OCSF Simulator
A Python library and CLI that generates simulated OCSF (Open Cybersecurity Schema Framework) event streams. Useful for testing streaming pipelines, security analytics tools, SIEMs, and detection rules with realistic synthetic data.
Install
pip install .
Optional extras:
pip install ".[ocsf]" # use the real ocsf-lib schema
pip install ".[kafka]" # enable Kafka output
pip install ".[all]"
Use as a CLI
By default, events are written as JSON lines to stdout:
ocsf-sim --interval 1.0 --batch-size 5 --max-events 20
Send events to Kafka instead:
ocsf-sim --enable-kafka --kafka-servers localhost:9092 --kafka-topic ocsf-events
Common flags:
| Flag | Description |
|---|---|
--interval |
Seconds between batches (default 1.0) |
--batch-size |
Events per batch (default 10) |
--max-events |
Stop after generating N events |
--duration |
Stop after N minutes |
--event-classes |
OCSF class UIDs to generate (default 3002 4001 1007 2001) |
--profiles |
OCSF profiles to apply (default cloud security_control) |
--ocsf-version |
OCSF schema version (default 1.1.0) |
--enable-kafka |
Publish events to Kafka |
Run ocsf-sim --help for the full list.
Use as a library
from ocsf_simulator import JSONSchemaFaker, stream_ocsf_events
# One-shot event generation
faker = JSONSchemaFaker(ocsf_version="1.1.0")
event = faker.generate_ocsf_event(3002, profiles=["host", "security_control"])
# Streaming generator (yields events forever)
for event in stream_ocsf_events(event_classes=[3002, 4001], interval=1.0):
print(event)
Supported event classes
The simulator can generate events for any OCSF class, with richer dedicated generators for these commonly-used ones:
| UID | Class |
|---|---|
| 1001 | File System Activity |
| 1007 | Process Activity |
| 2001 | Security Finding |
| 3002 | Authentication |
| 4001 | Network Activity |
License
Apache-2.0
Metadata
Release files for timeplus-ocsf-simulator 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| timeplus_ocsf_simulator-0.1.0.tar.gz | 2.6 MB | Without provenance | Details for timeplus_ocsf_simulator-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| timeplus_ocsf_simulator-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for timeplus_ocsf_simulator-0.1.0-py3-none-any.whl |
Total release size: 5.1 MB
Release files / timeplus_ocsf_simulator-0.1.0.tar.gz
| Download URL | timeplus_ocsf_simulator-0.1.0.tar.gz |
|---|---|
| Size | 2.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
88a5bc689148d2e1a1999cfba9163ad3340f38929750f30d50e0450793c1d88c
|
|
BLAKE2b-256 checksum How to use checksums |
f9ae4550dc260bc119790c200429124211ade6d581dd6f0b9a290daaf82b36bd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.6
|
Release files / timeplus_ocsf_simulator-0.1.0-py3-none-any.whl
| Download URL | timeplus_ocsf_simulator-0.1.0-py3-none-any.whl |
|---|---|
| Size | 2.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b25e74635859b24c2e303c5b40f516c746c759b847af204d1b6a23efa2935e07
|
|
BLAKE2b-256 checksum How to use checksums |
a2347d36c96884bb5a75cc0acdc03743e9a079e721e4310a75c067ece1c897d0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.6
|
Security for timeplus-ocsf-simulator 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.