java-sensitive-log-auditor

To detect sensitive data leaks in Java logs, you need to audit code for exposures in SLF4J/Log4j outputs, System.out/err, and exception messages by analyzing sensitive field names like iban or password. This process identifies potential breaches and returns structured findings with severity and masking recommendations.

The best way to check Java code for GDPR and PCI-DSS logging violations is to scan .java files for sensitive data exposures in stack traces and exception messages. This audit detects sources like email and password literals, providing remediation guidance to ensure compliance.

Sensitive data detection works by analyzing Java code to locate sinks, such as log outputs and toString methods, and tracing them back to sources like sensitive field names and literals. It then reports these exposures with structured findings and safe masking patterns.

Yes, you can use this audit to find unmasked IBAN or DNI fields by scanning Java services that use Log4j. The auditor detects sensitive field names and literals in log outputs, returning structured findings with masking recommendations to secure the data.

Common sources of sensitive data exposure in Java applications include sensitive field names like iban, dni, email, and password, as well as hardcoded literals. These sources often leak through SLF4J/Log4j logs, System.out/err, and unmasked toString outputs in exception messages.

Yes, this logging audit works for code reviews of Java services by scanning .java files to identify sensitive data exposures in logging practices. It returns structured findings with severity levels and remediation guidance to help teams fix issues during the review process.