CVE-2024-6564 (GCVE-0-2024-6564)
Vulnerability from cvelistv5 – Published: 2024-07-08 15:18 – Updated: 2024-08-01 21:41
VLAI
EPSS
VEX
Title
Buffer overflow in Rensas RCAR
Summary
Buffer overflow in "rcar_dev_init" due to using due to using untrusted data (rcar_image_number) as a loop counter before verifying it against RCAR_MAX_BL3X_IMAGE. This could lead to a full bypass of secure boot.
Severity
6.7 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-09 15:14 UTC
CWE
- CWE-120 - Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/renesas-rcar/arm-trusted-firmw… | |
| https://asrg.io/security-advisories/cve-2024-6564/ | third-party-advisory |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Renesas | rcar_gen3_v2.5 |
Affected:
c2f286820471ed276c57e603762bd831873e5a17 , ≤ c9fb3558410032d2660c7f3b7d4b87dec09fe2f2
(git)
|
guessed | |
| renesas | rcar_gen3_v2.5 |
Affected:
c2f286820471ed276c57e603762bd831873e5a17 , ≤ c9fb3558410032d2660c7f3b7d4b87dec09fe2f2
(custom)
cpe:2.3:a:renesas:rcar_gen3_v2.5:*:*:*:*:*:*:*:* |
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"vectorString": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-120",
"description": "CWE-120 Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2024-07-08T15:20:00.212Z",
"orgId": "c15abc07-96a9-4d11-a503-5d621bfe42ba",
"shortName": "ASRG"
},
"references": [
{
"url": "https://github.com/renesas-rcar/arm-trusted-firmware/commit/c9fb3558410032d2660c7f3b7d4b87dec09fe2f2"
},
{
"tags": [
"third-party-advisory"
],
"url": "https://asrg.io/security-advisories/cve-2024-6564/"
}
],
"source": {
"discovery": "UNKNOWN"
},
"title": "Buffer overflow in Rensas RCAR",
"x_generator": {
"engine": "Vulnogram 0.1.0-dev"
}
}
},
"cveMetadata": {
"assignerOrgId": "c15abc07-96a9-4d11-a503-5d621bfe42ba",
"assignerShortName": "ASRG",
"cveId": "CVE-2024-6564",
"datePublished": "2024-07-08T15:18:17.265Z",
"dateReserved": "2024-07-08T15:06:44.987Z",
"dateUpdated": "2024-08-01T21:41:03.762Z",
"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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