CVE-2026-34941 (GCVE-0-2026-34941)
Vulnerability from cvelistv5 – Published: 2026-04-09 18:29 – Updated: 2026-04-10 14:11
VLAI
EPSS
VEX
Title
Wasmtime has a Heap OOB read in component model UTF-16 to latin1+utf16 string transcoding
Summary
Wasmtime is a runtime for WebAssembly. Prior to 24.0.7, 36.0.7, 42.0.2, and 43.0.1, Wasmtime contains a vulnerability where when transcoding a UTF-16 string to the latin1+utf16 component-model encoding it would incorrectly validate the byte length of the input string when performing a bounds check. Specifically the number of code units were checked instead of the byte length, which is twice the size of the code units. This vulnerability can cause the host to read beyond the end of a WebAssembly's linear memory in an attempt to transcode nonexistent bytes. In Wasmtime's default configuration this will read unmapped memory on a guard page, terminating the process with a segfault. Wasmtime can be configured, however, without guard pages which would mean that host memory beyond the end of linear memory may be read and interpreted as UTF-16. A host segfault is a denial-of-service vulnerability in Wasmtime, and possibly being able to read beyond the end of linear memory is additionally a vulnerability. Note that reading beyond the end of linear memory requires nonstandard configuration of Wasmtime, specifically with guard pages disabled. This vulnerability is fixed in 24.0.7, 36.0.7, 42.0.2, and 43.0.1.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-10 14:11 UTC
CWE
- CWE-125 - Out-of-bounds Read
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/bytecodealliance/wasmtime/secu… | x_refsource_CONFIRM |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| bytecodealliance | wasmtime |
Affected:
< 24.0.7
Affected: >= 25.0.0, < 36.0.7 Affected: >= 37.0.0, < 42.0.2 Affected: >= 43.0.0, < 44.0.1 |
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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