GHSA-6HMM-77R2-H6HR
Vulnerability from github – Published: 2022-05-24 17:06 – Updated: 2022-12-21 16:39Amazon EC2 Plugin 1.47 and earlier does not perform permission checks in methods performing form validation. This allows users with Overall/Read access to Jenkins to connect to an attacker-specified URL within the AWS region using attacker-specified credentials IDs obtained through another method.
This vulnerability might also allow attackers to capture credentials stored in Jenkins. We have not been able to confirm that this is possible.
Additionally, these form validation methods do not require POST requests, resulting in a CSRF vulnerability.
Amazon EC2 Plugin 1.48 requires POST requests and Overall/Administer permission for the affected form validation methods.
{
"affected": [
{
"package": {
"ecosystem": "Maven",
"name": "org.jenkins-ci.plugins:ec2"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.48"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2020-2091"
],
"database_specific": {
"cwe_ids": [
"CWE-862"
],
"github_reviewed": true,
"github_reviewed_at": "2022-12-21T16:39:59Z",
"nvd_published_at": "2020-01-15T16:15:00Z",
"severity": "MODERATE"
},
"details": "Amazon EC2 Plugin 1.47 and earlier does not perform permission checks in methods performing form validation. This allows users with Overall/Read access to Jenkins to connect to an attacker-specified URL within the AWS region using attacker-specified credentials IDs obtained through another method.\n\nThis vulnerability might also allow attackers to capture credentials stored in Jenkins. We have not been able to confirm that this is possible.\n\nAdditionally, these form validation methods do not require POST requests, resulting in a CSRF vulnerability.\n\nAmazon EC2 Plugin 1.48 requires POST requests and Overall/Administer permission for the affected form validation methods.",
"id": "GHSA-6hmm-77r2-h6hr",
"modified": "2022-12-21T16:39:59Z",
"published": "2022-05-24T17:06:22Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-2091"
},
{
"type": "WEB",
"url": "https://github.com/jenkinsci/ec2-plugin/commit/0cdbaf2d7da5c368209f427559c8608dec22a63b"
},
{
"type": "PACKAGE",
"url": "https://github.com/jenkinsci/ec2-plugin"
},
{
"type": "WEB",
"url": "https://jenkins.io/security/advisory/2020-01-15/#SECURITY-1004"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:L",
"type": "CVSS_V3"
}
],
"summary": "Missing permission checks in Jenkins Amazon EC2 Plugin"
}
Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
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.
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.