CVE-2026-25990 (GCVE-0-2026-25990)
Vulnerability from cvelistv5 – Published: 2026-02-11 20:53 – Updated: 2026-09-16 12:04
VLAI
EPSS
VEX
Title
Pillow has an out-of-bounds write when loading PSD images
Summary
Pillow is a Python imaging library. From 10.3.0 to before 12.1.1, an out-of-bounds write may be triggered when loading a specially crafted PSD image. This vulnerability is fixed in 12.1.1.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-11 21:21 UTC
CWE
- CWE-787 - Out-of-bounds Write
Assigner
References
26 references
Impacted products
47 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| python-pillow | Pillow |
Affected:
>= 10.3.0, < 12.1.1
|
guessed | |
| Red Hat | Red Hat Ansible Automation Platform 2.5 for RHEL 8 |
Unaffected:
0:12.1.1-1.el8ap , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.5::el8 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.5 for RHEL 9 |
Unaffected:
0:12.1.1-1.el9ap , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.5::el9 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.6 for RHEL 9 |
Unaffected:
0:12.1.1-1.el9ap , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
||
| Red Hat | Red Hat Satellite 6.16 for RHEL 8 |
Unaffected:
0:12.1.1-1.el8pc , < *
(rpm)
cpe:/a:redhat:satellite:6.16::el8 cpe:/a:redhat:satellite_capsule:6.16::el8 |
||
| Red Hat | Red Hat Satellite 6.16 for RHEL 9 |
Unaffected:
0:12.1.1-1.el9pc , < *
(rpm)
cpe:/a:redhat:satellite:6.16::el9 cpe:/a:redhat:satellite_capsule:6.16::el9 |
||
| Red Hat | Red Hat Satellite 6.17 for RHEL 9 |
Unaffected:
0:12.1.1-1.el9pc , < *
(rpm)
cpe:/a:redhat:satellite:6.17::el9 cpe:/a:redhat:satellite_capsule:6.17::el9 |
||
| Red Hat | Red Hat Satellite 6.18 for RHEL 9 |
Unaffected:
0:12.1.1-1.el9pc , < *
(rpm)
cpe:/a:redhat:satellite:6.18::el9 cpe:/a:redhat:satellite_capsule:6.18::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1772160593 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1772160625 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1772713830 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1778244546 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.5 |
Unaffected:
1774414699 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.5::el8 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.6 |
Unaffected:
1774417022 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776247907 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776257621 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776243239 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776243238 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776243299 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776243249 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776243309 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776259063 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776336652 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776319193 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776319179 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776319185 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776318795 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776319453 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776336534 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776319275 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1783998774 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1783998857 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1778264363 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1778600187 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat Quay 3.10 |
Unaffected:
1773971077 , < *
(rpm)
cpe:/a:redhat:quay:3.10::el8 |
||
| Red Hat | Red Hat Quay 3.12 |
Unaffected:
1773771962 , < *
(rpm)
cpe:/a:redhat:quay:3.12::el8 |
||
| Red Hat | Red Hat Quay 3.15 |
Unaffected:
1775169219 , < *
(rpm)
cpe:/a:redhat:quay:3.15::el8 |
||
| Red Hat | Red Hat Quay 3.16 |
Unaffected:
1775069491 , < *
(rpm)
Unaffected: 1775169226 , < * (rpm) cpe:/a:redhat:quay:3.16::el9 |
||
| Red Hat | Red Hat Quay 3.9 |
Unaffected:
1773936323 , < *
(rpm)
cpe:/a:redhat:quay:3.9::el8 |
||
| Red Hat | OpenShift Lightspeed |
cpe:/a:redhat:openshift_lightspeed
|
||
| Red Hat | Red Hat AI Inference Server |
cpe:/a:redhat:ai_inference_server:3
|
||
| Red Hat | Red Hat Ansible Automation Platform 2 |
cpe:/a:redhat:ansible_automation_platform:2
|
||
| Red Hat | Red Hat Enterprise Linux 7 |
cpe:/o:redhat:enterprise_linux:7
|
||
| Red Hat | Red Hat Enterprise Linux 8 |
cpe:/o:redhat:enterprise_linux:8
|
||
| Red Hat | Red Hat Enterprise Linux AI (RHEL AI) 3 |
cpe:/a:redhat:enterprise_linux_ai:3
|
||
| Red Hat | Red Hat OpenShift AI (RHOAI) |
cpe:/a:redhat:openshift_ai
|
||
| Red Hat | Red Hat Satellite 6 |
cpe:/a:redhat:satellite:6
|
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"metrics": [
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{
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{
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"cpes": [
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"defaultStatus": "affected",
"packageName": "python-pillow",
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{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
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],
"defaultStatus": "affected",
"packageName": "python3.12-pillow",
"product": "Red Hat Satellite 6.18 for RHEL 9",
"vendor": "Red Hat",
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"cpe:/a:redhat:ai_inference_server:3.3::el9"
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"product": "Red Hat Ansible Automation Platform 2.5",
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"product": "Red Hat Ansible Automation Platform 2.6",
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"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
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"defaultStatus": "affected",
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"versions": [
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"cpes": [
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"vendor": "Red Hat",
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"collectionURL": "https://catalog.redhat.com/software/containers/",
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{
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"cpes": [
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"cpes": [
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"vendor": "Red Hat",
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"cpes": [
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"product": "Red Hat OpenShift AI 2.25",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1776336652",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:2.25::el9"
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"defaultStatus": "affected",
"packageName": "rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9",
"product": "Red Hat OpenShift AI 2.25",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1776319193",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:2.25::el9"
],
"defaultStatus": "affected",
"packageName": "rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9",
"product": "Red Hat OpenShift AI 2.25",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1776319179",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:2.25::el9"
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"packageName": "rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9",
"product": "Red Hat OpenShift AI 2.25",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1776319185",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:2.25::el9"
],
"defaultStatus": "affected",
"packageName": "rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9",
"product": "Red Hat OpenShift AI 2.25",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
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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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