🎯

risk-register

🎯Skill

from zbruhnke/claude-code-starter

VibeIndex|
What it does

Systematically documents and assesses risks for sensitive changes, providing a structured approach to identifying, mitigating, and monitoring potential issues during software modifications.

risk-register

Installation

Install skill:
npx skills add https://github.com/zbruhnke/claude-code-starter --skill risk-register
2
Last UpdatedJan 15, 2026

Skill Details

SKILL.md

Document risks for changes touching auth, data, or migrations. Lists top risks, how to test/monitor them, and rollback strategy.

Overview

# Risk Register

For changes that touch sensitive areas (authentication, data, migrations, infrastructure), document the risks explicitly. This is what senior developers do naturally - making it explicit ensures nothing is overlooked.

When to Use

Use this skill when your change involves:

  • Authentication/Authorization - Login, sessions, permissions, tokens
  • User Data - PII, passwords, payment info, user content
  • Data Migrations - Schema changes, data transformations, backfills
  • External Integrations - Third-party APIs, webhooks, OAuth
  • Infrastructure - Deployment, scaling, configuration changes
  • Breaking Changes - API changes, behavioral changes, deprecations

Quick Start

```

/risk-register

```

Or specify the change:

```

/risk-register "Adding password reset functionality"

```

The Risk Register Template

For each risky change, complete this register:

```markdown

# Risk Register: [Feature/Change Name]

Summary

Brief description of what's changing and why it's sensitive.

Top 3 Risks

Risk 1: [Name]

Likelihood: Low / Medium / High

Impact: Low / Medium / High / Critical

Description:

What could go wrong?

Mitigation:

How are we preventing this?

Detection:

How would we know if this happened?

Response:

What do we do if it happens?

---

Risk 2: [Name]

...

Risk 3: [Name]

...

Testing Strategy

Pre-deployment

  • [ ] Unit tests cover the change
  • [ ] Integration tests for critical paths
  • [ ] Manual testing of edge cases
  • [ ] Security review completed

Post-deployment

  • [ ] Smoke test in production
  • [ ] Monitor error rates
  • [ ] Watch for anomalies in [specific metrics]
  • [ ] Verify [specific functionality] works

Monitoring & Alerting

What should we watch after deployment?

| Metric | Normal Range | Alert Threshold | Response |

|--------|--------------|-----------------|----------|

| Login failure rate | < 5% | > 10% | Check auth service |

| API error rate | < 1% | > 5% | Investigate errors |

| ... | ... | ... | ... |

Rollback Strategy

Can we rollback?

Yes / Partial / No (explain why)

Rollback steps

  1. [Step 1]
  2. [Step 2]
  3. [Step 3]

Rollback time estimate

[X minutes/hours]

Data implications

What happens to data created after deployment if we rollback?

Approval

  • [ ] Engineer reviewed risks
  • [ ] Security reviewed (if auth/data)
  • [ ] Stakeholder aware of risks

```

Risk Categories

Authentication Risks

| Risk | Impact | Common Mitigations |

|------|--------|-------------------|

| Session hijacking | Critical | Secure cookies, HTTPS, token rotation |

| Credential stuffing | High | Rate limiting, MFA, breach detection |

| Token leakage | Critical | Short expiry, secure storage, no logging |

| Privilege escalation | Critical | Strict authz checks, principle of least privilege |

| Account takeover | Critical | Email verification, suspicious activity alerts |

Data Risks

| Risk | Impact | Common Mitigations |

|------|--------|-------------------|

| Data loss | Critical | Backups, soft deletes, transaction safety |

| Data corruption | Critical | Validation, constraints, idempotency |

| Data leakage | Critical | Access controls, encryption, audit logs |

| Privacy violation | High | PII handling, consent, data minimization |

| Compliance breach | High | Audit trails, retention policies |

Migration Risks

| Risk | Impact | Common Mitigations |

|------|--------|-------------------|

| Failed migration | High | Dry runs, backups, reversible migrations |

| Data inconsistency | High | Validation checks, reconciliation |

| Downtime | Medium | Rolling deploys, feature flags |

| Performance degradation | Medium | Index analysis, query optimization |

Example Risk Register

```markdown

# Risk Register: Password Reset Feature

Summary

Adding password reset via email. Touches auth system, sends emails with tokens,

allows password changes without current password.

Top 3 Risks

Risk 1: Token Theft/Replay

Likelihood: Medium

Impact: Critical

Description:

Reset tokens could be intercepted or reused to take over accounts.

Mitigation:

  • Tokens expire in 1 hour
  • Single use (invalidated after use)
  • Tokens are cryptographically random (32 bytes)
  • HTTPS only

Detection:

  • Alert on multiple reset attempts for same user
  • Log all password resets with IP

Response:

  • Invalidate all tokens for affected user
  • Force password change
  • Notify user of suspicious activity

---

Risk 2: Email Enumeration

Likelihood: High

Impact: Medium

Description:

Attackers could use the reset form to discover which emails have accounts.

Mitigation:

  • Same response for valid/invalid emails
  • Rate limiting on reset endpoint
  • CAPTCHA after 3 attempts

Detection:

  • Monitor for high volume of reset requests
  • Alert on requests from same IP for many emails

Response:

  • Block IP temporarily
  • Enable additional rate limiting

---

Risk 3: Token Logged/Exposed

Likelihood: Low

Impact: Critical

Description:

Reset token appears in logs, error messages, or URLs shared externally.

Mitigation:

  • Token in POST body, not URL
  • Logging excludes token field
  • Error messages are generic

Detection:

  • Grep logs for token patterns
  • Review error handling

Response:

  • Purge affected logs
  • Rotate any exposed tokens
  • Notify affected users

Testing Strategy

Pre-deployment

  • [x] Unit tests for token generation, validation, expiry
  • [x] Integration test for full reset flow
  • [x] Test expired token rejection
  • [x] Test reused token rejection
  • [x] Security review of token handling

Post-deployment

  • [ ] Smoke test: Complete reset flow in production
  • [ ] Monitor email delivery rate
  • [ ] Watch for spike in reset requests

Monitoring & Alerting

| Metric | Normal | Alert | Response |

|--------|--------|-------|----------|

| Reset requests/hour | < 100 | > 500 | Check for abuse |

| Reset completion rate | > 80% | < 50% | Check email delivery |

| Failed reset attempts | < 10% | > 30% | Check token generation |

Rollback Strategy

Can we rollback?

Yes - feature flag controls access to reset endpoint.

Rollback steps

  1. Disable PASSWORD_RESET_ENABLED feature flag
  2. Invalidate all outstanding reset tokens
  3. Communicate to support team

Rollback time estimate

~5 minutes (feature flag toggle)

Data implications

Outstanding reset tokens will be invalidated. Users mid-reset will need to retry.

```

Integration with Wiggum

When wiggum detects changes to auth, data, or migrations, it should prompt:

```

This change touches [auth/data/migrations].

Should we create a risk register? (y/n)

```

If yes, use this skill to document risks before proceeding.

Remember

  • Be specific - "data loss" is too vague; "orphaned records if parent deleted" is actionable
  • Be honest - If you can't roll back, say so
  • Think like an attacker - What would you try if you wanted to break this?
  • Think like ops - How would you know something is wrong at 3am?

The goal isn't to prevent all risks - it's to know what the risks are and have a plan.