Discover AI
Build a view of supported AI applications, assistants, agents, runtimes, and connected components. Bring local evidence together with context from your directory and cloud environment.
COMING SOON · AI COVERAGE
AI adoption spans cloud services, desktop applications, coding assistants, and local runtimes. Each can introduce credentials, permissions, and connections that expand your identity attack surface.
Saporo is extending its Preemptive Identity Exposure Management platform to help uncover Shadow AI, connect AI-related evidence to your identity graph, and prioritize changes that reduce exposure.
PRODUCT PREVIEW
Join the waitlist for updates on Saporo’s AI coverage and opportunities to preview supported capabilities.
WHAT WE’RE BUILDING
Build a view of supported AI applications, assistants, agents, runtimes, and connected components. Bring local evidence together with context from your directory and cloud environment.
Connect AI components to identities, credentials, permissions, and reachable resources across directory, cloud and local environments. Understand how AI-related access can create attack opportunities.
Identify credential exposure, risky configurations, and excessive permissions. Use attack-path context to prioritize supported remediation and track changes in identity exposure over time.
SHADOW AI VISIBILITY
AI adoption can extend beyond centrally managed services. Coding assistants, browser extensions, local runtimes, and MCP configurations may be missing from IT’s inventory.
Saporo’s planned local discovery will surface AI tools and the settings, skills, plugins and connections surrounding them. Connecting these findings to identity and access context will help teams investigate Shadow AI and understand the exposure it introduces.
Go beyond identifying a tool. Understand the access and configuration that can make it an attack opportunity.
PLANNED INITIAL COVERAGE
Initial coverage brings together evidence from Active Directory, Azure, Entra ID, and local environments to connect AI discovery with identity exposure.
Review AI-related Group Policy settings alongside directory identities, computers, and permissions. Add context on configured policies and the systems they target.
Relate AI applications and supported agent identities to permissions and Azure resources. Understand the identities and delegated access through which AI can reach enterprise resources.
Identify supported AI applications, assistants, runtimes, MCP configurations, skills, and plugins. Add context from credential exposure indicators, local accounts, file permissions, and security settings.
COLLECTION APPROACHES
Directory and cloud evidence combines with endpoint collection to build the picture. Local collection methods depend on the operating system and the access available.
Agentless remote collection
Read supported AI files and settings remotely on reachable Windows devices, with the necessary local administrative access. No Saporo agent is installed on each target.
Planned on-device collection
Bring local AI tools and configurations into your identity exposure view through an on-device collector. Collection runs in the user’s context on macOS and Linux.
FREQUENTLY ASKED QUESTIONS
Initial coverage focuses on Active Directory, Azure, Microsoft Entra ID, and supported local AI tools and configurations. The goal is to connect AI-related evidence to the identities, credentials, permissions, and policies that determine exposure.
Local collection can surface supported applications, extensions, runtimes, and configurations that central inventories may miss. This gives teams evidence to investigate potential Shadow AI and assess its exposure. Finding an installation or configuration does not, by itself, prove active use or determine whether the tool is approved.
No. Planned coverage includes supported applications, assistants, coding tools, local runtimes, MCP configurations, skills, and plugins. Saporo will examine their identity and access context without assuming that every AI component is an autonomous agent or has a separate identity.
Direct provider integrations are planned for later phases. Initial coverage can still identify supported tools such as Claude Code, Cursor, and OpenAI Codex through local evidence, including configuration that references connected providers. This does not provide a complete view of the provider’s organization or workspace.
The initial Windows approach uses agentless remote collection and requires reachable devices and the necessary local administrative access. macOS and Linux collection is planned to run on the device in the user’s context. Directory and cloud evidence comes through the corresponding Saporo collectors.
Supported checks are being developed for exposed credentials, overly broad file access, risky MCP commands or connections, and permissive execution settings. Combining these findings with directory and cloud permissions will help reveal attack opportunities and prioritize changes that reduce exposure.
This capability focuses on discovery, identity access, and configuration exposure. Planned collection concerns selected application and configuration data, permissions, policy settings, and credential exposure indicators. It does not include collecting AI conversations, scanning source code repositories, or blocking agent actions at runtime.
AI coverage extends Saporo’s existing identity graph and exposure management capabilities. Supported AI findings and relationships will be analyzed alongside the wider environment, helping teams understand reachable resources, prioritize attack opportunities, and track the impact of supported remediation.
The capability is in development. Join the waitlist for updates on preview opportunities, supported coverage, and availability.
Get updates on AI discovery, Shadow AI visibility, and exposure reduction across cloud and local environments.