OPENSUSE-SU-2019:2343-1
Vulnerability from csaf_opensuse - Published: 2019-10-20 16:18 - Updated: 2026-09-20 18:58Summary
Security update for libpcap
Severity
Important
Notes
Title of the patch: Security update for libpcap
Description of the patch: This update for libpcap fixes the following issues:
- CVE-2019-15165: Added sanity checks for PHB header length before allocating memory (bsc#1153332).
- CVE-2018-16301: Fixed a buffer overflow (bsc#1153332).
This update was imported from the SUSE:SLE-15:Update update project.
Patchnames: openSUSE-2019-2343
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
7.8 (High)
Affected products
Recommended
8 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: openSUSE Leap 15.0:libpcap-devel-0:1.8.1-lp150.3.3.1.i586 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap-devel-0:1.8.1-lp150.3.3.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap-devel-32bit-0:1.8.1-lp150.3.3.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap-devel-static-0:1.8.1-lp150.3.3.1.i586 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap-devel-static-0:1.8.1-lp150.3.3.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap1-0:1.8.1-lp150.3.3.1.i586 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap1-0:1.8.1-lp150.3.3.1.x86_64 | — |
Vendor Fix
|
|
| Unresolved product id: openSUSE Leap 15.0:libpcap1-32bit-0:1.8.1-lp150.3.3.1.x86_64 | — |
Vendor Fix
|
Threats
Impact
important
5.3 (Medium)
Affected products
Recommended
8 products, the same list as for
CVE-2018-16301
Threats
Impact
moderate
References
13 references
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"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
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"threats": [
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"category": "impact",
"date": "2019-10-20T16:18:04Z",
"details": "moderate"
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"title": "CVE-2019-15165"
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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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