids": [
"CWE-126"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-10-09T13:17:05Z",
"severity": "LOW"
},
"details": "The Affinity by Canva application before 3.3.1 (October 2026 release) did not correctly handle incomplete UTF-8 character sequences when parsing text in Affinity document files, leading to a heap buffer over-read. A threat actor could craft an Affinity document that, when opened by a user in Affinity, could disclose the contents of adjacent heap memory in the document\u0027s text or result in an application crash.",
"id": "GHSA-h877-95q5-3r86",
"modified": "2026-10-09T15:31:29Z",
"published": "2026-10-09T15:31:29Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-101094"
},
{
"type": "WEB",
"url": "https://trust.canva.com?tcuUid=1998378a-9134-47e9-b761-7a49d5fd6bfb"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:L/I:N/A:L",
"type": "CVSS_V3"
}
]
}
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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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