GHSA-6MQQ-8R44-VMJC
Vulnerability from github – Published: 2019-03-14 15:41 – Updated: 2024-10-21 21:07
VLAI
Summary
Exposure of Sensitive Information to an Unauthorized Actor in Apache Spark
Details
In Apache Spark 1.0.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, when using PySpark or SparkR, it's possible for a different local user to connect to the Spark application and impersonate the user running the Spark application.
Severity
4.7 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "Maven",
"name": "org.apache.spark:spark-core_2.10"
},
"ranges": [
{
"events": [
{
"introduced": "1.0.0"
},
{
"fixed": "2.1.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "org.apache.spark:spark-core_2.10"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "org.apache.spark:spark-core_2.11"
},
"ranges": [
{
"events": [
{
"introduced": "1.0.0"
},
{
"fixed": "2.1.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "org.apache.spark:spark-core_2.11"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "org.apache.spark:spark-core_2.11"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.3.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "pyspark"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "pyspark"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2018-1334"
],
"database_specific": {
"cwe_ids": [
"CWE-200"
],
"github_reviewed": true,
"github_reviewed_at": "2020-06-16T21:19:47Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "In Apache Spark 1.0.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, when using PySpark or SparkR, it\u0027s possible for a different local user to connect to the Spark application and impersonate the user running the Spark application.",
"id": "GHSA-6mqq-8r44-vmjc",
"modified": "2024-10-21T21:07:39Z",
"published": "2019-03-14T15:41:04Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-1334"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-6mqq-8r44-vmjc"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/pyspark/PYSEC-2018-25.yaml"
},
{
"type": "WEB",
"url": "https://lists.apache.org/thread.html/4d6d210e319a501b740293daaeeeadb51927111fb8261a3e4cd60060@%3Cdev.spark.apache.org%3E"
},
{
"type": "WEB",
"url": "https://spark.apache.org/security.html#CVE-2018-1334"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Exposure of Sensitive Information to an Unauthorized Actor in Apache Spark"
}
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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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