SUSE-SU-2024:0464-1
Vulnerability from csaf_suse - Published: 2024-02-14 08:21 - Updated: 2026-09-20 15:39Summary
Security update for python3
Severity
Moderate
Notes
Title of the patch: Security update for python3
Description of the patch: This update for python3 fixes the following issues:
- CVE-2023-27043: Fixed incorrectly parses e-mail addresses which contain a special character (bsc#1210638).
- CVE-2022-48566: Use CRYPTO_memcmp() for compare_digest (bsc#1214691).
Patchnames: SUSE-2024-464,SUSE-SUSE-MicroOS-5.1-2024-464
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
5.9 (Medium)
Affected products
Recommended
9 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:libpython3_6m1_0-0:3.6.15-150000.3.138.1.aarch64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:libpython3_6m1_0-0:3.6.15-150000.3.138.1.s390x | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:libpython3_6m1_0-0:3.6.15-150000.3.138.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:python3-0:3.6.15-150000.3.138.1.aarch64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:python3-0:3.6.15-150000.3.138.1.s390x | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:python3-0:3.6.15-150000.3.138.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:python3-base-0:3.6.15-150000.3.138.1.aarch64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:python3-base-0:3.6.15-150000.3.138.1.s390x | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Linux Enterprise Micro 5.1:python3-base-0:3.6.15-150000.3.138.1.x86_64 | — |
Vendor Fix
|
Threats
Impact
moderate
5.3 (Medium)
Affected products
Recommended
9 products, the same list as for
CVE-2022-48566
Threats
Impact
moderate
References
13 references
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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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