FKIE_CVE-2026-103237
Vulnerability from fkie_nvd - Published: 2026-09-30 10:17 - Updated: 2026-09-30 18:18
Severity
Summary
MISP contains an improper input validation vulnerability in its ORM save path. When a user submits data through various endpoints (attribute add/edit, event edit, free-text import, sighting capture, shadow attribute proposal, event report creation, object reference add, user admin edit), the application sanitizes the flat record by stripping the primary key and pinning the event_id or object_id to the caller's context. However, the underlying ORM's set() method gives priority to a nested key whose name matches the model alias and discards the outer scalar fields.
An authenticated user with basic write permissions can exploit this by embedding a nested block under the model alias key inside their request. The sanitization logic (id removal, event_id pinning) is applied to the outer record, but the ORM binds to the inner record instead, which carries an attacker-chosen id and event_id. This allows the attacker to overwrite, re-parent, or soft-delete rows belonging to other organizations or events they have no read access to.
Impact:
- Cross-tenant data integrity compromise (attribute values rewritten, objects re-parented to attacker events, rows soft-deleted)
- Affects multiple entity types: Attribute, Object, EventReport, Sighting, AttributeTag, ShadowAttribute
- Requires only a low-privilege authenticated account with perm_add
Affected versions: <2.5.48
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"cpes": [
"cpe:2.3:a:misp:misp:*:*:*:*:*:*:*:*"
],
"modules": [
"AttributesController",
"EventReportsController",
"EventsController",
"ObjectReferencesController",
"ShadowAttributesController",
"UsersController",
"AppModel",
"Event model",
"MispAttribute model",
"MispObject model",
"ShadowAttribute model",
"Sighting model"
],
"product": "MISP",
"repo": "https://github.com/MISP/MISP",
"vendor": "MISP",
"versions": [
{
"lessThan": "2.5.48",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "MISP contains an improper input validation vulnerability in its ORM save path. When a user submits data through various endpoints (attribute add/edit, event edit, free-text import, sighting capture, shadow attribute proposal, event report creation, object reference add, user admin edit), the application sanitizes the flat record by stripping the primary key and pinning the event_id or object_id to the caller\u0027s context. However, the underlying ORM\u0027s set() method gives priority to a nested key whose name matches the model alias and discards the outer scalar fields.\n\nAn authenticated user with basic write permissions can exploit this by embedding a nested block under the model alias key inside their request. The sanitization logic (id removal, event_id pinning) is applied to the outer record, but the ORM binds to the inner record instead, which carries an attacker-chosen id and event_id. This allows the attacker to overwrite, re-parent, or soft-delete rows belonging to other organizations or events they have no read access to.\n\nImpact:\n\n- Cross-tenant data integrity compromise (attribute values rewritten, objects re-parented to attacker events, rows soft-deleted)\n\n- Affects multiple entity types: Attribute, Object, EventReport, Sighting, AttributeTag, ShadowAttribute\n\n- Requires only a low-privilege authenticated account with perm_add\n\nAffected versions: \u003c2.5.48"
}
],
"id": "CVE-2026-103237",
"lastModified": "2026-09-30T18:18:15.917",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.3,
"baseSeverity": "HIGH",
"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": "NONE",
"subIntegrityImpact": "HIGH",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:N/SC:N/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": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-103237",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-30T17:08:29.034418Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-30T10:17:16.687",
"references": [
{
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"url": "https://github.com/MISP/MISP/commit/9485ae40d"
}
],
"sourceIdentifier": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-20"
},
{
"lang": "en",
"value": "CWE-639"
}
],
"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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