CVE-2026-59893 (GCVE-0-2026-59893)
Vulnerability from cvelistv5 – Published: 2026-08-17 17:41 – Updated: 2026-08-17 18:54
VLAI
EPSS
VEX
Title
sqlparse: Inefficient Regex Handling of Dollar-Quoted SQL Literals Leads to ReDoS (Denial of Service)
Summary
sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, SQL_REGEX in sqlparse/keywords.py and the per-position loop in sqlparse/lexer.py repeatedly scan unmatched dollar-quoted literal and multiline-comment delimiters, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split(). This issue is fixed in version 0.6.0.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-17 18:54 UTC
CWE
- CWE-1333 - Inefficient Regular Expression Complexity
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/andialbrecht/sqlparse/security… | x_refsource_CONFIRM |
| https://github.com/andialbrecht/sqlparse/commit/d… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| andialbrecht | sqlparse |
Affected:
< 0.6.0
|
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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