System prompt hardening

System prompts operate behind the scenes, hidden from traditional scanners. This creates a critical visibility gap, leaving core AI logic unmonitored and unprotected.

Without standardized metrics, security teams cannot measure vulnerability severity. This makes it extraordinarily difficult to prioritize risks or justify security resources to leadership.

Developers lack a formal playbook for securing AI instructions. This absence of standards leads to inconsistent logic, increasing the risk of injection and data leaks.

Automatically detect hidden prompts and gain immediate context. By labeling prompts as “conversational,” teams can quickly identify specific attack vectors and prioritize high-risk components.

Stop guessing which threats matter. AI Weakness Enumeration (AIWE) provides a 1–100 score, allowing you to prioritize the most critical AI security risks objectively.

Automatically refine prompt logic to close security gaps. This ensures your AI applications are resistant to adversarial manipulation and protected against unauthorized data exposure.

“One of our most indicative KPIs is the amount of time for us to remediate vulnerabilities and also the amount of time developers spend fixing vulnerabilities in our code base, which has reduced significantly. We’re talking about at least 80% reduction in time.”

“When the product you sell is an application you develop, your teams need to be fast, secure and compliant. These three factors often work in opposite directions. Mend provides the opportunity to align these often competing factors, providing Vonage with an advantage in a very competitive marketplace.”

“The biggest value we get out of Mend is the fast feedback loop, which enables our developers to respond rapidly to any vulnerability or license issues. When a vulnerability or a license is disregarded or blocked, and there is a policy violation, they get the feedback directly.”