FKIE_CVE-2021-24023
Vulnerability from fkie_nvd - Published: 2021-06-03 15:15 - Updated: 2026-06-17 03:39
Severity
7.8 (High) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/
Summary
An improper input validation in FortiAI v1.4.0 and earlier may allow an authenticated user to gain system shell access via a malicious payload in the "diagnose" command.
References
| URL | Tags | ||
|---|---|---|---|
| psirt@fortinet.com | https://fortiguard.com/advisory/FG-IR-21-033 | Vendor Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | https://fortiguard.com/advisory/FG-IR-21-033 | Vendor Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| fortinet | fortiai_firmware | * | |
| fortinet | fortiai_3500f | - |
{
"affected": [
{
"affectedData": [
{
"product": "Fortinet FortiAI",
"vendor": "Fortinet",
"versions": [
{
"status": "affected",
"version": "FortiAI 1.4.0 and earlier"
}
]
}
],
"source": "psirt@fortinet.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:o:fortinet:fortiai_firmware:*:*:*:*:*:*:*:*",
"matchCriteriaId": "2ABCF7D4-85F6-4BA1-9DDB-C5F068877730",
"versionEndIncluding": "1.4.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
},
{
"cpeMatch": [
{
"criteria": "cpe:2.3:h:fortinet:fortiai_3500f:-:*:*:*:*:*:*:*",
"matchCriteriaId": "4C8E5455-5A75-4758-83D5-4ED5CB4E3793",
"vulnerable": false
}
],
"negate": false,
"operator": "OR"
}
],
"operator": "AND"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "An improper input validation in FortiAI v1.4.0 and earlier may allow an authenticated user to gain system shell access via a malicious payload in the \"diagnose\" command."
},
{
"lang": "es",
"value": "Una comprobaci\u00f3n de entrada inapropiada en FortiAI versi\u00f3n v1.4.0 y anteriores puede permitir a un usuario autenticado conseguir acceso al shell del sistema por medio de una carga \u00fatil maliciosa en el comando \"diagnose\""
}
],
"id": "CVE-2021-24023",
"lastModified": "2026-06-17T03:39:10.653",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "HIGH",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "SINGLE",
"availabilityImpact": "COMPLETE",
"baseScore": 9.0,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:N/AC:L/Au:S/C:C/I:C/A:C",
"version": "2.0"
},
"exploitabilityScore": 8.0,
"impactScore": 10.0,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 5.9,
"source": "psirt@fortinet.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2021-24023",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-10-23T14:13:46.765477Z",
"version": "2.0.3"
}
}
]
},
"published": "2021-06-03T15:15:07.633",
"references": [
{
"source": "psirt@fortinet.com",
"tags": [
"Vendor Advisory"
],
"url": "https://fortiguard.com/advisory/FG-IR-21-033"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Vendor Advisory"
],
"url": "https://fortiguard.com/advisory/FG-IR-21-033"
}
],
"sourceIdentifier": "psirt@fortinet.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-78"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
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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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