CVE-2023-50290

What is this vulnerability?

CVE-2023-50290 is categorized as a medium Information Exposure flaw with a CVSS base score of 6.5. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

Exposure of Sensitive Information to an Unauthorized Actor vulnerability in Apache Solr. The Solr Metrics API publishes all unprotected environment variables available to each Apache Solr instance. Users are able to specify which environment variables to hide, however, the default list is designed to work for known secret Java system properties. Environment variables cannot be strictly defined in Solr, like Java system properties can be, and may be set for the entire host, unlike Java system properties which are set per-Java-proccess.

The Solr Metrics API is protected by the "metrics-read" permission. Therefore, Solr Clouds with Authorization setup will only be vulnerable via users with the "metrics-read" permission. This issue affects Apache Solr: from 9.0.0 before 9.3.0.

Users are recommended to upgrade to version 9.3.0 or later, in which environment variables are not published via the Metrics API.

This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.

Risk Assessment

Impact on Systems

✅ Credential Theft: Exposed secrets enable unauthorized access to infrastructure, cloud services, and third-party integrations.

✅ Compliance Violation: Leaking PII or credentials may violate GDPR, HIPAA, PCI-DSS, and SOC 2 requirements.

✅ Supply Chain Risk: Compromised credentials in public repositories can propagate to downstream consumers.

How to Fix and Mitigate CVE-2023-50290

1. Apply Vendor Patches: Upgrade affected components to their latest, non-vulnerable versions immediately.
2. Implement Input Validation: Ensure all user-supplied data is validated, sanitized, and type-checked before processing.
3. Deploy Runtime Protection: Use Precogs continuous monitoring to detect exploitation attempts in real time.
4. Audit Dependencies: Review and update all third-party libraries and transitive dependencies.

Defending with Precogs AI

Apache Solr exposes sensitive information to unauthorized actors through unauthenticated metrics endpoints or verbose error messages. Attackers extract system configuration details to map the attack surface. Precogs API Security Engine audits endpoint access controls and error response verbosity.

Use Precogs to continuously scan your codebase, binaries, APIs, and infrastructure for this vulnerability class and related attack patterns. Our AI-powered detection engine combines static analysis with threat intelligence to identify exploitable weaknesses before attackers do.

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Vulnerability Code Signature

Attack Data Flow

Vulnerable Code Pattern

# ❌ VULNERABLE: Information Exposure
@app.errorhandler(500)
def internal_error(error):
    # Taint sink: returns stack trace to user
    return f"Internal Server Error: {error}", 500

Secure Code Pattern

# ✅ SECURE: Generic error message
@app.errorhandler(500)
def internal_error(error):
    # Log the detailed error internally
    app.logger.error(f"Server Error: {error}")
    # Return a generic message to the user
    return "An internal server error occurred.", 500

How Precogs Detects This

Precogs API Security Engine comprehensively audits all web endpoints to ensure verbose error messages and sensitive metadata are not exposed.\n