OPENSUSE-SU-2026:10430-1
Vulnerability from csaf_opensuse - Published: 2026-03-25 00:00 - Updated: 2026-09-17 16:58Summary
python311-lmdb-2.1.1-1.1 on GA media
Severity
Moderate
Notes
Title of the patch: python311-lmdb-2.1.1-1.1 on GA media
Description of the patch: These are all security issues fixed in the python311-lmdb-2.1.1-1.1 package on the GA media of openSUSE Tumbleweed.
Patchnames: openSUSE-Tumbleweed-2026-10430
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
9.8 (Critical)
Affected products
Recommended
8 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: openSUSE Tumbleweed:python311-lmdb-0:2.1.1-1.1.aarch64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python311-lmdb-0:2.1.1-1.1.ppc64le | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python311-lmdb-0:2.1.1-1.1.s390x | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python311-lmdb-0:2.1.1-1.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python313-lmdb-0:2.1.1-1.1.aarch64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python313-lmdb-0:2.1.1-1.1.ppc64le | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python313-lmdb-0:2.1.1-1.1.s390x | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python313-lmdb-0:2.1.1-1.1.x86_64 | — |
Vendor Fix
|
Threats
Impact
important
9.8 (Critical)
Affected products
Recommended
8 products, the same list as for
CVE-2019-16224
Threats
Impact
important
7.5 (High)
Affected products
Recommended
8 products, the same list as for
CVE-2019-16224
Threats
Impact
moderate
9.8 (Critical)
Affected products
Recommended
8 products, the same list as for
CVE-2019-16224
Threats
Impact
important
7.5 (High)
Affected products
Recommended
8 products, the same list as for
CVE-2019-16224
Threats
Impact
moderate
References
16 references
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"title": "CVE description"
}
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{
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"ids": [
{
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"text": "https://www.suse.com/security/cve/CVE-2019-16226"
}
],
"notes": [
{
"category": "general",
"text": "An issue was discovered in py-lmdb 0.97. mdb_node_del does not validate a memmove in the case of an unexpected node-\u003emn_hi, leading to an invalid write operation. NOTE: this outcome occurs when accessing a data.mdb file supplied by an attacker.",
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"system_name": "SUSE CVE Page",
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}
],
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"category": "general",
"text": "An issue was discovered in py-lmdb 0.97. For certain values of mn_flags, mdb_cursor_set triggers a memcpy with an invalid write operation within mdb_xcursor_init1. NOTE: this outcome occurs when accessing a data.mdb file supplied by an attacker.",
"title": "CVE description"
}
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}
]
}
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
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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.