CVE-2026-42561 (GCVE-0-2026-42561)
Vulnerability from cvelistv5 – Published: 2026-05-13 20:55 – Updated: 2026-08-07 12:04
VLAI
EPSS
VEX
Title
Python-Multipart: Denial of Service via unbounded multipart part headers
Summary
Python-Multipart is a streaming multipart parser for Python. Prior to 0.0.27, python-multipart has a denial of service vulnerability in multipart part header parsing. When parsing multipart/form-data, MultipartParser previously had no limit on the number of part headers or the size of an individual part header. An attacker could send a request with either many repeated headers without terminating the header block or a single very large header value, causing excessive CPU work before request rejection or completion. This vulnerability is fixed in 0.0.27.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-14 16:04 UTC
CWE
Assigner
References
12 references
| URL | Tags |
|---|---|
| https://github.com/Kludex/python-multipart/securi… | x_refsource_CONFIRM |
| https://access.redhat.com/security/cve/CVE-2026-42561 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2477309 | issue-trackingx_refsource_REDHAT |
| https://security.access.redhat.com/data/csaf/v2/v… | x_sadp-csaf-vex |
| https://access.redhat.com/errata/RHSA-2026:42132 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:42142 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:43038 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:37275 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:44696 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:51357 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:51194 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:51219 | vendor-advisoryx_refsource_REDHAT |
Impacted products
17 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Kludex | python-multipart |
Affected:
< 0.0.27
|
guessed | |
| Red Hat | Red Hat Ansible Automation Platform 2.6 |
Unaffected:
1783832856 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.6 |
Unaffected:
1783920640 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.7 |
Unaffected:
1783923914 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.7::el9 |
||
| Red Hat | Red Hat Ansible Automation Platform 2.7 |
Unaffected:
1783918403 , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.7::el9 |
||
| Red Hat | Red Hat Migration Toolkit for Applications 8.2 |
Unaffected:
1784109883 , < *
(rpm)
cpe:/a:redhat:migration_toolkit_applications:8.2::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782887848 , < *
(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 6.19 |
Unaffected:
1785929994 , < *
(rpm)
cpe:/a:redhat:satellite:6.19::el9 |
||
| Red Hat | Red Hat Satellite 6.19 |
Unaffected:
1785806554 , < *
(rpm)
cpe:/a:redhat:satellite:6.19::el9 |
||
| Red Hat | Exploit Intelligence |
cpe:/a:redhat:exploit_intelligence:0
|
||
| 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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"initial_release_date": "2026-05-15T01:58:47Z",
"product_status:recommended": "7",
"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2026-42561",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2026-42561.json",
"version": "5"
},
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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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