SparkApplication · Apache
CVE-2017-12612
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedIn 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.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · high confidenceThe Apache Spark launcher API performs unsafe deserialization of data received through its socket connection in versions 1.6.0 through 2.1.1. An attacker with access to any user account on the local machine can exploit this to achieve arbitrary code execution as the user running the Spark application. This vulnerability only affects applications launched programmatically via the launcher API, not those run through spark-submit or spark-shell.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data
SparkApplication
= 1.6.0= 1.6.1= 1.6.2= 1.6.3= 2.0.0= 2.0.1= 2.0.2= 2.1.0= 2.1.1CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Local
- Complexity
- Low
- Privileges
- Low
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Identify installed Spark versionRun `spark-submit --version` or check the SPARK_HOME directory for a version fileAffected if The version is 1.6.0, 1.6.1, 1.6.2, 1.6.3, 2.0.0, 2.0.1, 2.0.2, 2.1.0, or 2.1.1
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Determine if programmatic launcher API is usedSearch source code for imports of `org.apache.spark.launcher` package or usage of `SparkLauncher` classAffected if The application uses SparkLauncher or related classes to launch Spark programmatically
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Identify socket-based launcher communicationReview application code to see if it uses the socket-based launcher (default behavior when using SparkLauncher)Affected if The SparkLauncher is configured to use default socket-based communication (not Kerberos or other authentication)
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Check for untrusted local user accessAudit local system accounts and filesystem permissions on the Spark working directoryAffected if Local untrusted users have write access to the directory where Spark launcher socket communications occur
You are affected if Spark version is between 1.6.0 and 2.1.1 inclusive AND your application programmatically launches Spark using the launcher API without additional authentication on socket communications.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
From vendor dataUpgrade Apache Spark to version 2.2.0 or later to remediate this vulnerability. Alternatively, audit and refrain from using the programmatic launcher API in affected versions.
Fix this in Spark
Scoped from the published advisory
- Consultation8.0 h
- Implementation16.0 h
- Testing12.0 h
- Review / QA4.0 h
An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $11,200.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2017-12612 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2017-12612 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Verified mitigations, workarounds, and config changes
- Version or environment caveats, and links to real fixes
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