CVE-2024-37022 (GCVE-0-2024-37022)
Vulnerability from cvelistv5 – Published: 2024-06-13 17:25 – Updated: 2024-08-02 03:43
VLAI
EPSS
VEX
Title
Fuji Electric Tellus Lite V-Simulator Out-of-bounds Write
Summary
Fuji Electric Tellus Lite V-Simulator is vulnerable to an out-of-bounds write, which could allow an attacker to manipulate memory, resulting in execution of arbitrary code.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-19 18:48 UTC
CWE
- CWE-787 - Out-of-bounds Write
Assigner
References
1 reference
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Fuji Electric | Tellus Lite V-Simulator |
Affected:
0 , < 4.0.20.0
(custom)
|
guessed | |
| fujielectric | tellus_lite_v-simulator |
Affected:
0 , < 4.0.20.0
(custom)
cpe:2.3:a:fujielectric:tellus_lite_v-simulator:*:*:*:*:*:*:*:* |
Date Public
2024-06-13 17:00
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"value": "\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\n\n\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\n\n\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eFuji Electric Tellus Lite V-Simulator is vulnerable to an out-of-bounds write, which could allow an attacker to manipulate memory, resulting in execution of arbitrary code.\u003c/span\u003e\n\n\u003c/span\u003e\n\n\u003c/span\u003e"
}
],
"value": "Fuji Electric Tellus Lite V-Simulator is vulnerable to an out-of-bounds write, which could allow an attacker to manipulate memory, resulting in execution of arbitrary code."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
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"format": "CVSS",
"scenarios": [
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"value": "GENERAL"
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{
"cvssV4_0": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "LOCAL",
"baseScore": 8.5,
"baseSeverity": "HIGH",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "PASSIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N",
"version": "4.0",
"vulnAvailabilityImpact": "HIGH",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
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"value": "GENERAL"
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"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-787",
"description": "CWE-787 Out-of-bounds Write",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2024-06-13T17:25:49.609Z",
"orgId": "7d14cffa-0d7d-4270-9dc0-52cabd5a23a6",
"shortName": "icscert"
},
"references": [
{
"url": "https://www.cisa.gov/news-events/ics-advisories/icsa-24-165-14"
}
],
"solutions": [
{
"lang": "en",
"supportingMedia": [
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"type": "text/html",
"value": "\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eFuji Electric recommends users update to \u003c/span\u003e\u003ca target=\"_blank\" rel=\"nofollow\" href=\"https://felib.fujielectric.co.jp/en/M10009/M20034/document_detail/a1f9328f-82f4-434a-b593-32874d1e897d\"\u003ev4.0.20.0\u003c/a\u003e.\u003cbr\u003e"
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],
"value": "Fuji Electric recommends users update to v4.0.20.0 https://felib.fujielectric.co.jp/en/M10009/M20034/document_detail/a1f9328f-82f4-434a-b593-32874d1e897d ."
}
],
"source": {
"advisory": "ICSA-24-165-14",
"discovery": "EXTERNAL"
},
"title": "Fuji Electric Tellus Lite V-Simulator Out-of-bounds Write",
"x_generator": {
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}
},
"cveMetadata": {
"assignerOrgId": "7d14cffa-0d7d-4270-9dc0-52cabd5a23a6",
"assignerShortName": "icscert",
"cveId": "CVE-2024-37022",
"datePublished": "2024-06-13T17:25:49.609Z",
"dateReserved": "2024-06-06T17:39:34.310Z",
"dateUpdated": "2024-08-02T03:43:50.589Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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