In this lesson, you will learn how to create automated scripts to identify files with non-standard ACL assignments across a large enterprise filesystem.
When managing enterprise storage, auditing permissions manually is impossible. ACLs provide granular control, but they often lead to "permission drift" where files accumulate unintended access rights over time. To maintain security, you need to programmatically scan your directories to flag objects that deviate from your organization’s standard security policy.
The Auditing Logic
The most efficient way to audit ACLs at scale is by combining the getfacl command with standard text processing tools like awk or grep. While ls -l shows a + symbol to indicate an ACL exists, it doesn't show the content. For an audit, we need to extract the specific entries and compare them against a baseline.
Consider this script snippet designed to find any file that contains an explicit "named user" ACL entry, which is often considered a non-standard configuration in strictly UGO-governed environments:
# Find all files with ACLs and search for specific named user entries
find /data/storage -type f -exec getfacl -p {} + | \
awk '/^# file:/ {filename=$3} /user:[^:]+:/ {print "Non-standard ACL found on: " filename}'
Why Automation Matters
In this script, the find command traverses the filesystem, and getfacl -p outputs the absolute path and ACL rules. The awk command maintains state: when it sees a filename, it remembers it, and when it detects a user: entry (representing a named user rather than an owner or "others"), it flags the file for human review.
By automating this, you aren't just looking for any ACL; you are looking for specific violations. In a production environment, you might expand this script to output results into a CSV format or trigger an alert when an ACL exceeds the standard mask, ensuring that your layered defense strategy remains intact without manual oversight.
Key Takeaway: Automating ACL audits requires piping getfacl output into text processing tools to identify and filter out unauthorized permission patterns at scale.