GHSA-RR6C-MF52-HVF4
Vulnerability from github – Published: 2022-05-14 03:00 – Updated: 2022-05-14 03:00
VLAI
Details
Applications deployed to Cloud Foundry, versions v166 through v227, may be vulnerable to a remote disclosure of information, including, but not limited to environment variables and bound service details. For applications to be vulnerable, they must have been staged using automatic buildpack detection, passed through the Java Buildpack detection script, and allow the serving of static content from within the deployed artifact. The default Apache Tomcat configuration in the affected java buildpack versions for some basic web application archive (WAR) packaged applications are vulnerable to this issue.
Severity
5.9 (Medium)
{
"affected": [],
"aliases": [
"CVE-2016-0708"
],
"database_specific": {
"cwe_ids": [
"CWE-200"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2018-07-11T20:29:00Z",
"severity": "MODERATE"
},
"details": "Applications deployed to Cloud Foundry, versions v166 through v227, may be vulnerable to a remote disclosure of information, including, but not limited to environment variables and bound service details. For applications to be vulnerable, they must have been staged using automatic buildpack detection, passed through the Java Buildpack detection script, and allow the serving of static content from within the deployed artifact. The default Apache Tomcat configuration in the affected java buildpack versions for some basic web application archive (WAR) packaged applications are vulnerable to this issue.",
"id": "GHSA-rr6c-mf52-hvf4",
"modified": "2022-05-14T03:00:03Z",
"published": "2022-05-14T03:00:03Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2016-0708"
},
{
"type": "WEB",
"url": "https://www.cloudfoundry.org/blog/cve-2016-0708"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N",
"type": "CVSS_V3"
}
]
}
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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.
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.
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