FKIE_CVE-2026-26030
Vulnerability from fkie_nvd - Published: 2026-02-19 17:24 - Updated: 2026-06-17 10:25
Severity
Summary
Semantic Kernel, Microsoft's semantic kernel Python SDK, has a remote code execution vulnerability in versions prior to 1.39.4, specifically within the `InMemoryVectorStore` filter functionality. The problem has been fixed in version `python-1.39.4`. Users should upgrade this version or higher. As a workaround, avoid using `InMemoryVectorStore` for production scenarios.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| microsoft | semantic_kernel | * |
{
"affected": [
{
"affectedData": [
{
"product": "semantic-kernel",
"vendor": "microsoft",
"versions": [
{
"status": "affected",
"version": "\u003c 1.39.4"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:microsoft:semantic_kernel:*:*:*:*:*:python:*:*",
"matchCriteriaId": "C6E2587D-AC15-4660-BC94-3B2D03FD88E9",
"versionEndExcluding": "1.39.4",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Semantic Kernel, Microsoft\u0027s semantic kernel Python SDK, has a remote code execution vulnerability in versions prior to 1.39.4, specifically within the `InMemoryVectorStore` filter functionality. The problem has been fixed in version `python-1.39.4`. Users should upgrade this version or higher. As a workaround, avoid using `InMemoryVectorStore` for production scenarios."
},
{
"lang": "es",
"value": "Semantic Kernel, el SDK de Python de kernel sem\u00e1ntico de Microsoft, tiene una vulnerabilidad de ejecuci\u00f3n remota de c\u00f3digo en versiones anteriores a la 1.39.4, espec\u00edficamente dentro de la funcionalidad de filtro de \u0027InMemoryVectorStore\u0027. El problema ha sido solucionado en la versi\u00f3n \u0027python-1.39.4\u0027. Los usuarios deber\u00edan actualizar a esta versi\u00f3n o una superior. Como soluci\u00f3n alternativa, evite usar \u0027InMemoryVectorStore\u0027 para escenarios de producci\u00f3n."
}
],
"id": "CVE-2026-26030",
"lastModified": "2026-06-17T10:25:37.857",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.9,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.1,
"impactScore": 6.0,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-26030",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-02-20T04:55:50.393336Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-02-19T17:24:50.487",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Issue Tracking",
"Patch"
],
"url": "https://github.com/microsoft/semantic-kernel/pull/13505"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/microsoft/semantic-kernel/releases/tag/python-1.39.4"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Vendor Advisory"
],
"url": "https://github.com/microsoft/semantic-kernel/security/advisories/GHSA-xjw9-4gw8-4rqx"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-94"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
Loading…
Loading…
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.
Loading…
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.
Loading…
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.
Loading…