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Maven🐍 PyPI

CVE-2017-12612

HIGH

Apache Spark Deserialization of Untrusted Data vulnerability

Also known asGHSA-8rhc-48pp-52grPYSEC-2017-147
Published
Sep 13, 2017
Updated
Jul 8, 2026
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed

Blast Radius

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

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

Description

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.

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
Mavenorg.apache.spark:spark-core_2.11all versions2.1.2
Mavenorg.apache.spark:spark-core_2.10all versions2.1.2
🐍PyPIpysparkall versions2.1.2

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_2.11. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update org.apache.spark:spark-core_2.11 to 2.1.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2017-12612 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether CVE-2017-12612 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to CVE-2017-12612. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

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.
O3 Security · Impact-Aware SCA

Is CVE-2017-12612 in your dependencies?

O3 detects CVE-2017-12612 across Maven, PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.