profiles
Supabase Security Tool Profiles
Profiles help you choose tools and approaches without guesswork. They focus on verified facts, tradeoffs, and who each option fits best — then link you to comparisons and templates to take action.
What a tool profile includes
- Verified factual data (with sources)
- Feature and tradeoff summary
- Pros/cons
- Who it’s best for
- Links to comparisons and curated collections when available
Browse Supabase security tool profiles
| Tool | Type | Pricing | URL |
|---|---|---|---|
| Mockly | security-scanner | $20/scan (Snapshot) or $29/mo (Subscription, 2 scans/mo on 1 project) | /profiles/mockly |
| SQL Audit Checklist | checklist | Free (time to run and interpret results). | /profiles/sql-audit-checklist |
| Supabase Dashboard Review | manual-workflow | Varies (engineering time). | /profiles/supabase-dashboard-review |
Quick shortlist (start here)
If you’re unsure where to start, pick one option that matches your constraint and run it this week:
- Mockly →
/profiles/mockly— A Supabase security scanner that highlights public exposure risks (tables, storage, RPC) and drafts backend-only fixes you can ship confidently. - SQL Audit Checklist →
/profiles/sql-audit-checklist— A repeatable set of SQL queries you run to find exposure signals (public grants, missing RLS, public RPC) and confirm your project is backend-only. - Supabase Dashboard Review →
/profiles/supabase-dashboard-review— A manual review workflow using the Supabase Dashboard (SQL Editor, policies, storage settings, and logs) to spot exposure risks before they ship.
How to choose a tool for Supabase security
- Pick the option that matches your constraint (time vs depth vs repeatability).
- Prefer solutions that help you verify fixes (not just detect issues).
- Ensure the approach covers tables, storage, and RPC (common blind spots).
- Add a repeatable process after the first win.
A practical evaluation rubric (don’t choose by features alone)
| Criterion | What good looks like | Why it matters |
|---|---|---|
| Time-to-signal | You can run it and get meaningful findings in < 1 hour | You’ll actually use it before launch |
| Actionability | It suggests fixes and verification steps | Findings without fixes stall remediation |
| Repeatability | Easy to re-run after migrations in every env | Drift is a common source of leaks |
| Surface coverage | Covers tables + Storage + RPC | Teams fix tables and forget Storage/RPC |
| Verification | Helps you prove direct client access is blocked | Prevents false confidence |
Common evaluation criteria
- Time-to-signal (how fast you get a meaningful report)
- Repeatability across environments
- Actionable fixes and verification steps
- Learning value for your team
- Coverage of non-table surfaces (Storage + RPC)
How to combine tools for best results (hybrid workflow)
Most teams get the best outcome by combining fast signal with deeper verification.
A strong hybrid workflow is:
- Scan for fast signal (find public tables/buckets/RPC).
- Use a checklist/manual review to validate and understand edge cases.
- Apply templates/conversions to lock down access and move to backend-only paths.
- Re-run the scan/checklist after migrations to catch drift early.
How to verify a tool’s output is actionable
- It points to a concrete resource (table/bucket/function), not a vague concept.
- It tells you what to change and how to verify the change worked.
- It reduces ambiguity: you can reproduce the risky behavior before fixing it.
- It helps you prevent drift: re-run after migrations and compare results.
What to do after you choose a tool (so it doesn’t become shelfware)
A tool only helps if it becomes part of your workflow.
- Schedule a recurring run (after migrations and before major releases).
- Pick one “anchor” direct access test per surface (tables/Storage/RPC) and keep it as a regression step.
- Standardize how you record fixes: what changed, how you verified, and how you’ll prevent drift.
- After your first win, expand coverage to the next surface instead of adding complexity to the same one.
Common mistakes when choosing a tool
- Picking the “most powerful” tool but never running it (no repeatability).
- Choosing based on pricing alone and ignoring operational fit (time, expertise).
- Using a tool to detect issues but not adopting verification and drift guards.
- Fixing tables but ignoring Storage and RPC surfaces.
What counts as a verified fact in profiles
Profiles are easy to get wrong, so this system treats factual claims as data with sources.
- If a claim can change (pricing, product capabilities), store it as a verified fact with a source reference.
- If you can’t cite a source, describe it as a tradeoff or workflow characteristic instead of a hard fact.
- If something changes, treat the sources as the truth and re-check critical behaviors in your environment.
This keeps profiles useful at scale: readers can trust that facts are traceable and opinions are labeled as tradeoffs.
How to read a profile quickly (and decide)
If you’re scanning profiles, don’t start with features. Start with fit:
- Read verified facts first (what is definitely true, with sources).
- Read tradeoffs next (where it can go wrong in real workflows).
- Pick one concrete surface and try the workflow once this week (tables, Storage, or RPC).
- Only then compare it to an alternative using a comparison page.
This keeps you from choosing based on checkboxes and helps you pick the option you’ll actually run again after migrations.
If a profile feels incomplete
Some tools change quickly, and not every nuance fits into a single page.
- Start from verified facts and sources.
- Treat tradeoffs as hypotheses, then validate by running the workflow once on one real surface.
- If your decision depends on a single capability, test it directly before committing.
The goal of a profile is to help you make a better first decision — not to replace a hands-on trial.
Next step
Open one profile, then compare it to an alternative that matches your current workflow and constraints.
FAQ
Why do profiles require verified facts?
Because profiles are easy to get wrong. Requiring factual fields with sources prevents accidental misinformation at scale.
Where should I go after reading a profile?
Use comparisons to evaluate two options side-by-side, use curation to pick a workflow that matches your constraints, and use templates/integrations to actually implement and verify fixes in your project.
What if a tool changes over time?
Treat profiles as a starting point. Check the sources linked in the verified facts section, and validate critical behavior in your own environment before you commit to a workflow.
Next step
If you want to evaluate options based on your real exposures, run a Mockly scan and start with the highest‑impact fixes.