Compare Dryrun Security vs. Cody

DryRun Security has been created based on our extensive experience in training over 10,000 developers and security experts in the realm of application security testing, as well as our work on security products at GitHub and Signal Sciences. Through this experience, we identified a significant gap in the current market: the lack of security context tailored for developers. Since developers are constantly making code adjustments throughout their workdays, they require a security solution that offers relevant security insights, enabling them to work more efficiently and safely. Traditional security code reviews can hinder the progress of development teams, often occurring too late in the production cycle. It is essential for developers to receive security context as soon as a pull request is initiated, allowing them to understand the potential impacts of the code changes being submitted. Up until now, the majority of security testing has employed a one-size-fits-all strategy, leading to developer frustration due to excessive, repetitive alerts and unreliable outcomes. By focusing on providing actionable security context at critical moments, DryRun Security aims to revolutionize the way developers approach security in their workflows.

Cody is an advanced AI coding assistant developed by Sourcegraph to enhance the efficiency and quality of software development. It integrates seamlessly with popular Integrated Development Environments (IDEs) such as VS Code, Visual Studio, Eclipse, and various JetBrains IDEs, providing features like AI-driven chat, code autocompletion, and inline editing without altering existing workflows. Designed to support both individual developers and teams, Cody emphasizes consistency and quality across entire codebases by utilizing comprehensive context and shared prompts. It also extends its contextual understanding beyond code by integrating with tools like Notion, Linear, and Prometheus, thereby gathering a holistic view of the development environment. By leveraging the latest Large Language Models (LLMs), including Claude 3.5 Sonnet and GPT-4o, Cody offers tailored assistance that can be optimized for specific use cases, balancing speed and performance. Developers have reported significant productivity gains, with some noting time savings of approximately 5-6 hours per week and a doubling of coding speed when using Cody.