Nim package names cannot contain hyphens, so `nimble install -y nph`
in the lint workflow aborted on `validatePackageName` before nph could
be installed, causing the Nim lint job to fail with `nph: command not
found`. Renaming the manifest to match the binary name resolves it
and lets contributors run nimble inside the project.
- New Aenebris.ML.Engine module: pure decision pipeline composing
the previously-built Loader, Inference, Calibration, and IForest
modules into a single per-request scoring path.
Engine record holds (Ensemble, Calibrator, Maybe IForest,
EngineConfig); runEngine takes a feature vector and produces
DecisionDetails (Decision, raw proba, calibrated proba, optional
IForest score). The Decision is one of DecisionHuman, DecisionBot,
or DecisionChallenge.
- Implements the escalation-gate semantics per the 2026 research
correction (over the deprecated 0.8/0.2 weighted blend):
calibrated <= humanThreshold -> DecisionHuman
calibrated >= botThreshold -> DecisionBot
otherwise (ambiguous band):
if IForest configured and ifScore >= escalation threshold
-> DecisionBot (escalation)
else if challenges enabled
-> DecisionChallenge
else
-> DecisionHuman (fallthrough)
Defaults: 0.3 / 0.7 thresholds, 0.6 IForest escalation, challenges
on by default.
- 17 tests covering: defaultEngineConfig values, decision boundaries
with NoCalibrator and no IForest (low/mid/high leaf ensembles),
ambiguous-band escalation via low-vs-high anomaly IForests,
ambiguous-band with challenges disabled (fallthrough to Human or
escalation to Bot), Platt calibrator pulling decisions across
thresholds, and DecisionDetails field correctness.
- aenebris.cabal: expose Aenebris.ML.Engine in the library stanza.
- 342 total examples passing, 0 GHC warnings on the new module.
The Wai middleware wiring (extract features -> runEngine -> route by
Decision) is the next module (ML.Middleware); Engine intentionally
stays pure / independent of HTTP machinery so it can be unit-tested
without request fixtures.
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.
CarterPerez-dev