Paid, authorized reviews
Qualify the business need, agree scope, authorization, and payment before testing, then deliver evidence, remediation support, and a re-test.
See the engagement model →I review the trust boundaries in founder-led, AI-coded SaaS—the auth, tenancy, integrations, business logic, and agent surfaces most likely to inherit repeatable mistakes.
The thesis
Models sample from a shared training distribution. They reproduce the same plausible-looking OAuth callbacks, middleware gaps, RLS policies, URL fetchers, and token checks across unrelated products.
That makes the bugs fingerprintable. The advantage is not generic “cybersecurity”; it is knowing where AI-scaffolded applications tend to put trust in the wrong tier, then testing those boundaries by hand.
Operating model
Qualify the business need, agree scope, authorization, and payment before testing, then deliver evidence, remediation support, and a re-test.
See the engagement model →Researcher-owned accounts, minimum reproducible proof, private disclosure, remediation first, and publication on a responsible timeline.
Read the advisories →The operator
Edu
Independent application-security researcher
I work directly with the founder or technical owner. There is no account team between the scope conversation, the testing, the report, and the re-test.
Non-negotiables
No hands-on client testing before the system boundary and permission are explicit.
Prove impact with the smallest safe action. No persistence, dumping, or destructive theater.
Every finding includes reproduction, impact, root cause, and a concrete remediation path.
An independently discovered vulnerability is disclosed for remediation whether or not paid work follows.
Work together
Send the product, business deadline, and high-risk workflow. I will tell you whether there is a sensible fixed scope.
Scope a security review