CVE-2023-26487 (GCVE-0-2023-26487)
Vulnerability from cvelistv5 – Published: 2023-03-03 23:47 – Updated: 2025-02-25 15:01
VLAI
EPSS
VEX
Title
Vega has cross-site scripting vulnerability in `lassoAppend` function
Summary
Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs.`lassoAppend' function accepts 3 arguments and internally invokes `push` function on the 1st argument specifying array consisting of 2nd and 3rd arguments as `push` call argument. The type of the 1st argument is supposed to be an array, but it's not enforced. This makes it possible to specify any object with a `push` function as the 1st argument, `push` function can be set to any function that can be access via `event.view` (no all such functions can be exploited due to invalid context or signature, but some can, e.g. `console.log`). The issue is that`lassoAppend` doesn't enforce proper types of its arguments. This issue opens various XSS vectors, but exact impact and severity depends on the environment (e.g. Core JS `setImmediate` polyfill basically allows `eval`-like functionality). This issue was patched in 5.23.0.
Severity
6.5 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-25 14:31 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/vega/vega/security/advisories/… | x_refsource_CONFIRM |
| https://github.com/vega/vega/commit/01adb034f2472… | x_refsource_MISC |
| https://github.com/vega/vega/releases/tag/v5.23.0 | x_refsource_MISC |
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"source": {
"advisory": "GHSA-w5m3-xh75-mp55",
"discovery": "UNKNOWN"
},
"title": "Vega has cross-site scripting vulnerability in `lassoAppend` function"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2023-26487",
"datePublished": "2023-03-03T23:47:28.486Z",
"dateReserved": "2023-02-23T23:22:58.575Z",
"dateUpdated": "2025-02-25T15:01:54.570Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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