SUSE-SU-2026:22660-1
Vulnerability from csaf_suse - Published: 2026-07-14 10:40 - Updated: 2026-09-16 20:03Summary
Security update for python-soupsieve
Severity
Important
Notes
Title of the patch: Security update for python-soupsieve
Description of the patch: This update for python-soupsieve fixes the following issues
- CVE-2026-49476: Memory Exhaustion via Large Comma-Separated Selector Lists (bsc#1271187).
- CVE-2026-49477: Regular Expression Denial of Service (ReDoS) via Selector Parser (bsc#1271188).
Patchnames: SUSE-SLES-16.0-1246
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
7.5 (High)
Affected products
Recommended
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: SUSE Linux Enterprise Server 16.0:python313-soupsieve-2.6-160000.4.1.noarch | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Server for SAP applications 16.0:python313-soupsieve-2.6-160000.4.1.noarch | — |
Vendor Fix
|
Threats
Impact
important
7.5 (High)
Affected products
Recommended
2 products, the same list as for
CVE-2026-49476
Threats
Impact
important
References
12 references
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"category": "general",
"text": "Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.8.4, the CSS selector parser in soupsieve allocates unbounded memory when compiling large comma-separated selector lists, allowing an attacker who can supply a crafted selector string to soupsieve.compile() or Beautiful Soup .select() / .select_one() to allocate hundreds of megabytes of heap memory from a relatively small input and cause denial of service. This issue is fixed in version 2.8.4.",
"title": "CVE description"
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{
"category": "general",
"text": "Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.8.4, the CSS selector parser in soupsieve contains a regular expression vulnerable to catastrophic backtracking when processing an attribute selector with an unterminated quoted value in soupsieve/css_parser.py, allowing an attacker who can supply untrusted CSS selector strings to soupsieve.compile() or Beautiful Soup .select() / .select_one() to cause CPU exhaustion and denial of service. This issue is fixed in version 2.8.4.",
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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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