OPENSUSE-SU-2026:11169-1
Vulnerability from csaf_opensuse - Published: 2026-07-01 00:00 - Updated: 2026-09-17 17:12Summary
python3-onionshare-2.6.4-1.1 on GA media
Severity
Moderate
Notes
Title of the patch: python3-onionshare-2.6.4-1.1 on GA media
Description of the patch: These are all security issues fixed in the python3-onionshare-2.6.4-1.1 package on the GA media of openSUSE Tumbleweed.
Patchnames: openSUSE-Tumbleweed-2026-11169
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
Affected products
Recommended
4 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: openSUSE Tumbleweed:python3-onionshare-0:2.6.4-1.1.aarch64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python3-onionshare-0:2.6.4-1.1.ppc64le | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python3-onionshare-0:2.6.4-1.1.s390x | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Tumbleweed:python3-onionshare-0:2.6.4-1.1.x86_64 | — |
Vendor Fix
|
Threats
Impact
moderate
Affected products
Recommended
4 products, the same list as for
CVE-2026-54706
Threats
Impact
moderate
References
8 references
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"text": "OnionShare is an open source tool that lets you securely and anonymously share files, host websites, and chat with friends using the Tor network. Prior to 2.6.4, OnionShare CLI/Desktop follows symbolic links in cli/onionshare_cli/web/send_base_mode.py through SendBaseModeWeb.set_file_info() and stream_individual_file(), allowing remote recipients of Share or Website mode to read local files outside the selected directory. This issue is fixed in version 2.6.4.",
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}
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"text": "OnionShare is an open source tool that lets you securely and anonymously share files, host websites, and chat with friends using the Tor network. Prior to 2.6.4, OnionShare CLI/Desktop does not enforce the Receive mode disable_files setting in cli/onionshare_cli/web/receive_mode.py, where ReceiveModeRequest._get_file_stream() writes multipart file[] data to disk despite the text-only setting. This issue is fixed in version 2.6.4.",
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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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