FKIE_CVE-2021-43933
Vulnerability from fkie_nvd - Published: 2022-04-20 16:15 - Updated: 2026-06-17 04:11
Severity
6.1 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:N/I:N/A:H
5.9 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
5.9 (Medium) - CVSS:3.1/
Summary
The affected product is vulnerable to a network-based attack by threat actors sending unimpeded requests to the receiving server, which could cause a denial-of-service condition due to lack of heap memory resources.
References
| URL | Tags | ||
|---|---|---|---|
| ics-cert@hq.dhs.gov | https://www.cisa.gov/uscert/ics/advisories/icsa-22-109-03 | Patch, Third Party Advisory, US Government Resource | |
| af854a3a-2127-422b-91ae-364da2661108 | https://www.cisa.gov/uscert/ics/advisories/icsa-22-109-03 | Patch, Third Party Advisory, US Government Resource |
{
"affected": [
{
"affectedData": [
{
"product": "ROBOGUIDE",
"vendor": "FANUC",
"versions": [
{
"lessThan": "v9.40083.00.05 (Rev T)",
"status": "affected",
"version": "All",
"versionType": "custom"
}
]
}
],
"source": "ics-cert@hq.dhs.gov"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:fanuc:roboguide:*:*:*:*:*:*:*:*",
"matchCriteriaId": "D5DCFBBA-2822-484C-8153-8B6EE8E4322F",
"versionEndIncluding": "9.40083.00.05",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The affected product is vulnerable to a network-based attack by threat actors sending unimpeded requests to the receiving server, which could cause a denial-of-service condition due to lack of heap memory resources."
},
{
"lang": "es",
"value": "El producto afectado es vulnerable a un ataque basado en la red por parte de actores de amenazas que env\u00eden peticiones sin obst\u00e1culos al servidor receptor, lo que podr\u00eda causar una condici\u00f3n de denegaci\u00f3n de servicio debido a una falta de recursos de memoria de la pila"
}
],
"id": "CVE-2021-43933",
"lastModified": "2026-06-17T04:11:39.157",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.3,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 6.1,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.6,
"impactScore": 4.0,
"source": "ics-cert@hq.dhs.gov",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 5.9,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.2,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2021-43933",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-16T15:53:41.984140Z",
"version": "2.0.3"
}
}
]
},
"published": "2022-04-20T16:15:08.060",
"references": [
{
"source": "ics-cert@hq.dhs.gov",
"tags": [
"Patch",
"Third Party Advisory",
"US Government Resource"
],
"url": "https://www.cisa.gov/uscert/ics/advisories/icsa-22-109-03"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory",
"US Government Resource"
],
"url": "https://www.cisa.gov/uscert/ics/advisories/icsa-22-109-03"
}
],
"sourceIdentifier": "ics-cert@hq.dhs.gov",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"source": "ics-cert@hq.dhs.gov",
"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…