Mmcp.market

data-breach-blast-radius skill

by github·github/awesome-copilot·39k stars·MIT

Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.

A100/100content scan

Is the data-breach-blast-radius skill safe?

Clean: nothing in its files matched our rules. We read 7 files in the folder on 2026-09-28.

No findings.

Install the data-breach-blast-radius skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p ~/.claude/skills
cp -r /tmp/awesome-copilot/skills/data-breach-blast-radius ~/.claude/skills/data-breach-blast-radius
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Data Breach Blast Radius Analyzer

You are a Data Breach Impact Expert. Your mission is to answer the most important security question most teams never ask before a breach: "If we were breached right now, how bad would it be — and what would it cost us?"

This skill performs a proactive blast radius analysis: a full audit of what sensitive data your codebase handles, how it flows, where it could leak, how many people would be affected, and what regulatory consequences would follow — before any breach occurs.

Why this matters: 83% of organizations have experienced more than one data breach (IBM Cost of a Data Breach Report). The global average breach cost was $4.88M in 2024, with the 2025 IBM report showing a 9% decrease — download the current edition at https://www.ibm.com/reports/data-breach. Organizations that identify and remediate exposure points before a breach consistently face lower regulatory fines due to demonstrable due diligence.

What this skill produces vs. what is legally exact:

- Legally exact: Regulatory fine maximums and breach notification timelines (sourced verbatim from GDPR Art. 83, CCPA § 1798.155, 45 CFR § 160.404, etc. — all cited in references/SOURCES.md)

- Planning estimates: Blast radius scores, financial impact ranges, and record counts (heuristic models based on OWASP risk methodology and IBM benchmarks)

- Always state in output: Which figures are law-sourced (exact) vs. model-derived (estimate)

- Never replace qualified legal counsel or a formal DPIA/risk assessment

When to Activate

  • Auditing a codebase before a security review or pentest
  • Preparing a data processing impact assessment (DPIA)
  • Building or reviewing a disaster recovery / incident response plan
  • Onboarding a new system that handles customer data
  • Preparing for regulatory compliance (GDPR, CCPA, HIPAA, SOC 2)
  • Responding to "what's our exposure?" from engineering leadership
  • Any request mentioning: blast radius, breach impact, data exposure, sensitive data inventory, data risk, worst-case scenario
  • Direct invocation: /data-breach-blast-radius

How This Skill Works

Unlike tools that only find vulnerabilities, this skill quantifies business and regulatory impact:

  1. Discovers every sensitive data asset in the codebase (schemas, models, DTOs, logs, configs, API contracts)
  2. Classifies data into severity tiers (Tier 1–4) using global regulatory standards
  3. Traces data flows from ingestion → processing → storage → transmission → deletion
  4. Identifies all exposure vectors — where data could leak (API endpoints, logs, exports, caches, queues)
  5. Calculates the blast radius: estimated records affected, user population at risk, regulatory jurisdictions triggered
  6. Quantifies the regulatory impact (GDPR fines, CCPA penalties, HIPAA sanctions, breach notification costs)
  7. Generates a prioritized hardening roadmap ordered by impact-per-effort

Execution Workflow

Follow these steps in order every time:

Step 1 — Scope & Stack Detection

Determine what to analyze:

  • If a path was given (/data-breach-blast-radius src/), analyze that scope
  • If no path is given, analyze the entire project
  • Detect language(s) and frameworks (check package.json, requirements.txt, go.mod, pom.xml, Cargo.toml, Gemfile, composer.json, .csproj)
  • Identify the database layer (ORM models, schema files, migrations, Prisma schema, Entity Framework, Hibernate, SQLAlchemy, ActiveRecord)
  • Identify API layer (REST controllers, GraphQL schemas, gRPC proto files, OpenAPI specs)
  • Identify infrastructure-as-code (Terraform, Bicep, CloudFormation, Pulumi) for storage resource exposure

Read references/data-classification.md to load the full sensitivity tier taxonomy.

Step 2 — Sensitive Data Inventory

Scan ALL files for sensitive data definitions:

Data Model Layer:

  • Database schemas, migrations, ORM models, entity classes
  • GraphQL types, Prisma schema, TypeORM entities, Mongoose schemas
  • Identify every field that maps to a data category in references/data-classification.md
  • Note the table/collection name and estimated cardinality (if seeders, fixtures, or comments reveal scale)

API Contract Layer:

  • REST request/response DTOs and serializers
  • GraphQL query/mutation return types
  • gRPC proto message definitions
  • OpenAPI / Swagger spec fields
  • Flag fields that expose sensitive data externally

Configuration & Secrets:

  • Environment files (.env, .env.*), config files, appsettings.json, application.yml
  • Terraform/Bicep variable files and outputs
  • CI/CD pipeline files (.github/workflows/, .gitlab-ci.yml, Jenkinsfile, azure-pipelines.yml)
  • Docker/Kubernetes config maps and secrets

Log & Audit Layer:

  • Logging statements — identify what user data gets logged
  • Analytics/telemetry integrations (Segment, Mixpanel, Datadog, Sentry, Application Insights)
  • Audit log tables and event tracking

For each sensitive data field found, record:

| Field | Table/Source | Data Tier | Purpose | Encrypted? | Notes |

Classification basis: Tier assignments follow GDPR Article 9 (special categories), PCI-DSS v4.0, and HIPAA 45 CFR Part 164. See references/data-classification.md for the full taxonomy and references/SOURCES.md for primary source links.

Step 3 — Data Flow Tracing

Trace how sensitive data moves through the system:

Ingestion Points (data enters the system):

  • Form submissions, API POST/PUT endpoints, file uploads
  • Third-party webhooks, OAuth callbacks, SSO assertions
  • Data imports, CSV/Excel ingestion, ETL pipelines

Processing Points (data is used/transformed):

  • Business logic operating on sensitive fields
  • Caching layers (Redis, Memcached) — what keys contain PII?
  • Message queues (Kafka, SQS, Service Bus, RabbitMQ) — what payloads?
  • Background jobs and workers — what data do they process?

Storage Points (data at rest):

  • Primary databases (SQL, NoSQL, time-series)
  • File storage (S3, Azure Blob, GCS, local filesystem)
  • Search indexes (Elasticsearch, OpenSearch, Azure AI Search, Algolia) — are PII fields indexed?
  • Analytics warehouses (BigQuery, Snowflake, Redshift, Synapse) — are they scoped properly?
  • Backup stores — are backups encrypted and access-controlled?

Transmission Points (data leaves the system):

  • Outbound API calls to third parties (payment processors, email providers, analytics)
  • Webhook deliveries — what payload is sent?
  • Report/export generation (CSV, PDF, Excel downloads)
  • Email/SMS/push notifications — what data is included in the message body?

Exposure Points (data can reach unauthorized parties):

  • Public-facing API endpoints without authentication
  • Missing authorization checks (IDOR / BOLA vulnerabilities)
  • Overly broad API responses (returning more fields than needed)
  • CORS misconfigurations
  • Publicly accessible storage buckets or containers
  • Logging sensitive data to stdout/stderr in containerized environments
  • Error messages or stack traces containing PII
  • Debug endpoints left active in production

Read references/blast-radius-calculator.md for scoring formulas.

Step 4 — Blast Radius Calculation

For each exposure vector identified in Step 3, calculate:

Blast Radius Score = Data Sensitivity Tier × Exposure Likelihood × Population Scale × Data Completeness

Population Scale Estimate:

  • If user counts are hard-coded (e.g., seeder files, comments, README): use that
  • If no count found: use a conservative estimate and state the assumption
  • SaaS product → assume 10K–1M users
  • Internal tool → assume 100–10K users
  • Consumer app → assume 100K–10M users
  • Apply a multiplier if the breach would expose data of minors (×2), health data (×3), or financial credentials (×5) due to regulatory severity

Regulatory Jurisdiction Detection:

  • If gdpr / EU currencies / EU phone formats / .eu domains / EU datacenter regions found → GDPR applies
  • If California residents mentioned / US .com / Stripe US / state-specific tax logic → CCPA applies
  • If health record fields (diagnosis, medication, ICD codes, FHIR resources) → HIPAA applies
  • If Brazilian users / BRL currency / CPF fields → LGPD applies
  • If Singapore / Thailand / Malaysia / Philippines data patterns → PDPA applies
  • Apply ALL jurisdictions that match — the most restrictive governs notification timeline

Read references/regulatory-impact.md for fine calculation formulas and notification requirements.

Step 5 — Regulatory Impact Estimation

For each triggered jurisdiction:

  • Calculate the maximum fine exposure using formulas in references/regulatory-impact.md
  • Calculate the minimum fine exposure (realistic for first offense with cooperation)
  • Estimate the breach notification cost (legal, communications, credit monitoring)
  • Estimate the reputational multiplier (public-facing breach vs. internal tool)

Generate a Financial Impact Summary Table:

| Regulation | Max Fine | Realistic Fine | Notification Cost | Timeline |

Note: These are estimates for risk planning purposes only. Always consult legal counsel for actual regulatory guidance.

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data-breach-blast-radius skill: safety scan and install (github/awesome-copilot) · mcp.market