As AI-first development and vibe coding accelerate software delivery, Legit Security is helping enterprises stay safe with a major update to its AI Security Command Center. The platform provides security teams with comprehensive insights into how AI-generated code, AI models, and MCP servers are used—and where they introduce risk—across the software development lifecycle (SDLC).
Balancing speed with security
While AI-assisted coding can dramatically increase productivity, it also introduces new vulnerabilities. Unvetted or low-reputation AI models may inject insecure code or bypass corporate policies, exposing applications to risk. Legit’s updated platform gives CISOs, AppSec teams, and product security professionals a single dashboard to monitor AI usage, detect unauthorized models, and track risks over time.
Key features in the updated AI Security Command Center include:
- Complete visibility into AI usage: Instantly see which AI models and MCP servers are in use, highlight areas of risk, and track frequently used or newly introduced AI components. Each model is enriched with reputation context for better decision-making.
- Detection of risky and unauthorized AI models: Identify low-reputation or unapproved models that could introduce vulnerabilities, even when engineers attempt to bypass corporate security policies.
- Real-time AI risk monitoring: Track riskiest AI secrets, policy-based risks, and changes in AI risk over time to measure organizational exposure.
- Team- and application-level metrics: The new AI heat map pinpoints teams generating the most AI security issues, enabling targeted training or remediation.
Yoav Stahl, VP of Product at Legit, noted, “AI tools have made it faster for application teams to deliver, but they’ve also increased many companies’ security risk levels. Security teams often lack visibility and a clear understanding of these risks. This release addresses a critical gap in AppSec for the AI era.”
With AI becoming an integral part of modern development, Legit’s enhanced platform positions security teams to proactively manage AI-driven risks without slowing innovation.
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