Solution · Shadow AI

Detect and Govern Shadow AI
Everywhere It Runs

Quick answer
Shadow AI is any AI tool, model, agent or MCP server used without security approval — whether on a laptop, inside source code or in a production workload. TigerGate discovers it at all three layers: the endpoint agent on devices, AI-SPM in code and cloud, and the eBPF AI gateway at runtime. Each finding shows who uses it and lets you allow or block it.
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Three Layers of Shadow AI

Point tools catch one. TigerGate covers all three in one console.

Laptops & employee devices

AI desktop apps, IDE assistants, AI CLIs, MCP servers, local models like Ollama

Source code

LLM API calls, model packages, vector DBs, prompt files, agent frameworks

Cloud + production workloads

eBPF AI gateway inventories live LLM traffic from Kubernetes, Docker, ECS and VMs

Why Shadow AI Is Different from Shadow IT

Shadow IT is a Dropbox install that bypasses IT. Shadow AI is an AI assistant that reads source code into a third-party model, an MCP server that calls back to an unknown endpoint, or an agent that spends real cloud budget on real cloud resources. The data-governance, cost, and credential-exposure risks are categorically different.

Three real patterns we see weekly: engineers using personal ChatGPT accounts to debug production code; developers installing MCP servers from GitHub that trigger shell commands on their laptop; agents configured in a side project calling corporate API keys picked up from ~/.env files.

What You Can Do With a Shadow AI Inventory

  • Approve or block per team. Platform engineers may run local models; finance may not.
  • Request/approve workflow. Developers request an AI tool, security approves with policy.
  • Rotate corporate credentials found in personal-account AI tool configs.
  • Produce ISO 42001 / EU AI Act evidence — a dated, exportable inventory of AI systems in use.
  • Monitor data exposure. Flag AI tools that process code or customer data without approved DPAs.

Compliance Mapping

  • ISO 42001 (AI Management Systems): AI inventory, risk assessment, lifecycle controls
  • EU AI Act: Article 6+ system inventory and classification
  • NIST AI RMF: MAP-1 (context) and MAP-2 (categorisation) require a system-of-record for AI in use
  • SOC 2: CC6.1 (logical access) when AI tools authenticate with personal accounts
  • DPDP Act (India): inventory and data-protection obligations extend to AI data processors

See compliance automation.

Shadow AI FAQ

Shadow AI is any AI tool, model, agent or MCP server used without security approval — whether on a laptop, inside source code, or in a production workload. It is the AI equivalent of shadow IT.
Data leakage into third-party models, prompt injection through compromised tools, agents calling unapproved cloud APIs, personal-account AI use that leaves no audit trail, and vendor supply-chain risk from MCP servers that call back to unknown endpoints.
Shadow IT is unapproved software. Shadow AI is a subset — AI-specific software, including models, agents, LLM gateways and MCP servers that may process company data in ways that bypass data governance.
A device-level agent inventories AI desktop apps, browser AI apps, IDE AI assistants, AI coding CLIs, MCP servers (local and remote), locally running models (Ollama, LM Studio) and the accounts used to authenticate to each — then flags unapproved ones.
Static and infrastructure analysis identifies LLM API calls, model packages (transformers, langchain, OpenAI SDK), vector databases and cloud-hosted model endpoints across your codebase and cloud accounts. See TigerGate AI-SPM for the full code and cloud scope.
An eBPF AI gateway sits in front of workload-level LLM traffic and inventories which models are being called from Kubernetes, Docker, ECS and bare metal — including models that weren't declared in code.
Yes. ISO 42001 (AI Management Systems) requires organisations to maintain a documented inventory of AI systems in use. Shadow AI detection is the operational control that produces that inventory.

Start Finding Shadow AI

Deploy TigerGate on 10 developer laptops and connect one cloud account. First shadow-AI inventory inside the trial.

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