Sicherheit beginnt mit
Transparenz.

Organizations with 81–100% AI-generated code ship vulnerable code at 3.4× the rate of those with 1–20%. Prioritization must account for AI code volume as a risk multiplier — not just severity scores. Effective security requires prioritization based on real-world risk, context, and cumulative exposure, not simply the number of findings.

Security cannot remain a checkpoint. It must be integrated directly into how developers write, test, and ship code — within the IDE, pipelines, and AI-assisted workflows where development now happens.

Tool sprawl and unclear ownership are limiting effectiveness. Organizations must simplify their security stacks, align responsibilities, and ensure consistent use of tools across teams and workflows.

AI should not be treated as an exception. Organizations need consistent governance over what is deployed, how it behaves, and what it can access — applying the same discipline to AI systems as to the rest of the software stack.

Developers are increasingly responsible for security outcomes. To succeed, they need systems that reduce noise, provide clear guidance, and enable action — not additional friction or disconnected tooling.

The window between vulnerability and exploit has collapsed to minutes. Manual triage and human-gated remediation can no longer keep pace. The only viable response is defense that combines the speed and automation of agentic AI with the precision of a deterministic engine.