4224b7d283
97% complete
2026-03-02 17:29:48 -05:00
f9b5a614d3
feat: did a couple things idk
2026-02-28 14:08:36 -05:00
d471de31fd
chore: lint and format all Phase 3 training code
2026-02-28 09:23:12 -05:00
cf92b157f3
feat(ai-threat-detection): complete Phase 2 — ML ensemble, inference, training pipeline
...
Add ONNX inference engine with 3-model ensemble (autoencoder, random forest,
isolation forest), ONNX export utilities, MLflow experiment tracking, and
classifier training scripts. Extend pipeline with hybrid ML/rules detection
mode, ensemble score fusion and blending, and full test coverage for all
new components. Fix Python 3 SyntaxError in parsers.py (except clause).
2026-02-28 04:40:33 -05:00
9397b12a4a
add learn folder, move hidden files, update root readme, add learn folder, add clang tidy, and format
2026-02-26 00:38:55 -05:00
47432c8ce4
issue 77 pt2 ruff
2026-02-18 19:47:47 -05:00
7f35fbd839
feat: complete Phase 1 — rule-based detection pipeline, API, Docker E2E
...
Phase 1 delivers end-to-end threat detection from nginx log ingestion
through rule-based scoring to REST API and WebSocket alerts.
- API layer: /threats, /stats, /models/status, /ws/alerts, /health, /ready
- Alert dispatcher with Redis pub/sub + PostgreSQL persistence
- Typer CLI: vigil serve, config, health
- Integration tests (tailer -> pipeline -> DB round-trip)
- Docker E2E verified: dev.compose.yml stack with all services healthy
- Linting clean: ruff, mypy strict (0 issues), pylint 10/10
- 75 tests passing across 8 test modules
2026-02-18 13:02:10 -05:00
3fd9f77335
checkpoint - phase 13 complete
2026-02-14 02:24:37 -05:00
CarterPerez-dev