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Database security

Skill ahtishamshahzad/agent_dev_flow/.ai/skills/security/database-security

Tool-neutral AI Engineering System: 174 reusable skills (installable as Claude Code plugins) for planning and building software with AI agents. Classify → plan → approve → build under quality gates. Works with Claude Code, Codex, Cursor, Windsurf, Copilot & Antigravity. Canonical in .ai/.

Install
npx -y skills add ahtishamshahzad/agent_dev_flow --skill database-security

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Use to review database security from an audit/threat lens — least-privilege access, network exposure, injection surface, encryption of sensitive data, tenant isolation depth, and PII handling — verifying the data-layer hardening holds. The security-review lens; the database pack owns the build-side design.

SKILL.md

5.9 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Database Security (Security Review Lens)

Purpose

Verify the data store's security posture actually holds against attack: least-privilege access, no network exposure, an injection-free data layer, encryption of sensitive data, real tenant isolation, and disciplined PII handling. The build-side design is ../../database/database-security; this security-pack skill is the review/audit lens on it, feeding ../../security-review.

When to Use

  • Auditing database security, in ../../security-review or threat-modeling data-disclosure threats.
  • Not for designing the data-layer hardening (../../database/database-security) — this verifies it.

Inputs

  • The database security design/implementation (../../database/database-security).
  • Data-sensitivity map, tenancy model, deployment topology.

Discovery Questions

  • What privileges does the app's runtime account actually hold — CRUD-only, or DDL/superuser it doesn't need?
  • Is the database network-reachable from anywhere beyond the app (public listener, exposed port)?
  • Is the data layer parameterized-only, or are there raw/string-built queries (incl. Mongo operator injection)?
  • What sensitive data exists, is it encrypted appropriately, and does account deletion truly remove PII?

Responsibilities

  • Least privilege: confirm the runtime account is CRUD-scoped (no DDL/superuser); migrations use a separate account; human/analytics access is limited and audited (../../database/database-security).
  • Network exposure: confirm private-network-only, TLS-enforced, no public listener — an internet-reachable database is a critical finding.
  • Injection surface: audit for parameterized-only access; flag string-built SQL and unvalidated object/operator injection in NoSQL (../../backend/backend-validation blocks {$gt:''}-shaped input); overlaps with api-security.
  • Encryption: sensitive data encrypted at rest, TLS in transit, and application-level field encryption for the truly sensitive (tokens, stored user secrets) with key management (secrets-audit).
  • Tenant isolation depth: confirm scoped queries are enforced (authorization-security, ../../backend/ownership-authorization) and evaluate whether the risk profile warrants DB-enforced isolation (row-level security / per-tenant schemas).
  • PII discipline: no PII in logs/backups/dev seeds (privacy-review, ../../testing/test-data-management); retention + tested deletion paths exist.
  • Route findings to fixes + regression tests (security-regression-testing).

Required Workflow

  1. Review account privileges (runtime, migration, human, analytics).
  2. Verify network isolation + TLS.
  3. Audit the data layer for injection (SQL + NoSQL operator).
  4. Verify encryption per data class + key management.
  5. Assess tenant-isolation depth + PII handling/deletion.
  6. Record findings; route to fixes + regression tests.

Decision Rules

  • Public-reachable database or app-account-with-DDL/superuser = confirmed high-severity findings.
  • Any string-built query is an injection finding regardless of "trusted" input.
  • Field-level encryption is for data whose leak survives a full dump — verify it's applied where the sensitivity demands, not encrypt-everything-into-mush.
  • Real production data in any lower environment is a finding (privacy-review).

Rules

  • Never print secrets or real data during the audit — location + severity only.
  • Findings separated Confirmed vs Potential; never declare "secure" (../../security-review).
  • Each finding maps to a fix + regression test; delegate build-side design to ../../database/database-security.

Anti-Patterns

  • Passing a database on a public IP.
  • App connecting as owner/superuser "temporarily forever."
  • The one legacy raw query nobody re-checks for injection.
  • "Encrypted at rest" (disk) presented as answering field-sensitivity.
  • PII in logs, backups, and dev seeds; deletion that flips a boolean.

Validation Checklist

  • Least-privilege accounts verified (runtime/migration/human/analytics).
  • Network private + TLS; no public listener.
  • Parameterized-only data layer (SQL + NoSQL) verified.
  • Encryption per class + key management confirmed.
  • Tenant-isolation depth assessed; PII handling/deletion verified.
  • Findings → fixes → regression tests.

Definition of Done

A recorded database security audit — access privileges, network exposure, injection surface, encryption, tenant isolation, PII handling — with Confirmed/Potential findings routed to fixes and regression tests, delegating build-side design to the database pack, and no "secure" claim.

Related Skills

../../database/database-security, authorization-security, ../../backend/ownership-authorization, api-security, secrets-audit, privacy-review, ../../testing/test-data-management, security-regression-testing, ../../security-review, threat-modeling.

Related Knowledge

../../../knowledge/ (data classes, tenancy model, topology).

Related References

../../../references/security/ (database review checklists, when populated).

Context Loading Guidance

  • Requires: the database security design/impl, sensitivity map, topology.
  • Does not require: re-designing the hardening (delegate), app feature code.
  • May load: ../../database/database-security, authorization-security.
  • Stop when: findings + routed fixes/tests are recorded.

Token Efficiency Guidance

The finding table (area → issue → severity → fix) is the artifact; never echo real data or secrets. Delegate build design rather than restating it.

What ships with it

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Just SKILL.md. No reference files, no scripts.

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