Find the AI agents
Discover internal copilots, agent frameworks, MCP servers, automation scripts, RAG apps, and LLM-connected tools.
AI security assessment and scanner
Kavryl scans your cloud, SaaS, identity, GitHub, and AI agent configs to show what AI systems exist, what they can access, and what to fix first.
Plain-English service
We run read-only scanners, review permissions, map risky access paths, and deliver an executive report your CIO, CISO, CEO, and engineering team can understand.
What we check
Most companies do not know which AI tools are connected to sensitive data. Kavryl gives you that visibility quickly, without needing admin write access.
Discover internal copilots, agent frameworks, MCP servers, automation scripts, RAG apps, and LLM-connected tools.
Review file access, shell access, browser tools, OAuth scopes, SaaS connectors, cloud permissions, and secrets exposure.
Prioritize findings by business impact, sensitive data access, destructive permissions, and likely attack paths.
What you get
A focused assessment for teams that need a clear answer: where are our AI agent risks and what do we fix first?
Scan Azure, AWS, GitHub, Microsoft 365 / Entra, Google Workspace, repos, MCP configs, and LLM app settings.
Connect agents, apps, identities, OAuth grants, cloud roles, secrets, and data stores into clear exposure paths.
Deliver a simple business report with severity, evidence, MITRE ATLAS and OWASP mapping, and owner-ready fixes.
Give security and engineering a short action plan to reduce access, tighten approvals, and monitor high-risk agents.
How we help
Kavryl starts as a practical service and scanner. The platform grows into continuous monitoring for AI agent exposure.
Collect read-only evidence from cloud, SaaS, identity, GitHub, and agent configuration sources.
Translate technical exposure into simple business risk: sensitive data, privilege, blast radius, and misuse paths.
Track fixes, reduce risky permissions, and monitor new AI agents as teams adopt more automation.
Why now
The risk is not only what an agent says. It is what the agent can do after it receives a bad instruction.
Buyer questions
AI agent security means finding AI agents, understanding what tools and data they can access, limiting risky permissions, and monitoring actions like sending messages, changing tickets, reading files, or running commands.
MCP security reviews Model Context Protocol servers and tools, including file access, shell access, browser automation, SaaS connectors, OAuth scopes, identity boundaries, and approval controls.
Kavryl scans for AI agents, MCP configs, LLM frameworks, risky tools, secrets, broad OAuth scopes, SaaS access, RAG apps, and cloud access paths.
Kavryl is built for CISOs, CTOs, security engineers, product security teams, platform teams, and engineering leaders adopting AI agents, MCP tools, internal copilots, RAG apps, or AI workflow automation.
What buyers receive
Security leaders need more than scanner output. Kavryl delivers executive, cloud, SaaS, identity, and agent reports that explain blast radius and owner-ready remediation.
Board-ready summary with business impact, top access paths, OWASP/API mapping, MITRE ATLAS-style interpretation, and first actions.
Synthetic subscription, account, resource, and ARN evidence modeled on Kavryl Azure and AWS scanner output.
Microsoft 365 / Entra, Google Workspace, GitHub, OAuth grants, and MCP tool findings with clear remediation steps.
Kavryl Security