Critical Vulnerability in Apache Parquet Java Library: What You Need to Know

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Whether you’re a data engineer, DevOps professional, or security analyst, understanding this vulnerability is essential. Here’s a breakdown of what went wrong, who’s affected, and what you can do to secure your systems.

the Threat: CVE-2025-30065 in Apache Parquet Java Library

– Vulnerability ID: CVE-2025-30065

– Severity: Critical (CVSS Score 10.0)

– Type: Deserialization of Untrusted Data

Affected Component: parquet-avro module in Apache Parquet Java

– Impacted Versions: 1.8.0 to 1.15.0

– Fixed Version: 1.15.1

What Is Apache Parquet?

Apache Parquet is a columnar storage format optimized for complex data processing. It is widely used in frameworks such as Apache Spark, Hadoop, Flink, and Drill, especially in big data and analytics ecosystems.

What Went Wrong?

Security researchers discovered a vulnerability in the schema parsing logic of the parquet-avro module. This allows attackers to craft malicious Parquet files which, when parsed by the Java library, can execute arbitrary code on the host system.

Attack Vector

The vulnerability hinges on the deserialization of data without proper validation. An attacker only needs to convince a target system to import a malicious Parquet file, potentially leading to full remote code execution.

Real-World Impact

According to Endor Labs:

Systems using unpatched versions are exposed to complete takeover if an attacker succeeds.
No active exploits are currently known (as of April 2025), but public disclosure raises the risk.

– Impacts include:

– Breach of data confidentiality

– Corruption or destruction of data (integrity)

– Denial of service or system shutdown (availability)

Who Is at Risk?

Big data infrastructures using Apache Spark, Hadoop, Flink, and Drill

– Custom applications importing and processing Parquet files

Any system not running Apache Parquet Java 1.15.1 or later

Recommended Actions

Upgrade Immediately: Move to Apache Parquet Java v1.15.1 or higher.
Avoid Untrusted Files: Reject or thoroughly validate Parquet files from unknown sources.
Harden Input Handling: Add schema validation and deserialization safeguards.
Enable Monitoring: Log Parquet file imports and set up behavioral anomaly detection.
Stay Informed: Follow Apache security advisories and updates.

What Undercode Say:

This vulnerability is more than just another CVE—it’s a red flag for how open-source data tools can become high-value targets when integrated into large infrastructures. At Undercode, we analyze not just the threat, but the ecosystem-level implications:

1. Open-Source Risk Revisited

Apache Parquet, like many open-source libraries, is deeply embedded in enterprise pipelines. This makes such flaws exponentially dangerous—a small library can bring down an entire system. It’s time to re-evaluate how dependencies are managed and monitored.

2. Deserialization: The Silent Killer

Deserialization vulnerabilities are notoriously hard to detect and easy to exploit. This flaw is a textbook case of how unchecked data formats can act as Trojan horses. Developers must enforce strict controls when parsing any external input, even from seemingly “safe” file formats.

3. Why Columnar Formats Need More Scrutiny

Columnar formats like Parquet are optimized for efficiency—but with that comes complexity. Schema parsing, metadata handling, and compression all introduce potential attack surfaces. Security must evolve alongside performance.

4. Incident Response Needs a Shift

Companies should have clear policies for third-party data ingestion, with pre-processing sandboxes, schema validation, and signature checks. Waiting for an exploit to emerge is no longer acceptable.

5. Future Exploits Are Inevitable

Now that this bug is public, we predict PoCs and exploits will surface within weeks. Automated scanners will likely be updated to hunt for vulnerable endpoints—especially those running Jupyter notebooks or Spark clusters exposed to the internet.

6. Supply Chain Fallout

Parquet isn’t just used by developers. It’s embedded in ETL tools, data lakes, machine learning pipelines, and cloud-native services. Companies may be affected without realizing it. The blast radius of this vulnerability is larger than it appears.

7. Security Teams Must Lead the Response

This is a DevSecOps moment. Security must guide development and data teams in patching, monitoring, and architecting better input pipelines. Open-source software is a shared responsibility.

Fact Checker Results:

✅ The vulnerability is confirmed and officially tracked as CVE-2025-30065.
✅ CVSS score of 10.0 is accurate as per industry advisory reports.
✅ No public exploits exist as of April 2025, but mitigation is urgent.

Stay alert, patch fast, and reassess your data pipeline hygiene. This isn’t just a bug—it’s a wake-up call for the entire big data ecosystem.

References:

Reported By: https://securityaffairs.com/176187/security/apache-parquets-java-library-critical-flaw.html
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