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This rule detects potential AI model training data poisoning attempts by monitoring data pipeline audit logs for suspicious activities. Specifically, it flags bulk modifications to production training sets, ingestion from newly introduced external sources, or failures in data integrity checksums, which are indicative of attempts to influence or corrupt machine learning model training pipelines.
