Automated vulnerability analysis that shows what can actually reach you

Reachability decides which alerts matter

Dependency alerts arrive by the hundred, most of them for code paths that never run. Static analysis flags patterns without knowing whether an attacker can reach them. The result is either alert fatigue or a backlog nobody trusts.

Static analysis and vulnerability intelligence supply the candidates, from your application code, your infrastructure as code and the published CVEs and advisories that match your dependencies. AI reasoning then does the part a scanner cannot: it reads the surrounding code to judge whether a vulnerable function is reachable, what input controls it, and what an exploit would expose.

An engineer checks every finding before it reaches you

Findings are triaged and prioritized by their impact in your system rather than by a generic severity score, and each comes with a suggested remediation. You receive checked results rather than raw tool output.

Coverage follows your changes, your permissions and the next advisory

Changes get a security-focused review as they are made, because a control can vanish in an ordinary merge. In one incident in my own factory’s records, 2 live security gates disappeared from a merge request after a stale base and a conflict resolution, and neither commit message mentioned it.

Cloud permissions and configuration are in scope, since an over-broad role or an exposed resource is often a larger risk than any code defect. New advisories are checked against what you already run, so a CVE published next month is assessed against your code when it appears rather than at the next audit.

Agents probe your system the way an attacker works

Agentic red-teaming uses autonomous agents that probe a system the way an attacker would: looking for a way in, following what they find, and chaining small weaknesses into a real path.

For a specific question, such as whether a newly disclosed vulnerability affects you, AI-assisted research traces the code path and reports what it found, how sure it is, and the evidence an engineer needs to check it.

My production security work taught me to ask what an attacker can do next

I have built a production system that streamed pending transactions, decoded them as they arrived, classified their intent and stopped a malicious one before it confirmed. This analysis asks your system the same question: what can an attacker do from here?

Your next professional security assessment starts better informed

Automated analysis and agentic red-teaming support a professional security assessment. They give that assessment more to work from and keep the findings between assessments visible.

It starts with a workflow review and runs with no constant meetings

A workflow review comes first, where I look at how a change moves through your team today and where security review sits in it. After that, my software factory does the volume of analysis, I review what it produces, and you get checked findings with no constant meetings.

Start with a workflow review, and bring the scanner backlog nobody trusts.