CVE-2026-32732 (GCVE-0-2026-32732)
Vulnerability from cvelistv5 – Published: 2026-03-13 21:43 – Updated: 2026-03-16 20:22
VLAI
EPSS
VEX
Title
XSS in @leanprover/unicode-input-component
Summary
Lean 4 VS Code Extension is a Visual Studio Code extension for the Lean 4 proof assistant. Projects that use @leanprover/unicode-input-component are vulnerable to an XSS exploit in 0.1.9 of the package and lower. The component re-inserted text in the input element back into the input element as unescaped HTML. The issue has been resolved in 0.2.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-03-16 20:09 UTC
CWE
- CWE-80 - Improper Neutralization of Script-Related HTML Tags in a Web Page (Basic XSS)
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/leanprover/vscode-lean4/securi… | x_refsource_CONFIRM |
| https://github.com/leanprover/vscode-lean4/pull/735 | x_refsource_MISC |
| https://leanprover.zulipchat.com/#narrow/channel/… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| leanprover | vscode-lean4 |
Affected:
< 0.2.0
|
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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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