osquery

osquery — SQL Lens on System State Why It Matters Admins spend time piecing together info: ps, netstat, digging through /var/log. Every system looks a bit different, and scripts pile up fast. osquery flips it around. It treats the OS as a database. System info becomes rows and tables you can query with SQL. Instead of custom scripts per host, you get one language to ask questions across Linux, macOS, and Windows.

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osquery — SQL Lens on System State

Why It Matters

Admins spend time piecing together info: ps, netstat, digging through /var/log. Every system looks a bit different, and scripts pile up fast. osquery flips it around. It treats the OS as a database. System info becomes rows and tables you can query with SQL. Instead of custom scripts per host, you get one language to ask questions across Linux, macOS, and Windows.

How It Works

The agent runs in the background and maps internals — processes, users, sockets, kernel modules, file hashes, startup items. You can poke it interactively with osqueryi, or let the daemon (osqueryd) collect on schedule. Data can be logged locally or shipped to a SIEM. Query packs make it easy to repeat checks fleet-wide: compliance audits, persistence lookups, or suspicious binaries. Same SQL runs on all supported OSes, so scaling is straightforward.

Technical Notes

Area Notes
Platforms Linux, Windows, macOS
Purpose Unified system visibility via SQL tables
Data scope Processes, users, sockets, configs, kernel modules, file integrity
Modes osqueryi (interactive), osqueryd (daemon)
Output JSON, local logs, SIEM feeds
License Apache 2.0, open source (originated at Facebook)

Deployment Notes

– Install via repo or vendor binary.
– Use osqueryi for ad-hoc queries like SELECT * FROM listening_ports;.
– Deploy osqueryd with packs for scheduled checks.
– Pipe results into ELK, Splunk, or any log shipper.
– Tune packs to avoid noise and CPU load.

Where It Fits

– Incident response: snapshot of processes, sockets, persistence.
– Compliance: standardized checks for PCI, HIPAA, CIS.
– Fleet ops: one query language across thousands of machines.
– Forensics: structured evidence collection.

Caveats

– Needs SQL literacy — not everyone is fluent.
– No prevention, visibility only.
– Badly written queries can spike CPU.
– For large rollouts, extra tooling like Fleet or Kolide is almost required.

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