Session 4: Build Intelligence, Security & Cloud layers (6 prototypes)

[blackboxprogramming]

Summary

Completed Session 4 build sprint across three critical layers: Intelligence (AI), Security (SEC), and Cloud (CLD). Built 6 new production-ready prototypes totaling 18 new files, advancing BlackRoad from 8 to 14 total prototypes.

Key Changes

Intelligence Layer (AI)

• prototypes/ai-failover/ - AI provider failover chain with circuit breakers

  • Routes requests through Claude → GPT → Llama with automatic cascading
  • Circuit breaker pattern prevents cascading failures
  • Health checks, latency tracking, provider scoring
  • 4 files: provider.py, circuit_breaker.py, failover_router.py, config.py

• prototypes/prompt-registry/ - Reusable, versioned prompt templates

  • 8 default templates with provider-specific overrides
  • Template versioning and inheritance

• prototypes/token-tracker/ - Per-route and per-provider token usage tracking

  • Budget alerts and cost tracking
  • Real-time usage dashboards

Security Layer (SEC)

• prototypes/webhook-verify/ - Webhook signature verification

  • Support for GitHub, Stripe, Slack, Salesforce
  • Replay attack protection
  • Request validation and logging

• prototypes/audit-log/ - Structured audit logging pipeline

  • Append-only event storage
  • Indexing for compliance queries
  • Export capabilities for audits

Cloud & Edge Layer (CLD)

• prototypes/api-gateway/ - Cloudflare Workers edge gateway
  • Rate limiting, authentication, CORS at the edge
  • Request routing and transformation
  • Response caching before reaching backend

Implementation Details

• Circuit Breaker Pattern: Tracks provider health across CLOSED → OPEN → HALF_OPEN states with configurable thresholds and recovery timeouts
• Provider Abstraction: Unified interface for Claude, OpenAI, and Llama with metrics collection (latency, cost, token usage)
• Edge-First Design: Cloudflare Workers handles auth/rate-limiting before requests reach infrastructure, reducing backend load
• Audit Everything: All system events logged immutably with structured format for compliance and debugging

Status Updates

• Updated .STATUS from SESSION_3 to SESSION_4 (2026-02-04)
• Marked 6 TODO items as complete (AI failover, prompt registry, token tracking, webhook verification, audit logging, API gateway)
• Added Session 4 summary to MEMORY.md with full implementation details
• All 6 prototypes marked as BUILT in status file

Testing

Each prototype includes:

• Configuration files with sensible defaults
• README with architecture diagrams
• Example usage patterns
• Error handling and logging

Ready for integration testing with the existing bridge infrastructure.

https://claude.ai/code/session_0136vvNAuboRaFzeaWbo547Y

In general, to fix clear‑text logging of sensitive data, you prevent direct or indirect inclusion of secrets (or objects closely tied to them) in log or status outputs. Instead, you log only non‑sensitive aggregates or metadata (e.g., counts, boolean flags) or explicitly redact sensitive parts.

For this specific case, the taint source is self._secrets and the sink is the string constructed in status_summary() and printed in main(). We should change status_summary() so it no longer embeds ', '.join(self._secrets.keys()). A simple, non‑disruptive approach is to log just the number of registered providers. This preserves useful diagnostics while avoiding exposure of the provider identifiers that CodeQL considers tainted. Concretely:

• In WebhookVerifier.status_summary, replace line 383:
  • f"║ Providers: {', '.join(self._secrets.keys()):<23}║",
• With a line reporting only the count, e.g.:
  • f"║ Providers: {len(self._secrets):<23}║",

No new imports or helper methods are needed; we only use len(self._secrets), which is already available.

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