Categories
CVE-2017-12612 high CVSS 7.8

Unsafe Deserialization in Apache Spark (CVE-2017-12612)

Summary

Vulnerability in Apache Spark (CVE-2017-12612). Successful exploitation can lead to full system takeover.

Original description

The description as published by the source.

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.

Source: NIST National Vulnerability Database NVD GitHub Advisory

Auto-generated summary

Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.

A vulnerability tracked as CVE-2017-12612 has been found in Apache Spark.
Successful exploitation can lead to full system takeover. CVSS score: 7.8/10.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "Apache Spark CVE-2017-12612" on the vendor's site.

CVE-2017-12612 (Apache Spark) — CWE-502 / CVSS v3 7.8
Attack vector: local / no user interaction
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.

❓ What is the problem

Unsafe deserialization (CWE-502) exists in Apache Spark.

📍 Affected scope

Check the vendor advisory for the affected versions of Apache Spark.

🔥 Severity

Severity: High (CVSS 7.8/10). Successful exploitation can lead to full system takeover.

🔧 How to fix

Update to the patched release per vendor advisory.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'Spark' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.

Response actions

Concrete steps and command examples for SOC/SRE teams to execute in order

  1. 1
    Identify exposure identify
    grep -r 'Spark' . | grep -v node_modules

    リポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で Spark を grep し、稼働しているサービス・バージョンを把握する。

  2. 2
    Post-deployment verification verify
    Confirm patched version is live in production

    パッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。

References

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