SUSE-SU-2021:3857-1
Vulnerability from csaf_suse - Published: 2021-12-01 16:02 - Updated: 2026-09-20 14:10Summary
Security update for python-sqlparse
Severity
Moderate
Notes
Title of the patch: Security update for python-sqlparse
Description of the patch: This update for python-sqlparse fixes the following issues:
- CVE-2021-32839: Fixed ReDoS via regular expression in StripComments filter (bsc#1190741).
Patchnames: SUSE-2021-3857,SUSE-SLE-Module-Basesystem-15-SP3-2021-3857
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
6.5 (Medium)
Affected products
Recommended
9 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: SUSE Enterprise Storage 7.1:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Desktop 15 SP3:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise High Performance Computing 15 SP3:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Module for Basesystem 15 SP3:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Server 15 SP3:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Server for SAP Applications 15 SP3:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Manager Proxy 4.2:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Manager Retail Branch Server 4.2:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Manager Server 4.2:python3-sqlparse-0:0.4.2-3.3.1.noarch | — |
Vendor Fix
|
Threats
Impact
moderate
References
8 references
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"notes": [
{
"category": "general",
"text": "sqlparse is a non-validating SQL parser module for Python. In sqlparse versions 0.4.0 and 0.4.1 there is a regular Expression Denial of Service in sqlparse vulnerability. The regular expression may cause exponential backtracking on strings containing many repetitions of \u0027\\r\\n\u0027 in SQL comments. Only the formatting feature that removes comments from SQL statements is affected by this regular expression. As a workaround don\u0027t use the sqlformat.format function with keyword strip_comments=True or the --strip-comments command line flag when using the sqlformat command line tool. The issues has been fixed in sqlparse 0.4.2.",
"title": "CVE description"
}
],
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"remediations": [
{
"category": "vendor_fix",
"details": "To install this SUSE Security Update use the SUSE recommended installation methods like YaST online_update or \"zypper patch\".\n",
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"scores": [
{
"cvss_v3": {
"baseScore": 6.5,
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
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"threats": [
{
"category": "impact",
"date": "2021-12-01T16:02:13Z",
"details": "moderate"
}
],
"title": "CVE-2021-32839"
}
]
}
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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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