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# distributed-network-event-detection-system
# Distributed Network Event Detection System
An alpha, graph-based Python network-intrusion-detection prototype. Its real-time components consume packet messages from Kafka, build and merge network graph state in Redis, dispatch node-analysis work, run model-based analysis, and print node results.
## Status and non-reproducible limitations
## Getting started
> **Not an end-to-end runnable deployment as checked out.** No packet producer/input-capture process or tested worker orchestration is provided. The included workers wait for messages on Kafka topics; starting them alone does not capture traffic.
To make it easy for you to get started with GitLab, here's a list of recommended next steps.
- The package metadata is alpha and only classifies Python 3.11. Its `readme = "README.md"` refers to a README missing from `graph_based_intrusion_detection/`, which may prevent standard package build metadata generation.
- Node analysis loads models and scalers from hard-coded absolute paths outside this repository. Although similarly named model files exist under `resources/models/`, the configured paths do not point there. Update the configuration for an environment before starting the node analyzer.
- Kafka and Redis addresses are hard-coded as `localhost:9092` and `localhost:6379` in the workers.
- The local Compose stack uses unpinned `latest` container images and is not a reproducible production deployment.
- No test suite, project test command, console entry point, or application deployment definition is present.
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
Do not use this prototype as a production intrusion-detection control without supplying and validating the missing capture, model-path, orchestration, retention, and security configuration.
## Add your files
## Components and data flow
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
The real-time code uses these Kafka topics and Redis state:
```
cd existing_repo
git remote add origin https://gitlab.com/blankinator/distributed-network-event-detection-system.git
git branch -M main
git push -uf origin main
1. `packet_processor` consumes `packets`, builds processed graph state, and publishes `processed_states`.
2. `state_merger` consumes `processed_states` and stores merged network state in Redis.
3. `work_dispatcher` reads network state, tracks nodes in Redis, sends work to `node_analysis`, and consumes `node_analysis_results`.
4. `node_analyzer` consumes node-analysis work, loads configured models/scalers, and publishes results.
5. `network_state_visualizer` reads the node registry from Redis and prints it to the terminal.
This describes the implemented connections, not a validated deployment order or a complete ingestion pipeline.
## Prerequisites and setup status
The nested package at `graph_based_intrusion_detection/` declares dependencies including Keras, TensorFlow, Kafka Python, Redis, NetworkX, NumPy, pandas, SciPy, scikit-learn, tqdm, and python-dotenv. Its package metadata identifies Python 3.11.
A standard package installation cannot be documented as reproducible until the missing nested README referenced by `pyproject.toml` is resolved. After package dependencies and metadata have been made installable, run the worker modules from `graph_based_intrusion_detection/` as shown below. No dependency lockfile is provided.
Before starting `node_analyzer`, make the configured model and scaler paths in `src/graph_based_intrusion_detection/utils/config.py` valid for the runtime. Set `LOG_FILE_PATH` and `LOG_LEVEL` before starting workers; for example: `export LOG_FILE_PATH=/tmp/network-event-detection.log` and `export LOG_LEVEL=INFO`. No environment-based broker or Redis configuration is implemented.
## Local infrastructure
From the nested package directory, start the provided local Kafka/Redis dependencies:
```bash
cd graph_based_intrusion_detection/deployment/kafka
docker compose up
```
## Integrate with your tools
This starts ZooKeeper, Kafka, and Redis and publishes Kafka on host port `9092` and Redis on host port `6379`. It is local development infrastructure only; the Compose file has no authentication, persistent-volume, image-pinning, or application-worker service configuration. Keep Kafka, Redis, and every message producer isolated to a trusted network: workers unpickle message content and must never consume messages from untrusted publishers.
- [ ] [Set up project integrations](https://gitlab.com/blankinator/distributed-network-event-detection-system/-/settings/integrations)
## Worker commands
## Collaborate with your team
After dependencies are installed, models are configured, and Kafka/Redis are running locally, each worker has a direct Python module entry point. Run these from `graph_based_intrusion_detection/`; an optional trailing worker ID is accepted.
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
```bash
python -m graph_based_intrusion_detection.realtime_event_detection.packet_processor [worker-id]
python -m graph_based_intrusion_detection.realtime_event_detection.state_merger [worker-id]
python -m graph_based_intrusion_detection.realtime_event_detection.work_dispatcher [worker-id]
python -m graph_based_intrusion_detection.realtime_event_detection.node_analyzer [worker-id]
python -m graph_based_intrusion_detection.realtime_event_detection.network_state_visualizer [worker-id]
```
## Test and Deploy
These are long-running workers. The repository does not establish a safe startup order, supervision model, shutdown procedure, health check, packet producer, or end-to-end validation command.
Use the built-in continuous integration in GitLab.
## Development and testing
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
No tests or test runner are present. The notebooks under `notebooks/` are exploratory artifacts rather than a documented operational workflow. There are no lint, format, build, or deployment scripts in the package metadata.
***
## Repository layout
# Editing this README
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
## Suggestions for a good README
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
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- `graph_based_intrusion_detection/src/graph_based_intrusion_detection/` — package source
- `realtime_event_detection/` — Kafka/Redis workers
- `packet_processing/`, `graph_processing/`, `analysis/` — graph construction and model analysis
- `utils/config.py` and `utils/constants.py` — hard-coded model paths, topics, ports, and runtime constants
- `graph_based_intrusion_detection/deployment/kafka/docker-compose.yml` — local ZooKeeper, Kafka, and Redis stack
- `graph_based_intrusion_detection/resources/models/` — checked-in model/scaler artifacts (not the paths currently configured for node analysis)
- `graph_based_intrusion_detection/notebooks/` — exploratory notebooks
- `infosheet.md` — capture/device notes, not operating documentation