# Security Reality Check v1 (Proposed Contribution)

**Type**: Implementation proposal (review artifact)  
**Audience**: Web4 maintainers + external red-team collaborators  
**Status**: Actionable draft  
**Date**: 2026-02-11

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## 1) Why this contribution

Web4 already has broad internal attack simulations and a strong research narrative, but multiple top-level docs still call out the same remaining gap: external adversarial validation and measurable security assurance under realistic conditions.

This proposal converts that gap into an executable work package that can be implemented incrementally and evaluated objectively.

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## 2) Goal

Create a small, repeatable **security validation pack** that ties high-priority attack hypotheses to explicit invariants and machine-checkable outcomes.

### Success criteria
- High-priority attack lanes have reproducible replay scripts.
- Each replay is evaluated against explicit Web4 invariants.
- Results produce a consistent scorecard: exploitability, detection quality, remediation status, residual risk.
- The pack can run in CI or a scheduled security pipeline.

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## 3) Scope (v1)

### In scope
1. **Invariant registry** (identity integrity, trust integrity, ATP conservation, authorization correctness, federation consistency).
2. **Replay harness** for P0 external vectors in the red-team matrix.
3. **Result scorecard** mapped to runbook severity definitions.
4. **Documentation synchronization notes** for stale path/metric drift that can create policy confusion.

### Out of scope (v1)
- Formal proofs of protocol security.
- Production cryptography redesign.
- Physical hardware compromise testing.

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## 4) Candidate implementation layout

- `review/security_reality_check_v1.md` (this plan)
- `review/security_reality_check_tasks.md` (execution checklist)
- `simulations/security_reality_check/` (new package)
  - `invariants.yaml`
  - `runner.py`
  - `scenarios/`
    - `rt01_witness_cartel.py`
    - `rt02_roi_sybil.py`
    - `rt04_trust_admin_pivot.py`
    - `rt05_replay_ordering_drift.py`
  - `reports/` (generated artifacts)

This keeps v1 localized and avoids disruptive refactors.

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## 5) Invariants (minimum set)

| Invariant ID | Description | Failure signal |
|---|---|---|
| INV-ID-01 | Identity state transitions require valid, non-replayed proofs | Unauthorized identity mutation accepted |
| INV-TRUST-01 | Trust cannot increase from invalid/insufficient witnesses | Unjustified trust inflation |
| INV-ATP-01 | ATP conservation constraints hold under attack traffic | Net ATP creation or unbounded drain bypass |
| INV-AUTH-01 | Privileged actions require valid delegation/authorization path | Out-of-policy privileged action succeeds |
| INV-FED-01 | Federation ordering/consistency checks reject replay and stale ordering | Divergent accepted state across peers |

---

## 6) Scenario lanes (P0-first)

The first four scenarios map directly to the existing external red-team matrix priorities:

1. **RT-01 Adaptive witness cartel**
2. **RT-02 ROI-positive Sybil economy**
3. **RT-04 Trust-to-admin pivot chain**
4. **RT-05 Replay + ordering drift**

Each scenario should define:
- attacker budget/capabilities,
- required starting privileges,
- explicit expected invariant outcomes,
- measurable detection telemetry.

---

## 7) Output scorecard format

Per scenario:
- `exploitability`: `confirmed | partial | not_reproduced`
- `invariants_violated`: list of invariant IDs
- `mttd_seconds`: numeric or `null`
- `mttr_seconds`: numeric or `null`
- `severity`: `critical | high | medium | low`
- `fix_status`: `open | mitigated | retest_passed`
- `residual_risk`: short rationale

Aggregate report:
- total scenarios executed,
- confirmed exploit count,
- by-severity distribution,
- unresolved critical/high findings,
- rerun/retest delta versus previous run.

---

## 8) Two-week execution plan

### Week 1
- Define `invariants.yaml` and acceptance semantics.
- Implement `runner.py` scaffolding and report schema.
- Build RT-01 and RT-02 first-pass replay scripts.

### Week 2
- Add RT-04 and RT-05 replay scripts.
- Wire scorecard output and baseline report generation.
- Run initial pass, document findings, and prioritize mitigations.

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## 9) Risks and mitigations

- **Risk**: Scenario scripts become tightly coupled to current simulation internals.  
  **Mitigation**: keep scenario interfaces narrow and versioned.

- **Risk**: Detection metrics unavailable in some paths.  
  **Mitigation**: allow `null` metrics with explicit telemetry TODOs.

- **Risk**: Confusion between synthetic replay and true external adversarial campaigns.  
  **Mitigation**: tag outputs as "internal replay validation" and map explicitly to external campaign phases.

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## 10) Expected value

- Turns security discussion from narrative claims into measurable evidence.
- Creates a bridge between existing simulation depth and external red-team execution.
- Establishes a reusable structure for regression testing of high-impact security weaknesses.

This is a high-leverage contribution because it is small enough to ship quickly, but foundational enough to improve both assurance quality and decision-making for pilot readiness.
