CVE-2019-16007 (GCVE-0-2019-16007)
Vulnerability from cvelistv5 – Published: 2020-09-23 00:26 – Updated: 2024-11-13 18:04
VLAI
EPSS
VEX
Title
Cisco AnyConnect Secure Mobility Client for Android Service Hijack Vulnerability
Summary
A vulnerability in the inter-service communication of Cisco AnyConnect Secure Mobility Client for Android could allow an unauthenticated, local attacker to perform a service hijack attack on an affected device or cause a denial of service (DoS) condition. The vulnerability is due to the use of implicit service invocations. An attacker could exploit this vulnerability by persuading a user to install a malicious application. A successful exploit could allow the attacker to access confidential user information or cause a DoS condition on the AnyConnect application.
Severity
5.9 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-11-13 17:23 UTC
CWE
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://tools.cisco.com/security/center/content/C… | vendor-advisoryx_refsource_CISCO |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Cisco | Cisco AnyConnect Secure Mobility Client |
Affected:
n/a
|
guessed |
Date Public
2020-01-08 00:00
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"vectorString": "CVSS:3.0/AV:P/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:H",
"version": "3.0"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-345"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "20200108 Cisco AnyConnect Secure Mobility Client for Android Service Hijack Vulnerability",
"refsource": "CISCO",
"url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-20200108-anyconnect-hijack"
}
]
},
"source": {
"advisory": "cisco-sa-20200108-anyconnect-hijack",
"defect": [
[
"CSCvr67149"
]
],
"discovery": "INTERNAL"
}
}
}
},
"cveMetadata": {
"assignerOrgId": "d1c1063e-7a18-46af-9102-31f8928bc633",
"assignerShortName": "cisco",
"cveId": "CVE-2019-16007",
"datePublished": "2020-09-23T00:26:45.174Z",
"dateReserved": "2019-09-06T00:00:00.000Z",
"dateUpdated": "2024-11-13T18:04:01.991Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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