Real attacks, taken apart. Every target anonymized, every technique intact - how we got in, why the gap was there, and exactly how to close it.

AI writes most startup code now, and it reproduces the insecure patterns in its training data at machine speed.

On a cloud-telephony platform.

Managed databases and buckets leak data when rules check that a caller is logged in but never that they own the record.

On a crypto-neobank.

The main app enforces auth well, but a sibling service on the same estate does not.

On a healthcare care-navigation startup.

Individually-medium findings combine into a critical breach.

On a contract-AI SaaS.

When a server trusts a caller-supplied email, domain, or identity claim as proof of who you are, anyone can become anyone.

On an AI lending platform.

MCP servers expose powerful tools to AI agents.

On a customer-support AI startup.

Self-registration that trusts a client role field or defaults new accounts to admin hands attackers privilege on signup.

On an AI voice-agent platform.

A live key shipped in a JS bundle, an APK, or a public repo is public.

On a property-management SaaS.

Shipping AI features creates attack surfaces classic appsec misses.

On an insurtech company.

An OTP with no rate limit, no expiry, and a code that never rotates makes brute force a certainty.

On a legal-AI platform for law firms.

On a student-housing CRM.

On a cardiac-telehealth clinic.

On a veterinary clinic-management SaaS.

On an EV-charging network.

On a healthcare voice-AI company.

On a real-estate CRM.

On a payments-orchestration platform.

On an AI-accounting fintech.

On a durable-medical-equipment marketplace.

On a coliving operator.

On a merchant-underwriting fintech.

On a diagnostics-AI company.

On a furnished-housing platform.

On a healthcare recognition platform.

On a large property marketplace.