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MEDIUM severity

CVE-2018-1334 — spark-core_2.10

MEDIUM

CVE-2018-1334 is a medium-severity (CVSS 4.7) Information Exposure vulnerability in org.apache.spark:spark-core_2.10. A fix is available for org.apache.spark:spark-core_2.10 — see the affected versions and patch details below.

Exposure of Sensitive Information to an Unauthorized Actor in Apache Spark

Also known asGHSA-6mqq-8r44-vmjcPYSEC-2018-25
Published
Updated
Affected
7 pkgs
Patched
7 / 7
Exploits
None indexed
Exploitation data as of Oct 23, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs43th percentile — riskier than 43% of all scored CVEsHighest risk
0.00%0.34%0.67%1.01%0.1%0.5%Apr 26Aug 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

CVE-2018-1334 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 395,249 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.

Real-World Exposure

7 pkgs affected
☕org.apache.spark:spark-core_2.10☕org.apache.spark:spark-core_2.10☕org.apache.spark:spark-core_2.11☕org.apache.spark:spark-core_2.11☕org.apache.spark:spark-core_2.11🐍pyspark🐍pyspark

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects Maven packages — download data is not available via public APIs for these ecosystems.

Description

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.

Affected Packages

7 total 7 fixed
EcosystemPackageVulnerable rangeFix
☕Mavenorg.apache.spark:spark-core_2.10≥ 1.0.0&&< 2.1.32.1.3org.apache.spark:spark-core_2.10:2.1.3
☕Mavenorg.apache.spark:spark-core_2.10≥ 2.2.0&&< 2.2.22.2.2org.apache.spark:spark-core_2.10:2.2.2
☕Mavenorg.apache.spark:spark-core_2.11≥ 1.0.0&&< 2.1.32.1.3org.apache.spark:spark-core_2.11:2.1.3
☕Mavenorg.apache.spark:spark-core_2.11≥ 2.2.0&&< 2.2.22.2.2org.apache.spark:spark-core_2.11:2.2.2
☕Mavenorg.apache.spark:spark-core_2.11≥ 2.3.0&&< 2.3.12.3.1org.apache.spark:spark-core_2.11:2.3.1
🐍PyPIpyspark≥ 2.2.0&&< 2.2.22.2.2pip install --upgrade 'pyspark==2.2.2'

Affected Products

1 product · 3 configurations
Application
sparkapache
≥ 2.2.0 && ≤ 2.2.1
1 version
2.3.0

Detection & mitigation playbook

Open-source dependency

  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for org.apache.spark:spark-core_2.10, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update org.apache.spark:spark-core_2.10 to 2.1.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2018-1334 is resolved across your whole dependency graph.

  3. Workarounds

    Assume what was exposed is already known: rotate any credential, token or key that the affected component could return, restrict the endpoint to callers that genuinely need it, and strip sensitive fields from responses and error output at the boundary rather than relying on the client not to read them.

Frequently Asked Questions

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.
O3 Security · Impact-Aware SCA

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CVE-2018-1334: spark-core_2.10 — Fixed in 2.1.3