CVE-2026-53205 (GCVE-0-2026-53205)
Vulnerability from cvelistv5 – Published: 2026-06-25 08:39 – Updated: 2026-08-05 12:34
VLAI
EPSS
VEX
Title
accel/ivpu: Add bounds checks for firmware log indices
Summary
In the Linux kernel, the following vulnerability has been resolved:
accel/ivpu: Add bounds checks for firmware log indices
Add validation that read and write indices in the firmware log buffer
are within valid bounds (< data_size) before using them. If
out-of-bounds indices are encountered (from firmware), clamp them to
safe values instead of proceeding with invalid offsets.
This prevents potential out-of-bounds buffer access when firmware
supplies invalid log indices.
Severity
7.1 (High)
Assigner
References
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Linux | Linux |
Affected:
0923a7d55a85179744926b7c11768a81679cc4d4 , < 5961c703414048f46818be8bbb11075a9a63fb4e
(git)
Affected: 1fc1251149a76d3b75d7f4c94d9c4e081b7df6b4 , < 8ec70c0dbdf04392a26e03e38798a373934177be (git) Affected: 1fc1251149a76d3b75d7f4c94d9c4e081b7df6b4 , < 535da9ad8420c3b686a642403d4147ff220255fd (git) Affected: 1fc1251149a76d3b75d7f4c94d9c4e081b7df6b4 , < dd1311bcf0e62f0c515115f46a3813370f4a4bb1 (git) Affected: 6.12.30 , < 6.12.94 (semver) |
guessed | |
| Linux | Linux |
Affected:
6.13
Unaffected: 0 , < 6.13 (semver) Unaffected: 6.12.94 , ≤ 6.12.* (semver) Unaffected: 6.18.36 , ≤ 6.18.* (semver) Unaffected: 7.0.13 , ≤ 7.0.* (semver) Unaffected: 7.1 , ≤ * (original_commit_for_fix) |
guessed |
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"source": "Red Hat CSAF VEX",
"status": "final",
"title": "kernel: accel/ivpu: Add bounds checks for firmware log indices",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-53205.json",
"version": "3"
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"cve": "CVE-2026-53205",
"id": "CVE-2026-53205",
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"product_status:recommended": "201",
"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2026-53205",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2026-53205.json",
"version": "11"
}
}
}
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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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