CVE-2016-7831 (GCVE-0-2016-7831)
Vulnerability from cvelistv5 – Published: 2017-06-09 16:00 – Updated: 2024-08-06 02:04
VLAI
EPSS
VEX
Summary
Sleipnir 4 Black Edition for Mac 4.5.3 and earlier and Sleipnir 4 for Mac 4.5.3 and earlier (Mac App Store) may allow a remote attacker to spoof the URL display via a specially crafted webpage.
Severity
6.1 (Medium)
CWE
- User Interface (UI) Misrepresentation of Information
Assigner
References
2 references
| URL | Tags |
|---|---|
| http://www.securityfocus.com/bid/94830 | vdb-entryx_refsource_BID |
| https://jvn.jp/en/jp/JVN28151745/index.html | third-party-advisoryx_refsource_JVN |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Fenrir Inc. | Sleipnir 4 Black Edition for Mac |
Affected:
4.5.3 and earlier
|
guessed | |
| Fenrir Inc. | Sleipnir 4 for Mac |
Affected:
4.5.3 and earlier (Mac App Store)
|
guessed |
Date Public
2016-12-07 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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