CVE-2026-53539 (GCVE-0-2026-53539)
Vulnerability from cvelistv5 – Published: 2026-06-22 16:55 – Updated: 2026-06-23 16:08
VLAI
EPSS
VEX
Title
Python-Multipart: Quadratic-time querystring parsing with semicolon separators causes CPU denial of service
Summary
Python-Multipart is a streaming multipart parser for Python. Prior to 0.0.30, when parsing application/x-www-form-urlencoded bodies, QuerystringParser located the field separator with a two step lookup: it first scanned the entire remaining buffer for &, and only when no & existed anywhere ahead did it fall back to scanning for ;. For a body that uses ; as the separator and contains no &, every field iteration performed a full failed & scan over the entire remaining buffer before locating the nearby ;. With N semicolon separated fields in a chunk of size B, this yields O(B^2) byte comparisons per chunk. An attacker can submit a small crafted body of the form a;a;a;... and cause the parser to spend seconds of CPU per request. A handful of concurrent requests can exhaust worker processes. This vulnerability is fixed in 0.0.30.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-23 14:05 UTC
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/Kludex/python-multipart/securi… | x_refsource_CONFIRM |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Kludex | python-multipart |
Affected:
< 0.0.30
|
guessed |
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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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