CVE-2026-104002 in Powertools Lambda Python
Summary
by MITRE • 10/02/2026
A fail-open error handling issue within the data masking utility of Powertools for AWS Lambda (Python) might allow actors to read sensitive field values that the application intended to mask.
To remediate this issue, users should upgrade to version 3.35.0.
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Analysis
by VulDB Data Team • 10/02/2026
The vulnerability identified in Powertools for AWS Lambda involves a critical logic error within its data masking utility, specifically categorized as a fail-open condition during exception handling. In secure software design, when an operation such as sensitive data redaction fails due to unexpected input or internal errors, the system should default to a safe state where access is denied or data remains obscured. However, in this instance, the error handling mechanism allows execution to proceed without masking the underlying values if specific conditions are met during processing. This architectural flaw means that instead of throwing an exception and halting the operation to prevent exposure, the utility may return the raw, unmasked data to the calling function or application layer.
From a technical perspective, this issue stems from how the library manages exceptions raised by its underlying masking logic. When the parser encounters malformed input or encounters edge cases that trigger internal errors, the catch block does not enforce strict output sanitization. Instead of ensuring that masked placeholders are returned regardless of processing success, it inadvertently passes through the original sensitive payload. This behavior violates the principle of least privilege and secure defaults, as it assumes a level of data integrity that is not guaranteed during runtime failures or when handling unexpected input formats common in dynamic serverless environments.
The operational impact of this vulnerability is severe for applications relying on Powertools to comply with regulatory requirements such as GDPR, HIPAA, or PCI-DSS. Sensitive fields including personally identifiable information (PII), financial data, or authentication credentials could be inadvertently logged, returned in API responses, or stored in downstream services without proper obfuscation. Since AWS Lambda functions often handle high volumes of requests and integrate with various logging mechanisms like CloudWatch Logs, an unmasked value might end up in plaintext logs if the application developer assumes masking was successful. This creates a significant risk of data leakage to unauthorized actors who may have access to log streams or API responses.
This vulnerability aligns closely with CWE-209: Generation of Error Message Containing Sensitive Information and CWE-754: Improper Check for Unusual or Exceptional Conditions, as the system fails to handle exceptional states securely by defaulting to an open state rather than a closed one. In terms of MITRE ATT&CK tactics, this flaw facilitates Data Exfiltration from Application Logs (T1005) and potentially Unauthorized Access to Sensitive Information if attackers can trigger specific error conditions through crafted inputs. The fail-open nature means that even without direct exploitation skills, an attacker could potentially induce the failure state by sending malformed payloads, thereby triggering the leak of sensitive data during normal application operation.
To remediate this issue, organizations must upgrade Powertools for AWS Lambda to version 3.35.0 or later, where the error handling logic has been corrected to ensure that masking failures result in safe defaults rather than exposing raw data. In addition to upgrading, developers should implement defense-in-depth strategies by validating input formats before they reach the masking utility and ensuring that logging configurations do not inadvertently capture full request payloads containing sensitive fields. Regular security audits of serverless function code paths are recommended to verify that no other components rely on similar fail-open patterns for critical data protection mechanisms.