SUSE-SU-2019:2261-1
Vulnerability from csaf_suse - Published: 2019-09-02 07:04 - Updated: 2019-09-02 07:04Summary
Security update for python-SQLAlchemy
Severity
Important
Notes
Title of the patch: Security update for python-SQLAlchemy
Description of the patch: This update for python-SQLAlchemy fixes the following issues:
Security issues fixed:
- CVE-2019-7164: Fixed SQL Injection via the order_by parameter (bsc#1124593).
- CVE-2019-7548: Fixed SQL Injection via the group_by parameter (bsc#1124593).
Patchnames: HPE-Helion-OpenStack-8-2019-2261,SUSE-2019-2261,SUSE-OpenStack-Cloud-8-2019-2261,SUSE-OpenStack-Cloud-Crowbar-8-2019-2261
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
8.8 (High)
Affected products
Recommended
3 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: HPE Helion OpenStack 8:python-SQLAlchemy-1.1.12-3.5.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE OpenStack Cloud 8:python-SQLAlchemy-1.1.12-3.5.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE OpenStack Cloud Crowbar 8:python-SQLAlchemy-1.1.12-3.5.1.x86_64 | — |
Vendor Fix
|
Threats
Impact
important
8.8 (High)
Affected products
Recommended
3 products, the same list as for
CVE-2019-7164
Threats
Impact
important
References
11 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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