Python AWS Lambda functions are ephemeral and highly distributed, which creates security visibility gaps that traditional perimeter defenses and proxy-based controls struggle to fill. Techniques such as credential stuffing, SQL injection, and server-side request forgery (SSRF) can look like legitimate application traffic, making them difficult to identify without visibility inside the application itself.

To help solve this challenge, Datadog App and API Protection (AAP) now extends full in-process application security monitoring to Python Lambda functions. By integrating directly with your application runtime through Datadog tracing libraries, AAP provides deeper insight into how requests interact with your code. This in-process visibility enables you to detect exploit attempts, correlate them with vulnerable code paths, and respond with higher confidence.

In this post, we’ll explore how AAP helps you:

Increase visibility in Lambda environmentsDetect successful injection attacks with Exploit PreventionIdentify and respond to account takeover attempts

Increase visibility in Lambda environments