About DryRun Security

Provides a GitHub-integrated security tool that uses Contextual Security Analysis to evaluate every pull request, identifying vulnerabilities like SQL injection, XSS, and broken access controls by analyzing code behavior, language, and environment. This approach delivers real-time security context to developers, reducing false positives and accelerating code reviews without slowing down the development pipeline.

```xml <problem> Security code reviews often slow down development teams and happen too late in the development pipeline. Developers need security context right when a pull request is opened to understand the impact of code changes. Existing security tools can burden developers with bloated build times and confusing results. </problem> <solution> DryRun Security provides a GitHub-integrated security tool that uses Contextual Security Analysis to evaluate every pull request. This approach analyzes code behavior, language, and environment to identify vulnerabilities like SQL injection, XSS, and broken access controls. By delivering real-time security context directly within the pull request, DryRun Security empowers developers to secure new features without slowing down the development pipeline. The tool aims to reduce false positives and accelerate code reviews by matching behavior rather than relying solely on pattern-based analysis. </solution> <features> - Contextual Security Analysis: Evaluates pull requests based on behavior, language, intent, detections, and environment. - Suite of Analyzers: Includes analyzers for secrets, codepaths, sensitive files, SQL injection, authentication/authorization, IDOR, SSRF, XSS, code behavior, code summary, mass assignment, and command injection. - Real-time Feedback: Provides security context to developers within seconds of opening a pull request. - GitHub App Integration: Installs in less than a minute and integrates directly into the GitHub workflow. - Support for Multiple Languages: Optimized for Python, Java, JavaScript/TypeScript, C++, C#, Golang, Rust, Swift, PHP, Ruby, Kotlin, Scala, and COBOL. - Private LLM: Uses a private LLM to analyze code, ensuring data is not fed through a public AI system. - Ephemeral Microservices: Employs ephemeral microservices to ensure code vanishes from the analysis engine after task completion. </features> <target_audience> The primary users are development teams and security professionals who need to identify and address security vulnerabilities in their code before it is merged into the main codebase. </target_audience> ```

What does DryRun Security do?

Where is DryRun Security located?

DryRun Security is based in Gainesville, United States.

When was DryRun Security founded?

DryRun Security was founded in 2023.

How much funding has DryRun Security raised?

DryRun Security has raised 11200000.

Location

Gainesville, United States

Founded

2023

Funding

11200000

Employees

10 employees

Major Investors

LiveOak Ventures, Work-Bench

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DryRun Security

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Executive Summary

dryrun.security 1K+

Crunchbase

Founded 2023 – Gainesville, United States

Funding

Estimated Funding

$10M+

Major Investors

LiveOak Ventures, Work-Bench

Team (10+)

No team information available.

Company Description

Problem

Security code reviews often slow down development teams and happen too late in the development pipeline. Developers need security context right when a pull request is opened to understand the impact of code changes. Existing security tools can burden developers with bloated build times and confusing results.

Solution

DryRun Security provides a GitHub-integrated security tool that uses Contextual Security Analysis to evaluate every pull request. This approach analyzes code behavior, language, and environment to identify vulnerabilities like SQL injection, XSS, and broken access controls. By delivering real-time security context directly within the pull request, DryRun Security empowers developers to secure new features without slowing down the development pipeline. The tool aims to reduce false positives and accelerate code reviews by matching behavior rather than relying solely on pattern-based analysis.

Features

Contextual Security Analysis: Evaluates pull requests based on behavior, language, intent, detections, and environment.

Suite of Analyzers: Includes analyzers for secrets, codepaths, sensitive files, SQL injection, authentication/authorization, IDOR, SSRF, XSS, code behavior, code summary, mass assignment, and command injection.

Real-time Feedback: Provides security context to developers within seconds of opening a pull request.

GitHub App Integration: Installs in less than a minute and integrates directly into the GitHub workflow.

Support for Multiple Languages: Optimized for Python, Java, JavaScript/TypeScript, C++, C#, Golang, Rust, Swift, PHP, Ruby, Kotlin, Scala, and COBOL.

Private LLM: Uses a private LLM to analyze code, ensuring data is not fed through a public AI system.

Ephemeral Microservices: Employs ephemeral microservices to ensure code vanishes from the analysis engine after task completion.

Target Audience

The primary users are development teams and security professionals who need to identify and address security vulnerabilities in their code before it is merged into the main codebase.