CVE-2016-2347 (GCVE-0-2016-2347)
Vulnerability from cvelistv5 – Published: 2017-04-21 20:00 – Updated: 2024-08-05 23:24
VLAI
EPSS
VEX
Summary
Integer underflow in the decode_level3_header function in lib/lha_file_header.c in Lhasa before 0.3.1 allows remote attackers to execute arbitrary code via a crafted archive.
Severity
7.8 (High)
CWE
- n/a
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://github.com/fragglet/lhasa/releases/tag/v0.3.1 | x_refsource_CONFIRM |
| http://www.talosintelligence.com/reports/TALOS-20… | x_refsource_MISC |
| https://github.com/fragglet/lhasa/commit/6fcdb8f1… | x_refsource_CONFIRM |
| http://lists.opensuse.org/opensuse-updates/2016-0… | vendor-advisoryx_refsource_SUSE |
| http://lists.opensuse.org/opensuse-updates/2016-0… | vendor-advisoryx_refsource_SUSE |
| http://www.debian.org/security/2016/dsa-3540 | vendor-advisoryx_refsource_DEBIAN |
Date Public
2016-03-31 00:00
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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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