CVE-2026-24486 (GCVE-0-2026-24486)
Vulnerability from cvelistv5 – Published: 2026-01-27 00:34 – Updated: 2026-09-16 12:04
VLAI
EPSS
VEX
Title
Python-Multipart has Arbitrary File Write via Non-Default Configuration
Summary
Python-Multipart is a streaming multipart parser for Python. Prior to version 0.0.22, a Path Traversal vulnerability exists when using non-default configuration options `UPLOAD_DIR` and `UPLOAD_KEEP_FILENAME=True`. An attacker can write uploaded files to arbitrary locations on the filesystem by crafting a malicious filename. Users should upgrade to version 0.0.22 to receive a patch or, as a workaround, avoid using `UPLOAD_KEEP_FILENAME=True` in project configurations.
Severity
8.6 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-27 20:50 UTC
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
17 references
Impacted products
22 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Kludex | python-multipart |
Affected:
< 0.0.22
|
guessed | |
| 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 Ansible Automation Platform 2.6 |
Unaffected:
1772204398 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.6 |
Unaffected:
1772429277 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776338381 , < *
(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:
1772093278 , < *
(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:
1770956034 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat Satellite 6.17 |
Unaffected:
1784834402 , < *
(rpm)
cpe:/a:redhat:satellite:6.17::el9 |
||
| Red Hat | Red Hat Satellite 6.18 |
Unaffected:
1769520238 , < *
(rpm)
cpe:/a:redhat:satellite:6.18::el9 |
||
| Red Hat | Red Hat Satellite 6.18 |
Unaffected:
1784554123 , < *
(rpm)
cpe:/a:redhat:satellite:6.18::el9 |
||
| Red Hat | Lightspeed Core |
cpe:/a:redhat:lightspeed_core
|
||
| 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 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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}
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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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