An administrator wants to ensure that none of the ES indexed data could be compromised through tampering. What feature would satisfy this requirement?

The correct choice is data integrity, which is essential in maintaining the accuracy and consistency of data throughout its lifecycle. Ensuring data integrity means implementing measures that protect the data from unauthorized alterations or corruption. In the context of Splunk Enterprise Security, this can include checksums, hash validations, and other mechanisms that help confirm that the data remains unaltered after being indexed. By focusing on data integrity, the administrator can ensure that the information remains reliable and trustworthy, which is crucial for security analytics and incident investigation.

While options like index consistency, indexer acknowledgement, and index access permissions may contribute to a secure data environment, they do not directly address the specific risk of data being compromised through tampering. Index consistency refers to ensuring data is consistent across indexes, indexer acknowledgement pertains to the confirmation that data has been successfully indexed, and index access permissions control who can access the indexed data. None of these features are primarily focused on the prevention of tampering, which is why data integrity stands out as the most relevant solution in this scenario.