# Project "GUARDIAN" — Implementation Complete

I have successfully transformed the GRID safety layer from a static pattern-matcher into an **Adaptive Defense System**.

## 🛡️ Core Capabilities

### 1. Unified Rule Orchestration (Foundational Hardening)
- **Source of Truth**: All safety rules (Weapons, Bio-threats, Jailbreaks) are now centralized in `safety/rules/registry.json`.
- **High Performance**: The `RuleEngine` pre-compiles regex patterns for <50ms evaluation in the pre-check pipeline.
- **Rich Metadata**: Every rule now carries Severity (Low-Critical) and Event Type (AI_BLOCK, JAILBREAK, etc.) metadata.

### 2. Adaptive Counter-Measures (The "Fencing" Mechanism)
- **Stateful Risk Scoring**: Every security violation is recorded in Redis via the `RiskScoreManager`. Users accumulate higher risk based on event severity.
- **Dynamic Decimation**: The `RateLimiter` now fetches this risk score. If a user is "poking the fences":
  - **Medium Risk**: Capacity and refill rate are halved.
  - **High Risk**: Capacity is decimated (reduced by 90%).
  - **Fail-Safe**: Trust naturally decays over time (0.1 points per hour) to allow for redemption.

### 3. The "Safety Canary" (Anti-Jailbreak & DLP)
- **Invisible Watermarking**: Responses and inputs are now cross-referenced via `safety_canary`.
- **Adaptive Injection**: Users with high risk scores (>0.2) receive responses with invisible UTF-8 "canary" tokens.
- **Immediate Detection**: If a user recycles an AI response into a prompt (common in multi-turn jailbreak attempts), the canary is detected in `pre_check.py`, and the request is blocked with `CRITICAL` severity and maximum risk score.

### 4. Forensic Loop Closure (Real-Time Shielding)
- **Dynamic Rule Injection**: The `/observe/rules/dynamic` endpoint allows Incident Response teams to push new shielding rules instantly via Redis.
- **Global Sync**: Every serving instance polls for dynamic rules every 30 seconds, allowing for global protection within seconds of discovery.

---

## 📂 Key Files Modified
- `safety/rules/engine.py`: The heart of Project GUARDIAN.
- `safety/rules/registry.json`: Centralized safety policy.
- `safety/observability/risk_score.py`: User trust tracking.
- `safety/observability/canary.py`: Adverse feedback detection.
- `safety/api/rate_limiter.py`: Adaptive hardening integration.
- `safety/detectors/pre_check.py`: Integrated multi-layer detector.
- `safety/workers/consumer.py`: Response watermarking loop.

## 🚀 Verification
You can verify the system by:
1. Connecting to the `WS /observe/stream` to watch live events.
2. Injecting a dynamic rule via `curl -X POST /observe/rules/dynamic`.
3. Observed the rate limit headers (`X-Risk-Score`) tightening after repeated violations.
