Medium Org.apache.spark CVEs with no public exploit
6 CVEs
Overview 6 matches · 0 protected · 0 exploited · 0 CISA KEV · 0 public PoC · 0 EPSS ≥ 0.5
6matches
0protected0.0%
0exploited0.0%
0CISA KEV0.0%
0public PoC0.0%
0EPSS ≥ 0.50.0%
Protected by Waratek
0
0.0%
Rule in development
0
0.0%
Mitigation candidate
0
0.0%
No exploit published
6
100.0%
blocked by ARMR today
0
0.0%
partly blocked
0
0.0%
not blocked
6
100.0%
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
6
100.0%
split by
peak 1 / year
20171
No exploit published1
Medium1
not blocked1
No public exploit1
20181
No exploit published1
Medium1
not blocked1
No public exploit1
20190
20200
20210
20221
No exploit published1
Medium1
not blocked1
No public exploit1
20230
20241
No exploit published1
Medium1
not blocked1
No public exploit1
20251
No exploit published1
Medium1
not blocked1
No public exploit1
20261
No exploit published1
Medium1
not blocked1
No public exploit1
2017201820192020202120222023202420252026
| 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-2025-55039 | 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-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-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. |