CVE-2026-45881 (GCVE-0-2026-45881)
Vulnerability from cvelistv5 – Published: 2026-05-27 12:16 – Updated: 2026-05-27 12:16
VLAI
EPSS
VEX
Title
soc: mediatek: svs: Fix memory leak in svs_enable_debug_write()
Summary
In the Linux kernel, the following vulnerability has been resolved:
soc: mediatek: svs: Fix memory leak in svs_enable_debug_write()
In svs_enable_debug_write(), the buf allocated by memdup_user_nul()
is leaked if kstrtoint() fails.
Fix this by using __free(kfree) to automatically free buf, eliminating
the need for explicit kfree() calls and preventing leaks.
[Angelo: Added missing cleanup.h inclusion]
Severity
5.5 (Medium)
Assigner
References
6 references
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Linux | Linux |
Affected:
13f1bbcfb5822fcaacfc652017b57b79ffcacefa , < 47a3e372f7d68776adb749a27c0ec9058ff1b4fd
(git)
Affected: 13f1bbcfb5822fcaacfc652017b57b79ffcacefa , < 06195456c4e4de3826c4ca60eca941c472f991d0 (git) Affected: 13f1bbcfb5822fcaacfc652017b57b79ffcacefa , < a58c97828911c0b6e25d6b556789da974003efda (git) Affected: 13f1bbcfb5822fcaacfc652017b57b79ffcacefa , < 0f6498077faa9cd89bb787bcc57063494a6f0601 (git) Affected: 13f1bbcfb5822fcaacfc652017b57b79ffcacefa , < 6bb10466e0884b4a68d4a1f3f4bb87eeb471c18a (git) Affected: 13f1bbcfb5822fcaacfc652017b57b79ffcacefa , < 6259094ee806fb813ca95894c65fb80e2ec98bf1 (git) |
guessed | |
| Linux | Linux |
Affected:
6.0
Unaffected: 0 , < 6.0 (semver) Unaffected: 6.1.165 , ≤ 6.1.* (semver) Unaffected: 6.6.128 , ≤ 6.6.* (semver) Unaffected: 6.12.75 , ≤ 6.12.* (semver) Unaffected: 6.18.14 , ≤ 6.18.* (semver) Unaffected: 6.19.4 , ≤ 6.19.* (semver) Unaffected: 7.0 , ≤ * (original_commit_for_fix) |
guessed |
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"title": "kernel: soc: mediatek: svs: Fix memory leak in svs_enable_debug_write()",
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"current_release_date": "2026-10-01T01:14:49Z",
"cve": "CVE-2026-45881",
"id": "CVE-2026-45881",
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"status": "interim",
"title": "SUSE CVE CVE-2026-45881",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2026-45881.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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