9680e54c90
fpr: fuscript, linuxbrew, snapd, msedge |
||
---|---|---|
.github | ||
detection | ||
fragments | ||
images | ||
incident_response | ||
policy | ||
vulnerabilities | ||
.gitignore | ||
LICENSE.txt | ||
Makefile | ||
README.md | ||
osquery.conf |
README.md
osquery-defense-kit
osquery queries for Detection & Incident Response, containing 250+ production-ready queries.
ODK (osquery-defense-kit) is unique in that the queries are designed to be used as part of a production detection & response pipeline. The detection queries are formulated to return zero rows during normal expected behavior, so that they may be configured to generate alerts when rows are returned.
At the moment, these queries are predominantly designed for execution on POSIX platforms (Linux & macOS). Pull requests to improve support on other platforms are fully welcome.
Requirements
- osquery v5.7.0 or above
- macOS or Linux
- If you plan to do local development you will also need Go v1.20+ for osqtool
Usage
Local Detection
Run make detect
for point-in-time detection. This will not detect as much as a production installation as it will not have access to historical events.
Production Detection
Download a released query pack into a convenient location, and point to these files from the packs
stanza of your osquery.conf
file
Local Data Collection for IR
Run make collect
. This is particularly useful for before/after analysis.
Local pack generation
Run make packs
. For more control, you can invoke osqtool directly, to override default intervals or exclude checks.
Local verification testing
Run make verify
File Organization
detection/
- Threat detection queries tuned for alert generation.policy/
- Security policy queries tuned for alert generation.incident_response/
- Data collection to assist in responding to possible threats. Tuned for periodic evidence collection.
The detection queries are further divided up by MITRE ATT&CK tactics categories.
At release time, the queries are packed up in osquery query pack format. See Local Pack Generation
for information on how to generate your own packs at any time.
Case Studies
Linux: Shikitega (September 2022)
https://cybersecurity.att.com/blogs/labs-research/shikitega-new-stealthy-malware-targeting-linux
Here is a partial list of what queries would have fired an alert based on these queries:
- Initial Dropper Execution, detected by:
execution/tiny-executable-events.sql
execution/tiny-executable.sql
- Next Stage Dropper Execution, detected by:
execution/tiny-executable-events.sql
execution/tiny-executable.sql
execution/unexpected-shell-parents.sql
- Escalation Prep, detected by:
execution/sketchy-fetchers.sql
execution/sketchy-fetcher-events.sql
c2/unexpected-talkers-linux.sql
c2/exotic-command-events.sql
c2/exotic-cmdline.sql
- Escalation Tool Execution detected by:
execution/unexpected-executable-permissions.sql
execution/unexpected-executable-directory-linux.sql
execution/unexpected-tmp-executables.sql
c2/exotic-command-events.sql
c2/exotic-cmdline.sql
initial_access/unexpected-shell-parents.sql
evasion/missing-from-disk-linux.sql
- Privilege Escalation detected by:
privesc/unexpected-setxid-process.sql
privesc/unexpected-privilege-escalation.sql
privesc/events/unexpected-privilege-escalation-events.sql
evasion/name_path_mismatch.sql
- Persistence detected by:
persistence/unexpected-cron-entries.sql
execution/unexpected-executable-directory-linux.sql
macOS: CloudMensis (April 2022)
https://www.welivesecurity.com/2022/07/19/i-see-what-you-did-there-look-cloudmensis-macos-spyware/
Here is a partial list of what stages would have been detected by particular queries:
-
Initial Dropper Execution, detected by:
c2/unexpected-talkers-macos.sql
-
Second Stage Execution, detected by:
execution/unexpected-executable-directory-macos.sql
persistence/unexpected-launch-daemon-macos.sql
execution/unexpected-mounts.sql
-
TCC Bypass, detected by:
evasion/unexpected-env-values.sql
-
Spy Agent Execution, detected by:
c2/unexpected-talkers-macos.sql
execution/exotic-command-events.sql
execution/unexpected-executable-directory-macos.sql
Policies
Contributions
Help Wanted! We support any new queries so long as they can be easily updated to address false positives.
Users may submit false positive exceptions for popular well-known software packages, but may be asked to provide evidence for the behavior.
Platform Support
While originally focused on Linux and macOS, we support the addition of queries on any platform supported by osquery.
In particular, we've been asked about Windows support: Chainguard doesn't have any Windows machines, but if you have Windows queries that you think would be useful and match our philosophy, we're more than willing to accept them!
False Positives
We endeavor to exclude real-world false positives from our detection
queries.
Managing false positives is easier said than done - pull requests are welcome!
CPU Overhead
In aggregate, queries should not consume more than 2% of the wall clock time across a day on a deployed system.
Intervals
Deployed intervals are automatically determined based on the tags supported by the osqtool, which we use for pack assembly.