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Boost Your Security Knowledge and Skills

Code velocity in an AI-era and how AppSec teams can stay ahead

In this fireside chat, we will share how teams securing real AI applications are approaching LLMs in practice, what changes, what stays the same, and where workflows need to evolve

Building Secure AI Applications

“Building Secure AI Applications” is your practical playbook for shipping LLM features without widening your attack surface. It distills the OWASP Top 10 for LLM Applications into a clear reference architecture, real controls, and a checklist that maps mitigations to the right layers. The guidance points to proven controls and third-party tools across the ecosystem so your teams can move faster with guardrails that hold up in production.

Code Review Agent Coverage Matrix

See the vulnerability categories the DryRun Security agents detect, with short definitions and example CWE mappings to help you align coverage to common weakness types.

Custom Policy Agent

The DryRun Security Custom Policy Agent lets you write secure-coding policies in plain English and automatically enforce them on every pull request all while delivering inline, developer-friendly guidance. And one of the best parts: there’s no regex, DSLs, or per-language rule maintenance.

SAST Accuracy Report

The SAST Accuracy Report puts five leading tools to the test—no tuning, no excuses—revealing how they handle real vulnerabilities like IDOR, BOLA, and broken authentication. See why DryRun Security’s AI-native engine delivers the accuracy and context others miss.

An AI-native Approach to Discovering Logic & Authorization Flaws

If you’re struggling with Authorization Mismatch, Authorization Bypass (e.g. IDOR, BOLA), authorization flaws, or you just can’t effectively identify complex logic flaws in modern API code, then this whitepaper is for you. It covers an LLM-native approach that combines deterministic evaluation and contextual reasoning to solve this problem at speed and at scale.

AI-powered AppSec

Explore the intersection of AI and application security with Ken Johnson, Co-founder and CTO of DryRun Security, as he shares our journey in utilizing Large Language Models (LLMs) for application security.

Contextual Security Analysis Guide

Find out more about how you can implement Contextual Security Analysis to improve CI/CD pipeline issues, reduce the time for discovery of security issues, and provide collaboration between groups.

Datasheet

We're passionate about providing a legitimate way for security teams to scale and developers to secure their code easily yet effectively. Download our datasheet for details on how you can break through the rules of AppSec to a better code review process for all.

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December 9, 2025

Building Secure AI Applications

“Building Secure AI Applications” is your practical playbook for shipping LLM features without widening your attack surface. It distills the OWASP Top 10 for LLM Applications into a clear reference architecture, real controls, and a checklist that maps mitigations to the right layers. The guidance points to proven controls and third-party tools across the ecosystem so your teams can move faster with guardrails that hold up in production.

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Contextual Security Analysis Guide

Find out more about how you can implement Contextual Security Analysis to improve CI/CD pipeline issues, reduce the time for discovery of security issues, and provide collaboration between groups.

Ken Johnson
Co-founder & CTO