Arcjet has released AI Prompt Injection Protection, a new capability designed to stop prompt injection attacks before they reach production AI models. The feature detects hostile prompts at the application boundary and gives developers a decision point inside the request lifecycle where malicious instructions can be blocked before inference occurs.
Companies are shipping AI features into production faster than security review cycles can keep up. As those systems gain access to data, tools, and expensive model endpoints, the security problem shifts from filtering bad text to enforcing policy inside the request lifecycle using real application context.
Arcjet is introducing a new control in that runtime enforcement layer. It detects hostile prompts before inference, giving developers an inline decision point before requests reach the model.
Once those instructions enter the model’s context window, the application depends on the model to resist adversarial input and follow the intended system behavior. That is not a reliable security model for production systems.
Arcjet moves enforcement earlier in the request path. Before the model runs, applications can inspect prompts with full context such as identity, session state, routing, and business logic, and block hostile instructions before they ever reach the model.
“Prompt injection is one of the first places teams feel the gap in AI security, but the bigger shift is that production AI needs enforcement, not just moderation,” said David Mytton, CEO at Arcjet. “Arcjet gives developers a decision point inside the request lifecycle, where they can apply policy using real application context before risky requests reach the model.”
The new protection capability integrates directly into Arcjet’s application-layer security model, which already protects endpoints against common web attacks and automated abuse. With prompt injection detection, developers can inspect prompts inline and block malicious requests before they are sent to model providers.
The new capability composes with Arcjet’s existing Shield, bot detection, rate limiting, and sensitive information detection, helping teams protect AI endpoints from hostile prompts, automated abuse, sensitive data exposure, and unnecessary inference spend.
This approach complements other AI security techniques rather than replacing them. Red teaming and model-side guardrails help identify vulnerabilities before deployment, but runtime enforcement remains critical once AI systems are exposed to real user traffic.
Arcjet’s prompt injection protection works alongside existing capabilities including:
- Boundary protection for public AI endpoints using Arcjet Shield.
- Sensitive data and personal information detection controls before model context is built.
- Automation detection and spend protection for expensive AI routes.
By combining these protections inside the request lifecycle, Arcjet enables developers to treat AI endpoints as production infrastructure rather than experimental features.
Prompt injection detection is designed to operate inline with minimal operational complexity. Developers can integrate the protection directly into application code and apply it to endpoints built with JavaScript and Python and with frameworks such as the Vercel AI SDK or LangChain.
