Add BMad review epic addendums for all 6 products

Per-product surgical additions to existing epics (not cross-cutting):
- P1 route: 8pts (key redaction, SSE billing, token math, CI runner)
- P2 drift: 12pts (mTLS revocation, state lock recovery, pgmq visibility, RLS leak, entropy scrubber)
- P3 alert: 10pts (HMAC replay, claim-check, out-of-order correlation, free tier, tenant isolation)
- P4 portal: 9pts (partial scan recovery, ownership conflicts, Meilisearch rebuild, VCR freshness, free tier)
- P5 cost: 7pts (concurrent baselines, remediation RBAC, Clock interface, property tests, Redis fallback)
- P6 run: 15pts (shell AST parsing, canary suite, intervention TTL, streaming audit, crypto signatures)

Total: 61 story points across 30 new stories
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# dd0c/alert — Epic Addendum (BMad Review Findings)
**Source:** BMad Code Review (March 1, 2026)
**Approach:** Surgical additions to existing epics — no new epics created.
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## Epic 1 Addendum: Webhook Ingestion
### Story 1.6: HMAC Timestamp Freshness (Replay Prevention)
As a security-conscious operator, I want webhook payloads older than 5 minutes to be rejected, so that captured webhooks cannot be replayed to flood my ingestion pipeline.
**Acceptance Criteria:**
- Datadog: Rejects `dd-webhook-timestamp` older than 300 seconds.
- PagerDuty: Rejects payloads with missing timestamp header.
- OpsGenie: Extracts timestamp from payload body and validates freshness.
- Fresh webhooks (within 5-minute window) are accepted normally.
**Estimate:** 2 points
### Story 1.7: SQS 256KB Claim-Check Round-Trip
As a reliable ingestion pipeline, I want large alert payloads (>256KB) to round-trip through S3 claim-check without data loss, so that high-cardinality incidents are fully preserved.
**Acceptance Criteria:**
- Payloads > 256KB are compressed and stored in S3; SQS message contains S3 pointer.
- Correlation engine fetches from S3 and processes the full payload.
- S3 fetch timeout (10s) sends message to DLQ without crashing the engine.
- Engine health check returns 200 after S3 timeout recovery.
**Estimate:** 3 points
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## Epic 2 Addendum: Correlation Engine
### Story 2.6: Out-of-Order Alert Delivery
As a reliable correlation engine, I want late-arriving alerts to attach to existing incidents (not create duplicates), so that distributed monitoring delays don't fragment the incident timeline.
**Acceptance Criteria:**
- Alert arriving after window close but within 2x window attaches to existing incident.
- Alert arriving after 3x window creates a new incident.
- Attached alerts update the incident timeline with correct original timestamp.
**Estimate:** 2 points
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## Epic 5 Addendum: Slack Bot
### Story 5.6: Free Tier Enforcement (10K alerts/month)
As a PLG product, I want free tier tenants limited to 10K alerts/month with 7-day retention, so that the free tier is sustainable and upgrades are incentivized.
**Acceptance Criteria:**
- Alert at count 9,999 accepted; alert at count 10,001 returns 429 with Stripe upgrade URL.
- Counter resets on first of each month.
- Data older than 7 days purged for free tier; 90-day retention for pro tier.
**Estimate:** 2 points
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## Epic 6 Addendum: Dashboard API
### Story 6.7: Cross-Tenant Negative Isolation Tests
As a multi-tenant SaaS, I want explicit negative tests proving Tenant A cannot read Tenant B's data, so that confused deputy vulnerabilities are caught before launch.
**Acceptance Criteria:**
- Tenant A query returns zero Tenant B incidents (explicit assertion, not just "works for A").
- Cross-tenant incident access returns 404 (not 403 — don't leak existence).
- Tenant A analytics reflect only Tenant A's alert count.
**Estimate:** 1 point
---
**Total Addendum:** 10 points across 5 stories