FKIE_CVE-2026-94373
Vulnerability from fkie_nvd - Published: 2026-09-21 13:17 - Updated: 2026-09-21 16:17
Severity
Summary
MISP contains a DOM-based cross-site scripting (XSS) vulnerability in the contextual menu JavaScript component. The ContextualMenu class populates HTML <option> elements by assigning user-controllable values to the innerHTML property. Because innerHTML parses and renders HTML markup, any untrusted string supplied as the option text (value.text or value) is interpreted as live DOM content rather than plain text. An attacker who can influence the data rendered in the contextual menu can inject arbitrary HTML or JavaScript that executes in the victim's browser within the MISP application origin. This may allow session hijacking, data exfiltration, or unauthorized actions performed on behalf of the authenticated user.
Version affected: <2.5.47
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"modules": [
"app/webroot/js/contextual_menu.js"
],
"product": "MISP",
"programFiles": [
"app/webroot/js/contextual_menu.js"
],
"repo": "https://github.com/MISP/MISP",
"vendor": "MISP",
"versions": [
{
"lessThan": "2.5.47",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "MISP contains a DOM-based cross-site scripting (XSS) vulnerability in the contextual menu JavaScript component. The ContextualMenu class populates HTML \u003coption\u003e elements by assigning user-controllable values to the innerHTML property. Because innerHTML parses and renders HTML markup, any untrusted string supplied as the option text (value.text or value) is interpreted as live DOM content rather than plain text. An attacker who can influence the data rendered in the contextual menu can inject arbitrary HTML or JavaScript that executes in the victim\u0027s browser within the MISP application origin. This may allow session hijacking, data exfiltration, or unauthorized actions performed on behalf of the authenticated user.\n\nVersion affected: \u003c2.5.47"
}
],
"id": "CVE-2026-94373",
"lastModified": "2026-09-21T16:17:30.017",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "HIGH",
"subIntegrityImpact": "HIGH",
"userInteraction": "PASSIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-94373",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-21T15:22:19.064596Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-21T13:17:12.757",
"references": [
{
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"url": "https://github.com/MISP/MISP/commit/b062698f2"
}
],
"sourceIdentifier": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"type": "Secondary"
}
]
}
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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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