Safeguard vs. Data Theorem

Safeguard is an AI-powered application and software supply chain security platform designed to move security teams from vulnerability detection to automated remediation. The platform continuously inventories repositories, containers, software packages, dependencies, and other assets to create a live view of an organization's software environment. Griffin AI combines SBOM data, abstract syntax trees, call graphs, reachability analysis, exploit information, and business impact data to identify which vulnerabilities represent meaningful risk. Instead of generating a ticket for every finding, Safeguard can suppress unreachable issues and focus remediation efforts on vulnerabilities that can actually affect production systems. For actionable problems, its agents can author code changes or dependency upgrades, run automated testing, verify compatibility, and submit or merge pull requests under organization-defined policies. Safeguard also uses its Eagle adversarial model to search for zero-day vulnerabilities and test the validity of findings and proposed patches. Compliance capabilities automatically connect security activity and evidence to hundreds of frameworks while supporting SBOM formats such as CycloneDX and SPDX and recording SLSA provenance. The broader platform includes runtime defenses for AI systems, secure coding assistance, hardened zero-CVE packages and container images, Trust Centers, third-party risk management, and continuous security monitoring. Developers can work with Safeguard through IDEs, CLIs, source-control systems, CI/CD pipelines, cloud integrations, and more than 25 tenant-scoped MCP tools available to AI agents. Every automated action is designed to be logged, attributable, auditable, and governed by the same policies used throughout the platform.

Evaluate your applications, APIs, and any concealed resources within your vast multi-cloud environment. Craft specific policies tailored to different asset types, employ automated security testing tools, and assess vulnerabilities within your systems. It's crucial to tackle security risks before deploying into production, ensuring that both applications and cloud data comply with necessary regulations. Introduce automated remediation strategies for identified vulnerabilities, including options to revert changes to mitigate the risk of data breaches. Effective security measures detect problems quickly, while superior security solutions are capable of completely eliminating them. Data Theorem is committed to developing exceptional products that simplify the intricate challenges of modern application security. Central to Data Theorem’s offerings is the Analyzer Engine, which enables users to continuously test and exploit application vulnerabilities using both this engine and proprietary testing tools. Additionally, Data Theorem has developed the premier open-source SDK, TrustKit, which is widely adopted by a multitude of developers. As our technological ecosystem grows, we empower our clients to effortlessly protect their entire Application Security (AppSec) framework. By focusing on innovative strategies, we aspire to remain at the cutting edge of security technology, ensuring that our clients can navigate the evolving landscape of cybersecurity challenges. This commitment to proactive security measures underscores our mission to safeguard digital assets effectively.