dc6567ae25
chore complete + add pre commit chnages
2026-04-19 18:54:08 -04:00
d277d50a93
feat: sbom generator & vulnerability matcher + docstrings across 6 projects
...
Add bomber CLI tool (Go) — scans dependencies across Go/Node/Python
ecosystems, generates SPDX 2.3 and CycloneDX 1.5 SBOMs, and matches
against OSV/NVD vulnerability databases with policy engine for CI/CD.
Add file-level docstrings to ai-threat-detection, firewall-rule-engine,
hash-cracker, linux-cis-hardening-auditor, binary-analysis-tool, and
credential-enumeration.
2026-04-08 23:53:40 -04:00
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
37738b4d0b
test: add end-to-end training integration test
2026-02-28 07:13:30 -05:00
60564437de
feat(cli): update train command to use orchestrator pipeline
2026-02-28 06:52:14 -05:00
a26d68e8d1
feat(ml): add training orchestrator with MLflow and validation
2026-02-28 06:41:10 -05:00
24eefc5fb4
feat(ml): add synthetic attack and normal traffic generator
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Six attack generators (SQLi, XSS, traversal, Log4Shell, SSRF,
scanner) plus normal traffic, all producing 35-dim feature vectors.
2026-02-28 06:31:22 -05:00
f9f8e1ef52
feat(ml): add stratified splitting with SMOTE oversampling
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70/15/15 train/val/test split with SMOTE applied only to the
training set. Extracts X_normal_train pre-SMOTE for autoencoder.
2026-02-28 06:29:07 -05:00
ee25636437
feat(ml): add model metadata persistence with version hashing
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SHA-256 based version hashing for ONNX artifacts and async
metadata persistence that replaces previous active model entries.
2026-02-28 06:00:28 -05:00
0a9cf12212
feat(ml): add ensemble validation with PR-AUC and F1 gates
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Loads ONNX models, normalizes per-model scores, fuses them,
and computes classification metrics with configurable quality gates.
2026-02-28 05:59:36 -05:00
2475d1603f
feat(ml): add CSIC 2010 data loader with feature extraction
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Parses multi-line CSIC 2010 HTTP request files into CSICRequest
dataclasses, converts to ParsedLogEntry with synthesized defaults,
and produces 35-dim feature vectors via the existing extraction pipeline.
2026-02-28 05:39:51 -05:00
cf92b157f3
feat(ai-threat-detection): complete Phase 2 — ML ensemble, inference, training pipeline
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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
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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