Vulnerabilities > Apache > Spark > 0.5.1
DATE | CVE | VULNERABILITY TITLE | RISK |
---|---|---|---|
2023-05-02 | CVE-2023-32007 | Unspecified vulnerability in Apache Spark ** UNSUPPORTED WHEN ASSIGNED ** The Apache Spark UI offers the possibility to enable ACLs via the configuration option spark.acls.enable. | 8.8 |
2023-04-17 | CVE-2023-22946 | Unspecified vulnerability in Apache Spark In Apache Spark versions prior to 3.4.0, applications using spark-submit can specify a 'proxy-user' to run as, limiting privileges. | 9.9 |
2022-11-01 | CVE-2022-31777 | Unspecified vulnerability in Apache Spark A stored cross-site scripting (XSS) vulnerability in Apache Spark 3.2.1 and earlier, and 3.3.0, allows remote attackers to execute arbitrary JavaScript in the web browser of a user, by including a malicious payload into the logs which would be returned in logs rendered in the UI. | 5.4 |
2022-07-18 | CVE-2022-33891 | OS Command Injection vulnerability in Apache Spark The Apache Spark UI offers the possibility to enable ACLs via the configuration option spark.acls.enable. | 8.8 |
2022-03-10 | CVE-2021-38296 | Authentication Bypass by Capture-replay vulnerability in multiple products Apache Spark supports end-to-end encryption of RPC connections via "spark.authenticate" and "spark.network.crypto.enabled". | 7.5 |
2020-06-23 | CVE-2020-9480 | Missing Authentication for Critical Function vulnerability in multiple products In Apache Spark 2.4.5 and earlier, a standalone resource manager's master may be configured to require authentication (spark.authenticate) via a shared secret. | 9.8 |
2018-07-12 | CVE-2018-1334 | Information Exposure vulnerability in Apache Spark 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. | 4.7 |
2017-07-12 | CVE-2017-7678 | Cross-site Scripting vulnerability in Apache Spark In Apache Spark before 2.2.0, it is possible for an attacker to take advantage of a user's trust in the server to trick them into visiting a link that points to a shared Spark cluster and submits data including MHTML to the Spark master, or history server. | 6.1 |