Ask. Reason.
Ship the fix.
A conversational security co-pilot grounded on your codebase, findings and threat model — answers cite the exact lines, propose a patch, and explain how an attacker would chain it.
Talk to your security agent.
Watch it think.
A real prompt, grounded on a real finding. The chat reasons over the code, cites the line, and writes the patch — exactly what your engineers will see in production.
How do you detect IDOR and BOLA bugs across our API?
Agents enumerate three personas (admin / member / guest) and probe every endpoint as each one. Cross-tenant reads that return 200 OK get re-verified in a sandbox before we ship a finding.
What about JWT alg-confusion or token forgery?
alg=none, RS256→HS256 confusion, kid path traversal and weak-secret brute-force are all in the playbook. Every token attack is reproduced live on staging — never just pattern-matched.
Can it find race conditions in our checkout flow?
We model the workflow and replay it with concurrent personas — coupon stacking, negative quantities and TOCTOU bugs in payment endpoints get reproduced with a verified PoC you can re-run.
Will SecureHup actually block my PR or just notify me?
Diff-aware: every PR triggers a focused replay against the preview env in under 3 min. Merge is only blocked when an exploit is actually reproduced — never on lint-style "maybe" findings.
Animated demo — every reply, citation and patch comes from the agents that already pentested your code.
A chat that has read your codebase.
Every answer is grounded on the same context the agents use to attack you — your routes, your auth model, your live findings — so you get specifics, not generic OWASP boilerplate.
Cited answers
Every claim links back to the exact file, function and finding it came from — no hallucinated APIs, no invented endpoints.
Threat-model aware
Knows your trust boundaries, roles and tenant model — so suggested mitigations actually match how your app is supposed to enforce access.
Lives next to your findings
Open any finding and ask "why is this CRITICAL?" or "what blast radius does it have?" — the chat already has the full exploit trace loaded.
From question to patch.
The chatbot doesn't stop at "here's what's wrong". It drafts the fix, points at the offending code, and tells your engineers what to verify before they merge.
Draft fixes on demand
"Patch endpoint X to enforce tenant scoping" returns a diff that fits your stack and existing patterns — ready to copy, push, or open as a PR.
Explain the chain
Ask how an attacker would weaponise a finding — the chat walks through the steps in plain English, with HTTP requests and impact at each hop.
Follow-up checks
Suggests the regression tests, log checks and re-scan queries you should run after merging — so a fix doesn't quietly reintroduce the bug elsewhere.