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Including CVEs outside Waratek scope✕Protection: None✕Product spark-core✕
Overview 11 matches · 9 in Waratek scope · 0 protected · 1 exploited · 0 CISA KEV · 2 public PoC · 1 EPSS ≥ 0.5
11matches 9in Waratek scope81.8% 0protected0.0% 1exploited9.1% 0CISA KEV0.0% 2public PoC18.2% 1EPSS ≥ 0.59.1%
Protected by Waratek 0 0.0% Rule in development 0 0.0% Mitigation candidate 1 9.1% No exploit published 8 72.7% Outside Waratek scope 0 0.0% Not applicable 2 18.2% Withdrawn CVE 0 0.0%
Critical 2 18.2% High 3 27.3% Medium 6 54.5% Low 0 0.0% None 0 0.0% Unknown 0 0.0%
blocked by ARMR today 0 0.0% partly blocked 0 0.0% not blocked 11 100.0% not established 0 0.0% unrecorded 0 0.0%
Exploited 1 9.1% Working exploit published 1 9.1% Proof of concept only 0 0.0% Forecast only 0 0.0% No public exploit 9 81.8%
split by peak 5 / year
Not applicable: 2No exploit published: 8Mitigation candidate: 1 Medium: 6High: 3Critical: 2 not blocked: 11 No public exploit: 9Working exploit published: 1Exploited: 1
20171 No exploit published1 Medium1 not blocked1 No public exploit1 20185 Mitigation candidate1 No exploit published2 Not applicable2 Critical1 High1 Medium3 not blocked5 Exploited1 Working exploit published1 No public exploit3 20191 No exploit published1 High1 not blocked1 No public exploit1 20200 20210 20222 No exploit published2 High1 Medium1 not blocked2 No public exploit2 20231 No exploit published1 Critical1 not blocked1 No public exploit1 20240 20250 20261 No exploit published1 Medium1 not blocked1 No public exploit1
2017201820192020202120222023202420252026
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CVE Severity Published▾ Status Exploitation Description
CVE-2026-32773 Medium 2026-09-02 No exploit published No public exploit There is a lack of XSS escaping in the Spark History Server prior to 3.5.8 which allows a malicious Spark job to generate arbitrary unescaped frontend code which could lead to a minimal privilege escalation in browser. Users are encouraged to upgrade to Spark 3.5.8 or later. This CVE is marked as "low" since the path to exploit requires both relatively high permissions (ability to launch a Spark job) and requires tricking a user with higher permissions to log in and visit the Spark history web page. Users are encouraged to upgrade their Spark history servers to Spark 3.5.8 or later.
CVE-2023-22946 Critical 2023-04-17 No exploit published No public exploit In Apache Spark versions prior to 3.4.0, applications using spark-submit can specify a 'proxy-user' to run as, limiting privileges. The application can execute code with the privileges of the submitting user, however, by providing malicious configuration-related classes on the classpath. This affects architectures relying on proxy-user, for example those using Apache Livy to manage submitted applications. Update to Apache Spark 3.4.0 or later, and ensure that spark.submit.proxyUser.allowCustomClasspathInClusterMode is set to its default of "false", and is not overridden by submitted applications.
CVE-2022-31777 Medium 2022-11-01 No exploit published No public exploit 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.
CVE-2021-38296 High 2022-03-10 No exploit published No public exploit Apache Spark supports end-to-end encryption of RPC connections via "spark.authenticate" and "spark.network.crypto.enabled". In versions 3.1.2 and earlier, it uses a bespoke mutual authentication protocol that allows for full encryption key recovery. After an initial interactive attack, this would allow someone to decrypt plaintext traffic offline. Note that this does not affect security mechanisms controlled by "spark.authenticate.enableSaslEncryption", "spark.io.encryption.enabled", "spark.ssl", "spark.ui.strictTransportSecurity". Update to Apache Spark 3.1.3 or later
CVE-2019-10099 High 2019-08-07 No exploit published No public exploit Prior to Spark 2.3.3, in certain situations Spark would write user data to local disk unencrypted, even if spark.io.encryption.enabled=true. This includes cached blocks that are fetched to disk (controlled by spark.maxRemoteBlockSizeFetchToMem); in SparkR, using parallelize; in Pyspark, using broadcast and parallelize; and use of python udfs.
CVE-2018-17190 Critical 2018-11-19 Not applicable No public exploit In all versions of Apache Spark, its standalone resource manager accepts code to execute on a 'master' host, that then runs that code on 'worker' hosts. The master itself does not, by design, execute user code. A specially-crafted request to the master can, however, cause the master to execute code too. Note that this does not affect standalone clusters with authentication enabled. While the master host typically has less outbound access to other resources than a worker, the execution of code on the master is nevertheless unexpected.
CVE-2018-11804 High 2018-10-24 No exploit published No public exploit Spark's Apache Maven-based build includes a convenience script, 'build/mvn', that downloads and runs a zinc server to speed up compilation. It has been included in release branches since 1.3.x, up to and including master. This server will accept connections from external hosts by default. A specially-crafted request to the zinc server could cause it to reveal information in files readable to the developer account running the build. Note that this issue does not affect end users of Spark, only developers building Spark from source code.
CVE-2018-11770 Medium 2018-08-13 Mitigation candidate Exploited From version 1.3.0 onward, Apache Spark's standalone master exposes a REST API for job submission, in addition to the submission mechanism used by spark-submit. In standalone, the config property 'spark.authenticate.secret' establishes a shared secret for authenticating requests to submit jobs via spark-submit. However, the REST API does not use this or any other authentication mechanism, and this is not adequately documented. In this case, a user would be able to run a driver program without authenticating, but not launch executors, using the REST API. This REST API is also used by Mesos, when set up to run in cluster mode (i.e., when also running MesosClusterDispatcher), for job submission. Future versions of Spark will improve documentation on these points, and prohibit setting 'spark.authenticate.secret' when running the REST APIs, to make this clear. Future versions will also disable the REST API by default in the standalone master by changing the default value of 'spark.master.rest.enabled' to 'false'.
CVE-2018-8024 Medium 2018-07-12 Not applicable Working exploit published In Apache Spark 2.1.0 to 2.1.2, 2.2.0 to 2.2.1, and 2.3.0, it's possible for a malicious user to construct a URL pointing to a Spark cluster's UI's job and stage info pages, and if a user can be tricked into accessing the URL, can be used to cause script to execute and expose information from the user's view of the Spark UI. While some browsers like recent versions of Chrome and Safari are able to block this type of attack, current versions of Firefox (and possibly others) do not.
CVE-2018-1334 Medium 2018-07-12 No exploit published No public exploit 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.
CVE-2017-7678 Medium 2017-07-12 No exploit published No public exploit 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. This data, which could contain a script, would then be reflected back to the user and could be evaluated and executed by MS Windows-based clients. It is not an attack on Spark itself, but on the user, who may then execute the script inadvertently when viewing elements of the Spark web UIs.