Who is Data Theorem?
Data Theorem is a cybersecurity company that provides automated Application Security Testing (AST) and protection for web, mobile, and cloud-native applications and APIs for enterprise environments.
- Automated security analysis and remediation for web, mobile, and API-based applications.
- Application and Application Programming Interface (API) runtime protection for cloud-native and serverless workloads.
- Continuous security testing integrated into software development and DevOps pipelines.
- Coverage for modern architectures including microservices, containers, and serverless functions.
- Enterprise-focused reporting, policy controls, and compliance support for application security programs.
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More About Data Theorem
Data Theorem focuses on application and API security (application security) for organizations that build and operate web, mobile, and cloud-native software. Its offerings are designed to discover application assets, continuously scan them for vulnerabilities and misconfigurations, and provide protection controls that can be enforced at runtime. The company targets enterprise security, DevOps, and application development teams that manage large portfolios of digital services exposed over the internet or mobile platforms.
The platform is typically positioned as part of an enterprise application security program alongside Secure Software Development Lifecycle (SSDLC) (SDLC) practices and DevSecOps workflows. Data Theorem supports integration into Continuous Integration and Continuous Deployment (CI/CD) pipelines so that security testing can run automatically during build and deployment processes. This aligns with practices such as shift-left security, where vulnerabilities are identified earlier in the development cycle, and continuous security validation in production environments.
Data Theorem applies techniques that map to categories such as Dynamic Application Security Testing (DAST), API security testing, and runtime application protection. Its technology is commonly described in the context of modern architectures including Representational State Transfer (REST) and GraphQL APIs, microservices, containers, Kubernetes-based deployments, and serverless platforms. The offerings typically interact with standard web and mobile protocols such as HTTP/HTTPS and common API gateway patterns used in enterprise environments.
For mobile and web applications, Data Theorem tools can help organizations identify insecure data storage, weak authentication or authorization, vulnerable third-party libraries, and configuration issues related to encryption and network communications. For APIs and cloud-native workloads, the platform focuses on discovering exposed endpoints, validating security controls, and flagging issues such as excessive permissions, missing authentication, and insecure configurations in cloud services.
From a marketplace taxonomy perspective, Data Theorem fits within application security (AppSec), API security, mobile application security, and cloud-native security categories. Enterprises use it to support compliance objectives, reduce application exposure to common attack techniques, and centralize visibility over security posture across web, mobile, and API-based services. The combination of automated discovery, continuous testing, and runtime protection enables organizations to manage risk across distributed application architectures that span on-premises (on-prem) and public cloud infrastructure.
Our description of Data Theorem. Updated December 2025.
