CVE-2026-46235 (GCVE-0-2026-46235)
Vulnerability from cvelistv5 – Published: 2026-05-28 09:41 – Updated: 2026-06-14 18:04
VLAI
EPSS
VEX
Title
media: saa7164: add ioremap return checks and cleanups
Summary
In the Linux kernel, the following vulnerability has been resolved:
media: saa7164: add ioremap return checks and cleanups
Add checks for ioremap return values in saa7164_dev_setup(). If
ioremap for BAR0 or BAR2 fails, release the already allocated PCI
memory regions, remove the device from the global list, decrement
the device count, and return -ENODEV.
This prevents potential null pointer dereferences and ensures proper
cleanup on memory mapping failures.
Severity
5.5 (Medium)
Assigner
References
6 references
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Linux | Linux |
Affected:
443c1228d50518f3c550e1fef490a2c9d9246ce7 , < 23dee5990d2c27ed79567fd61ccfe6876768531a
(git)
Affected: 443c1228d50518f3c550e1fef490a2c9d9246ce7 , < 3ce8f3057c51bb0a66aa3fab0862be74e9f88684 (git) Affected: 443c1228d50518f3c550e1fef490a2c9d9246ce7 , < a9b83f46e52cf1239d780920d1a7a3e415f7b5d9 (git) Affected: 443c1228d50518f3c550e1fef490a2c9d9246ce7 , < 6047dc542fa404b5c187cc2c7906aaaaec6d11ed (git) Affected: 443c1228d50518f3c550e1fef490a2c9d9246ce7 , < 6c22a6d8e4c1507bba504aeebe80476144a373eb (git) Affected: 443c1228d50518f3c550e1fef490a2c9d9246ce7 , < d51c60a498e83c9a79884c8e420f97e3885c9583 (git) |
guessed | |
| Linux | Linux |
Affected:
2.6.32
Unaffected: 0 , < 2.6.32 (semver) Unaffected: 6.1.175 , ≤ 6.1.* (semver) Unaffected: 6.6.140 , ≤ 6.6.* (semver) Unaffected: 6.12.90 , ≤ 6.12.* (semver) Unaffected: 6.18.32 , ≤ 6.18.* (semver) Unaffected: 7.0.9 , ≤ 7.0.* (semver) Unaffected: 7.1 , ≤ * (original_commit_for_fix) |
guessed |
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}
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"title": "kernel: media: saa7164: add ioremap return checks and cleanups",
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"cve": "CVE-2026-46235",
"id": "CVE-2026-46235",
"initial_release_date": "2026-05-29T01:14:36Z",
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"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2026-46235",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2026-46235.json",
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}
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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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