Files
blackroad-operating-system/services/codex/entries/015-quantitative-information-flow.md
Alexa Louise 9644737ba7 feat: Add domain architecture and extract core services from Prism Console
## Domain Architecture
- Complete domain-to-service mapping for 16 verified domains
- Subdomain architecture for blackroad.systems and blackroad.io
- GitHub organization mapping (BlackRoad-OS repos)
- Railway service-to-domain configuration
- DNS configuration templates for Cloudflare

## Extracted Services

### AIops Service (services/aiops/)
- Canary analysis for deployment validation
- Config drift detection
- Event correlation engine
- Auto-remediation with runbook mapping
- SLO budget management

### Analytics Service (services/analytics/)
- Rule-based anomaly detection with safe expression evaluation
- Cohort analysis with multi-metric aggregation
- Decision engine with credit budget constraints
- Narrative report generation

### Codex Governance (services/codex/)
- 82+ governance principles (entries)
- Codex Pantheon with 48+ agent archetypes
- Manifesto defining ethical framework

## Integration Points
- AIops → infra.blackroad.systems (blackroad-os-infra)
- Analytics → core.blackroad.systems (blackroad-os-core)
- Codex → operator.blackroad.systems (blackroad-os-operator)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-29 13:39:08 -06:00

1.2 KiB

Codex 15 — Quantitative Information Flow — Measure the Leak

Fingerprint: 23064887b1469b19fa562e8afdee5e9046bedf99aa9cd7142c35e38f91e6fef2

Aim

Keep secrets secure by quantifying leakage instead of relying on intuition.

Core

  • Define information leakage through a channel (C) as mutual information (\mathcal{L} = I(S; O) = H(S) - H(S \mid O)).
  • Enforce quantitative noninterference so that (\mathcal{L} \leq \epsilon) for each release.
  • Use hyperproperty reasoning (2-safety) to compare pairs of runs against policy constraints.

Runbook

  1. Annotate confidential sources and observable sinks; instrument systems to estimate (I(S; O)).
  2. Allocate an (\epsilon) leakage budget per module and deny releases that exceed the cap.
  3. Apply differential privacy, padding, or channel randomization to reduce (\mathcal{L}).

Telemetry

  • Bits leaked per query or release and cumulative leakage versus budget.
  • Effectiveness of mitigation techniques over time.
  • Alerts raised when leakage approaches thresholds.

Failsafes

  • Trigger an emergency kill switch when leakage exceeds the budget.
  • Capture forensic snapshots and patch the offending module before re-enabling output.

Tagline: Quantify every whisper.