Context limits
A model sees only what fits in its context. Large projects get summarized or truncated, and the risky file is often the one left out.
Prompts & Claude skills vs Hackaiz
A security prompt reads your code. Hackaiz tests your live system.
A prompt or a Claude skill asks an AI model to review text it is shown. It does not send requests to your deployed site, does not test your database access rules from outside, and does not prove that a flaw is exploitable. Hackaiz runs authorized, read-only checks on the real system, keeps evidence for every finding, prepares fixes you approve and rechecks after each change.
Asking the AI that wrote your app to secure it is like asking a spell-checker whether your front door locks.
Prompts & Claude skills vs Hackaiz
Prompt / Claude skill
What is examined
Only the files or text pasted into the conversation
Real-world test
None: the model reasons about code, it does not query your live app
Proof
An opinion that can sound confident and still be wrong
Configuration outside code
Invisible: hosting, headers, Supabase policies, exposed keys in the live bundle
Self-review bias
Same family of model judging code it may have generated
After the next change
Nothing happens until someone thinks to ask again
Fixes
Suggestions to copy and paste by hand
Hackaiz
What is examined
The deployed site, the connected repository, database rules and AI endpoints
Real-world test
Authorized read-only requests against the real system after domain proof
Proof
Each finding is tied to a captured server response or code location
Configuration outside code
Checked where they actually run
Self-review bias
Independent rule-bound checks, separate from the tool that built the app
After the next change
Rechecks when code, database or site changes
Fixes
Prepared fix, human approval, then a GitHub pull request you merge
What a prompt cannot see
The live app is not the code
Many breaches come from deployment: a public storage bucket, a missing access policy, a key shipped in the browser bundle. None of these are visible in a prompt.
Plausible is not proven
Language models can miss real flaws and invent false ones. Without a reproducible check, you cannot tell which is which.
Security decays
Every new feature can reopen a hole. A one-time prompt does not watch what changes next week.
Claude Mythos
What about Claude Mythos or another AI hacking model?
Claude Mythos is a real and very capable security model. A model, however powerful, is still a brain. Hackaiz is the framework that makes its work safe, proven and followed up.
01Restricted access
Anthropic opens its most advanced Mythos versions only to verified organizations. Most app builders cannot use them.
02A model is not a service
You still have to decide what to test, prove the site is yours, stay read-only, keep evidence, prepare the fix, get it approved and recheck after every change.
03Attackers will have it too
Anthropic itself expects these capabilities to spread, including to attackers. Your app must be rechecked whenever it changes, not once.
04Power without guardrails is a risk
An offensive model launched without limits on a production app can break or change data. Hackaiz requires domain proof, read-only checks and human approval.
Mythos is a racing engine. Hackaiz is the car, the licence, the dashboard and the inspection.
How Hackaiz uses AI
Hackaiz uses recent AI models to explain findings and prepare fixes. Verdicts rest on real responses from your system, stored as evidence. A stronger model improves the explanation, not the proof, and Hackaiz can adopt better models without changing its guardrails.
Use both
Keep your prompts and skills: they help you write cleaner code. Hackaiz is the independent check that verifies, with evidence, what is actually exposed once the app is online.
Frequently asked questions
- Can a Claude skill or a security prompt replace Hackaiz?
- No. A prompt or skill reviews the text given to an AI model. It does not test the deployed application, database access rules or keys exposed in production, and it produces no reproducible evidence. Hackaiz tests the real system with authorization and proves each finding.
- I secured my app with AI prompts. Do I still need Hackaiz?
- Yes, if the app is online with real users or data. Prompts improve code quality; Hackaiz verifies from outside what is actually reachable, with evidence, and rechecks after every change.
- Can Claude Mythos or an AI hacking model replace Hackaiz?
- No. Advanced Mythos versions are reserved for organizations verified by Anthropic, and a model is not a service: it does not prove domain ownership, enforce read-only tests, keep evidence, get fixes approved or recheck after changes. Hackaiz provides that framework. Mythos is a racing engine; Hackaiz is the car, the licence, the dashboard and the inspection.
- Does Hackaiz use AI?
- Yes. Hackaiz uses recent AI models to explain findings and prepare fixes. Verdicts rest on real responses from your system, stored as evidence, so a stronger model improves the explanation, not the proof.
- Can I use both?
- Yes. Use prompts and skills while building, and Hackaiz to verify the deployed result and keep checking it as it changes.