osquery differential results
osquery differential results. Scheduled query differential results describe rows added or removed relative to the query’s prior state.
Source and collection
Configured logger destination, commonly osqueryd.results.log; not the INFO status log.
Review the scheduled SQL, interval, host identifier and differential versus snapshot mode.
Native example and provenance
publisher documentation example. Published example; no independent capture provenance claimed.
Original publisher / pinned upstream fixture — preformatted example 6
One complete record selected; values unchanged.
Download the exact sample · Offline research kit
SHA-256: 09436c141a9bcdc9adde91df59d9b5b17ad2af4b37541614fb293f51a837a84d
{
"action": "added",
"columns": {
"name": "osqueryd",
"path": "/opt/osquery/bin/osqueryd",
"pid": "97830"
},
"name": "processes",
"hostname": "hostname.local",
"calendarTime": "Tue Sep 30 17:37:30 2014",
"unixTime": "1412123850",
"epoch": "314159265",
"counter": "1",
"numerics": false
}
Structure and field interpretation
| Field/path | Serialized type |
|---|---|
action | str |
columns.name | str |
columns.path | str |
columns.pid | str |
name | str |
hostname | str |
calendarTime | str |
unixTime | str |
epoch | str |
counter | str |
numerics | bool |
- action
- added, removed or snapshot semantics depend on logger mode.
- columns
- Result values from the scheduled SQL; values are commonly strings.
- name
- Scheduled query name.
- unixTime
- Event time represented as epoch seconds.
Investigation uses
- Investigate a new process or configuration row with its query name and schedule.
- Keep removed and added results together when evaluating state changes.
Validation boundaries
A scheduled process-table query can miss short-lived processes. An added row is a state delta, not automatically a real-time creation event.
This sample passed byte-integrity and JSON/XML parsing checks, including the catalogue’s specified event discriminators. This is not a complete vendor-schema validation or a tested detection.
For a simulation, first parse this fixture offline, then create a separately labelled synthetic variant and test it against the intended collector in an isolated lab. Never replay public example identities or destinations into production.
Related sources
Ecosystem connections
- Telemetry Library — ATT&CK data components
- Detection Rules — candidate detection content
- Threat hunting — from intelligence to validated defense
- Practical security learning paths
- AdversaryGraph — evidence-led investigation
References
Sample provenance is linked above. Field availability and product behavior must be checked against the deployed version.