CVE-2026-59300 in Spring Cloud Function
Summary
by MITRE • 08/27/2026
Potential for logging sensitive data in Spring Cloud Function AWS. Spring Cloud Function 5.0.0 - 5.0.3 Spring Cloud Function 4.3.0 - 4.3.4 Spring Cloud Function 4.2.0 - 4.2.7 Spring Cloud Function 3.2.16 and earlier
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Analysis
by VulDB Data Team • 08/27/2026
The identified vulnerability in Spring Cloud Function versions ranging from 3.2.16 through 5.0.3, specifically within the AWS adapter implementation, constitutes a significant information disclosure risk due to improper logging of sensitive data. This flaw arises when the framework processes incoming events for serverless functions deployed on Amazon Web Services Lambda environments. During the event handling lifecycle, particularly in versions prior to the patched releases, the internal logic responsible for parsing and validating input payloads inadvertently includes detailed representations of the raw request context or payload content within standard application logs. These logs are typically directed to stdout or stderr streams which AWS CloudWatch Logs aggregates by default, creating a direct pathway for sensitive information to be persisted in centralized logging systems where it may be accessible to operations teams, third-party monitoring services, or potentially attackers with compromised log access privileges.
From a technical perspective, this issue is classified under CWE-532, which covers the insertion of sensitive information into log files. The root cause lies in the serialization and stringification processes used by the AWS adapter when constructing diagnostic messages for debugging purposes. Instead of sanitizing or masking fields that contain personally identifiable information (PII), authentication tokens, session identifiers, or other confidential business data, the framework outputs these values as plain text within exception stack traces or informational log entries. This behavior persists across multiple major versions including 3.x, 4.x, and early 5.x releases, indicating a systemic design oversight in how input validation errors and general request metadata are reported to the developer console. The vulnerability is particularly dangerous because logging frameworks often operate with high verbosity levels during development or troubleshooting phases, increasing the likelihood that sensitive payloads will be captured without explicit awareness from the application developers who rely on Spring Cloud Function for abstraction over cloud provider specifics.
The operational impact of this vulnerability extends beyond simple data leakage to include potential compliance violations and security breaches. Organizations utilizing these versions may inadvertently violate regulatory requirements such as GDPR, HIPAA, or PCI-DSS which mandate strict controls over the storage and transmission of sensitive personal and financial data. If an attacker gains access to cloud logging infrastructure through misconfigured IAM roles or compromised credentials, they can harvest session tokens or user credentials directly from log entries generated by previous function invocations. This could lead to unauthorized access to backend systems, privilege escalation within the AWS environment, or further lateral movement across connected services. Furthermore, because Spring Cloud Function is often used in microservices architectures where functions communicate frequently, a single compromised instance can expose data flowing through multiple service boundaries, amplifying the blast radius of the incident.
To mitigate this risk, organizations must immediately upgrade to patched versions that address the logging sanitization logic: specifically Spring Cloud Function 5.0.4 or later for the latest release train, version 4.3.5 or higher for the 4.x line, and version 4.2.8 or above for the legacy 4.2 series. For users of the older 3.x branch, upgrading to version 3.2.17 is required as it represents the final security patch for that lineage. In addition to updating dependencies, developers should implement strict log filtering rules using tools like Logback or Log4j2 appenders to mask sensitive fields before they are written to output streams. It is also critical to review existing CloudWatch logs and other logging backends for any residual exposure of sensitive data from the vulnerable period and rotate any credentials that may have been exposed in those logs. Security teams should integrate static analysis tools configured with CWE-532 rules into their CI/CD pipelines to detect similar patterns in custom code, ensuring that future development adheres to secure coding standards regarding information handling. This vulnerability aligns with ATT&CK technique T1078, Valid Accounts, if the logged data includes credentials, and generally falls under the broader category of Sensitive Data Exposure as defined by OWASP Top 10 security risks for cloud-native applications.