Compare Backslash Security vs. Native

Backslash Security is the governance and visibility platform built for organizations where AI coding tools are already part of how software gets built. GitHub Copilot, Cursor, Windsurf, Claude Code, and Gemini CLI have fundamentally changed the development lifecycle — and the security controls most organizations rely on were not designed for this environment. Backslash provides a comprehensive AI coding tool inventory and policy enforcement across the full AI coding spectrum, giving security teams visibility into every active tool and the risk introduced before it reaches production. This includes vibe coding security — risk detection purpose-built for vulnerability patterns in AI-generated code that traditional scanners are not equipped to catch. As AI coding agents grow more capable, they increasingly operate with access to external services, internal data, and organizational infrastructure through MCP servers. Over-permissioned agents and misconfigured MCP connections create data leakage pathways — exposing sensitive organizational data to AI models without security team awareness or enforcement controls. These are active exposure points, not theoretical risks. Backslash addresses this directly. The platform maps every MCP server connection, identifies over-permissioned AI agent configurations, and enforces least-privilege access before data leakage occurs. Security teams gain full visibility into what AI agents can access and where permissions exceed what the task requires. For security leaders governing an environment that moved faster than their controls, Backslash is the missing layer — built from the ground up for AI-native development, not retrofitted from a previous generation of tooling.

Native serves as a cloud security control plane aimed at assisting organizations in establishing, executing, and upholding security policies throughout various cloud environments, encompassing contemporary AI infrastructures. Its primary objective is to deliver governance that is inherently secure, allowing teams to manage the provisioning, access, and oversight of AI services and cloud resources within their systems. Users can articulate their desired security objectives, which Native then translates into the necessary technical controls tailored for each cloud provider, thereby removing the need for manual interpretation of best practices or individual policy configurations for multiple environments. Additionally, Native enhances risk management through comprehensive visibility and planning tools that facilitate asset discovery, change simulation, and control implementation to mitigate risks and limit potential damages across systems. Moreover, it incorporates sophisticated functionalities such as environment segmentation, protection of data perimeters, and strategies for managing blast radius containment, further strengthening an organization’s security posture. By integrating these features, Native ensures a robust framework for cloud security management.