SAST
Static analysis tells you if your code has bad patterns.
Why apisec
Why apisec. Why now.
What's exploitable changes as fast as your application does. And your application is far more than code.
The real attack surface
Your application is a lot more than code.
Every piece below moves independently, and every one is part of what can be exploited, whether your team thinks about it that way or not.
AI-generated code, new microservices, new connections: they multiply that surface faster than any team can track by hand, and faster than a point-in-time review was ever built to catch. What worked two years ago wasn't built for this speed. Nothing was. Until now.
- APIs talking to other APIs
- Identity and access controls deciding who can touch what
- Third-party microservices you don't control
- MCP connections nobody mapped
- Business logic making the data-access decisions
What we do differently
We don't scan once. We build a living model of your application.
A living model of what your application actually is: code, APIs, the identity layer, and third-party connections. Then we run thousands of attacks against that model continuously, updating it in real time as your app changes, wired into your SDLC and CI/CD, on every release.
Not once a year. Not "mostly." If something's exploitable, you find out now, not after it's in production, and not after someone else finds it first.
This moment
AI didn't just change how fast you ship. It changed how fast you can be attacked.
Tools like Claude and OpenAI's models are changing how fast code gets written, and increasingly how it gets checked for surface-level flaws. That's real, and it isn't going away.
But generative AI is already being used to discover APIs and probe them for weakness, and it keeps getting better at it. When something's exploitable, AI doesn't just help attackers find it. It lets them exploit it at machine speed, continuously.
By 2029, Gartner projects that more than half of successful attacks on AI agents will exploit access-control gaps, not the code itself.
Source: Gartner — citation to be added
AI made building faster. It made exploiting faster too. What it didn't do is make "is this exploitable?" any easier to answer. That's still our job.
How apisec is unique
The living model is what makes everything else possible.
We build a living model of your application, because every application is different, and without that model you don't have anything. Without it, you have alerts. With it, you have proof.
- A live model of your app, not a snapshot.
- Thousands of AI-generated attack simulations, running continuously, adjusting as your app does.
- Built into your CI/CD, so nothing ships untested. Ever.
- Real, reproducible exploit paths across APIs, third-party services, identity, and access. The whole system, not just the repo.
Where we fit
apisec complements your security stack.
We fit right in.
DAST
Dynamic testing tells you if a running app has common, generic vulnerabilities.
SCA
SCA tells you if your dependencies have known vulnerabilities.
All of these matter. None of them tells you whether your actual application, with its real APIs, real authentication, and real third-party connections, can be exploited right now.
apisec tests what your other tools can't see: the business logic, the access control, and the way your APIs talk to each other and to services outside your walls. The stuff that's unique to your environment and breaks in ways a generic scanner was never built to catch.
And it's not a one-time integration. We plug into your SDLC and CI/CD once, then run continuously, evolving with your stack instead of going stale the way a point-in-time pen test does.
Other tools tell you what might be exploitable. We tell you exactly what is.