CVE-2026-3146 (GCVE-0-2026-3146)
Vulnerability from cvelistv5 – Published: 2026-02-25 03:02 – Updated: 2026-02-25 15:52 X_Open Source
VLAI
EPSS
VEX
Title
libvips matrixload.c vips_foreign_load_matrix_header null pointer dereference
Summary
A vulnerability has been found in libvips up to 8.18.0. The impacted element is the function vips_foreign_load_matrix_header of the file libvips/foreign/matrixload.c. The manipulation leads to null pointer dereference. The attack needs to be performed locally. The identifier of the patch is d4ce337c76bff1b278d7085c3c4f4725e3aa6ece. To fix this issue, it is recommended to deploy a patch.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-25 15:52 UTC
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.347652 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.347652 | signaturepermissions-required |
| https://vuldb.com/?submit.758691 | third-party-advisory |
| https://github.com/libvips/libvips/issues/4875 | issue-tracking |
| https://github.com/libvips/libvips/pull/4888 | issue-trackingpatch |
| https://github.com/libvips/libvips/commit/d4ce337… | patch |
| https://github.com/libvips/libvips/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| n/a | libvips |
Affected:
8.0
Affected: 8.1 Affected: 8.2 Affected: 8.3 Affected: 8.4 Affected: 8.5 Affected: 8.6 Affected: 8.7 Affected: 8.8 Affected: 8.9 Affected: 8.10 Affected: 8.11 Affected: 8.12 Affected: 8.13 Affected: 8.14 Affected: 8.15 Affected: 8.16 Affected: 8.17 Affected: 8.18.0 cpe:2.3:a:libvips:libvips:*:*:*:*:*:*:*:* |
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"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L/E:X/RL:O/RC:C",
"version": "3.1"
}
},
{
"cvssV3_0": {
"baseScore": 3.3,
"baseSeverity": "LOW",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L/E:X/RL:O/RC:C",
"version": "3.0"
}
},
{
"cvssV2_0": {
"baseScore": 1.7,
"vectorString": "AV:L/AC:L/Au:S/C:N/I:N/A:P/E:ND/RL:OF/RC:C",
"version": "2.0"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-476",
"description": "NULL Pointer Dereference",
"lang": "en",
"type": "CWE"
}
]
},
{
"descriptions": [
{
"cweId": "CWE-404",
"description": "Denial of Service",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-02-25T03:02:09.172Z",
"orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"shortName": "VulDB"
},
"references": [
{
"name": "VDB-347652 | libvips matrixload.c vips_foreign_load_matrix_header null pointer dereference",
"tags": [
"vdb-entry",
"technical-description"
],
"url": "https://vuldb.com/?id.347652"
},
{
"name": "VDB-347652 | CTI Indicators (IOB, IOC, IOA)",
"tags": [
"signature",
"permissions-required"
],
"url": "https://vuldb.com/?ctiid.347652"
},
{
"name": "Submit #758691 | libvips 8.19.0(7fab325d2) NULL Pointer Dereference (CWE-476)",
"tags": [
"third-party-advisory"
],
"url": "https://vuldb.com/?submit.758691"
},
{
"tags": [
"issue-tracking"
],
"url": "https://github.com/libvips/libvips/issues/4875"
},
{
"tags": [
"issue-tracking",
"patch"
],
"url": "https://github.com/libvips/libvips/pull/4888"
},
{
"tags": [
"patch"
],
"url": "https://github.com/libvips/libvips/commit/d4ce337c76bff1b278d7085c3c4f4725e3aa6ece"
},
{
"tags": [
"product"
],
"url": "https://github.com/libvips/libvips/"
}
],
"tags": [
"x_open-source"
],
"timeline": [
{
"lang": "en",
"time": "2026-02-24T00:00:00.000Z",
"value": "Advisory disclosed"
},
{
"lang": "en",
"time": "2026-02-24T01:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2026-02-24T20:59:04.000Z",
"value": "VulDB entry last update"
}
],
"title": "libvips matrixload.c vips_foreign_load_matrix_header null pointer dereference"
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2026-3146",
"datePublished": "2026-02-25T03:02:09.172Z",
"dateReserved": "2026-02-24T19:53:47.620Z",
"dateUpdated": "2026-02-25T15:52:33.882Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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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