What Is Shadow IT Detection? Manage and Uncover Risks

Employees are increasingly building custom tools using low-code/no-code platforms and AI builders like Lovable. They deploy these tools instantly, often without audit trails or security checks. This creates problem like tool sprawl, data risk, and compliance gaps. 

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Traditional shadow IT detection can’t help because it only flags third-party SaaS usage, not self-built apps running inside the firewall. However, Superblocks offers a governed environment that supports this kind of democratized development with full visibility.

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In this article, we'll cover:

• What shadow IT looks like in 2025
• Why traditional detection methods miss internal development
• How to identify and manage shadow internal tools

What shadow IT looks like in 2025

In 2025, shadow IT consists of employees building apps and workflows themselves without governance. In the past, employees drove shadow IT by purchasing unauthorized software. 

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Key examples include:

• Internal apps with no governance: Teams build custom dashboards, approval workflows, and data processing tools. They often bypass security review or formal deployment processes. This is a risk since these apps often connect to production databases and handle sensitive information. 

• Citizen-built workflows using low-code tools: Business users create automated processes in platforms like Zapier without proper oversight. These workflows can modify data, trigger actions, and integrate with critical systems.

• AI agents or bots running without audit trails: Employees build ChatGPT plugins, custom AI assistants, or automated bots that process company data through external APIs. These tools often lack logging, access controls, or data governance.

• Scripts and tools in untracked cloud environments: Developers deploy data pipelines or temporary solutions in personal cloud accounts, GitHub repositories, or sandbox environments that never get documented or secured.

Why traditional shadow IT detection falls short

Traditional shadow IT falls short because it cannot monitor the new wave of internal tooling built with low-code and AI coding tools. 

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Key gaps in 2025:

• No financial footprint: When an employee uses a free tier to build a customer data analysis tool or creates a workflow in a personal account, there's no spending to track.
• Instant deployment: AI tools can create functional applications faster than traditional approval cycles can even respond. By the time IT notices unusual activity, the tool is already in production use.
• Development happens everywhere: 82% of developers now build AI-generated solutions in environments that IT can’t monitor. They create solutions in personal cloud accounts, GitHub repositories, or browser-based platforms that don't route through corporate networks.

• No inventory of internally built apps: There's no centralized registry of custom applications, workflows, or automation scripts.

• Invisible integrations: Traditional detection monitored network traffic for known SaaS applications. Employees now build custom integrations through existing approved platforms. These connections look like normal business activity.

• Sensitive workflows run without oversight: Employees automate critical business processes with ad-hoc tools that lack proper authentication, logging, or backup procedures. When these tools break, the business impact can be significant.

What makes shadow internal tools risky

Shadow internal tools often touch sensitive systems but lack the guardrails of officially approved software.

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Common issues include:

• Unknown integration points: Employees create new workflows that connect internal tools to external services without approval. IT can’t see or monitor the risks associated with these connections.

• No audit logs or deployment history: These tools rarely log user actions or changes. That means no one knows who ran what, when, or why.

• Sensitive data passed into GenAI tools: Employees copy customer data or proprietary logic into AI tools like ChatGPT or Claude. These actions often happen outside your data loss prevention (DLP) controls with no visibility or review. 
• No RBAC: Shadow IT applications typically lack role-based access control. Teams might share a single admin login, or leave apps open without SSO, exposing sensitive functionality to anyone with the link.

• Public-facing apps deployed from test environments: Developers sometimes deploy test apps in cloud environments with default settings. These apps stay live and accessible to the public long after testing ends.

How to detect shadow IT across your internal stack

You can detect shadow IT across your internal stack by monitoring development activities, integrations, and unusual usage patterns.

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Here are key steps to shadow IT discovery across internal environments:

Code and development detection

Unapproved development often leaves a trail across source control, infra, and identity systems. Start by surfacing where unauthorized projects may live or run: 

• Check code repositories (GitHub, GitLab, internal Git servers) for unknown projects or scripts that aren’t part of official products.
• Scan the infrastructure for deployed applications that aren’t in the Configuration Management Database (CMDB).
• Check your identity provider for unauthorized OAuth connections.
• Flag unexpected low-code tools usage like Zapier workflows and Airtable databases.
• Detect unusual spikes in GPU usage on workstations or cloud instances that could indicate local AI model usage.
• Track outgoing traffic patterns to known AI service domains (OpenAI, Anthropic APIs).

Integration point detection

Unauthorized workflows often show up at your API edges. Focus on where data moves across tool boundaries:

• New external API calls that weren't in previous code versions.
• Traffic to platforms like Vercel, Netlify, GitHub Pages from corporate networks.
• Employees accessing personal AWS, Google Cloud, or Azure accounts during work hours.

Monitor behavioral and financial patterns

Shadow IT also shows up in how people behave. Financial records and usage patterns can signal unapproved tooling:

• Flag personal software or AI tool subscriptions that show up in expense reports.
• Look for after-hours development activity or productivity tool spikes.
• Monitor Slack, Notion, and docs for internal sharing of unsanctioned workflows or links.

Enable centralized monitoring and alerts

Once you’ve identified the weak points, bring everything into a unified view. Shadow IT detection gets more effective when signals are connected:

• Track data transformations and business logic flows across internal tools.
• Monitor prompts to external AI services and resulting data flows.
• Consolidate alerts and audit logs into shared dashboards for IT and security teams.

For more on securing low-code development, see our guide to low-code security.

Superblocks as a visibility and governance layer

Superblocks is a centrally governed platform that prevents shadow AI risks by giving IT full visibility and control over every app, workflow, and data integration. Instead of code scattered across personal tools, all development happens in a secure, auditable environment with compliance guardrails built in.

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Employees still get full flexibility (AI, WYSIWYG visual editor, or code) but within a governed environment that enforces RBAC, audit logs, and security policies by design.

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This capability is powered by:

• Context-aware AI: Clark AI, Superblocks AI agent, enforces organizational standards on every app it builds. It applies RBAC, schema constraints, and security policies automatically, so nothing escapes governance.
• Centralized oversight: Superblocks provides a unified dashboard for IT and platform teams to view all apps, jobs, and workflows.
• Controlled integrations: Limit which data sources and backend services can be used, giving IT visibility and control over external connections and sensitive data flow.‍
• RBAC for apps, data, and actions: You can set roles/permissions to control who can create apps, who can deploy them, and who can use them down to specific functionality.‍
• Standardized security and compliance: Every app built in Superblocks follows the same audit, logging, and policy requirements. The platform eliminates one-off tools with unknown risk by enforcing code validation, guardrails, and auditability at every step.‍
• Safe development spaces for citizen devs: Business users can build applications with pre-configured security controls, approved data connections, and automated checks. This reduces shadow IT by providing a sanctioned path for internal development.‍
• Built-in activity monitoring: Superblocks includes audit logs that capture user actions, app launches, data access, and changes to configurations. If a user runs an internal workflow, you’ll know who, when, and what the result was.‍
• Reusable building blocks: Enforce standards and policies by creating and distributing approved UI components, integration connectors, and logic blocks that everyone can reuse.‍
• Deploy in VPC or hybrid environments: The On-Premise Agent lets you run applications inside your network perimeter. You avoid the data exposure risk of shadow IT tools that might otherwise live on external servers.‍
• Secrets management and versioning: Superblocks manages credentials and API keys centrally. Git-based workflows track every change and let you roll back when needed.

6 tips to reduce shadow IT without slowing teams down

You can reduce shadow IT by giving users better sanctioned alternatives that work for their needs.

Here are seven tips:

1. Inventory internal apps

Ask teams what tools they’ve built and why. Most shadow tools exist because official ones don’t meet their needs. Start by understanding the gap.

2. Provide better alternatives

Replace unauthorized tools with approved platforms that do more. If teams are building scripts that call external APIs directly, give them access to approved internal API gateways. If they're building in personal development environments, provide governed development platforms like Superblocks.

3. Implement governance through platforms

Use platforms that include audit logs, access controls, and usage monitoring out of the box. Make it easier to build correctly than to build in the shadows.

4. Create fast-track approval processes

Establish a rapid evaluation process for new tools. Aim for 48-72 hours rather than weeks. Create pre-approved categories (development tools, productivity apps) that teams can adopt immediately with basic security requirements.

5. Enable self-service with guardrails

Let teams provision tools, data access, or environments themselves. For example, cloud accounts with spending limits, development environments with security controls, or internal tool builders with data access restrictions.

6. Address root causes, not symptoms 

Treating the underlying problem prevents recurrence. If teams are building shadow IT because procurement is slow, fix procurement. If they're doing it because approved tools lack features, upgrade the approved tools. 

Best practices for shadow IT prevention

Organizations prevent shadow IT when they give teams the right conditions to build securely, collaboratively, and in the open.

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What works:

• Dev-approved templates: Give teams starter templates for common use cases like dashboards, approval workflows, and data processing tools. This reduces the need to build from scratch in unsanctioned environments.

• CI/CD enforcement: Require all internal tools to follow your deployment pipeline. Even simple apps should go through testing, review, and version control.

• Monitoring AI output: Track what employees send to external AI tools, what responses come back, and how that data flows into your systems.

• Logging user access and actions: Log not just app access, but what users did, including edits, submissions, and data exports. Full visibility prevents silent failures and unauthorized changes.

What to avoid:

• One-off builds with no code history: Any tool that can’t be rolled back or reviewed creates risk. Use Git-based workflows to track changes.

• Apps running in unmanaged environments: Don't allow production applications to run in personal cloud accounts, unsupported infrastructure, or environments without proper monitoring and backup procedures.

• Manual-only governance processes: If governance depends entirely on people reviewing requests, it won’t scale. Automate as much of the process as possible.

• Ignoring non-engineer-built tools: Don't assume that only developers can create shadow IT. Business users with access to low-code tools, AI platforms, or automation services can create significant risks.

 Read our complete guide to citizen developer governance.

Shadow IT starts at home — Superblocks can help

Your internal tools are part of your attack surface. If you can’t see them, you can’t secure them.

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Superblocks gives you a unified view of your tooling ecosystem while providing teams the AI-powered building tools, visual editors, and code flexibility they want.

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Key capabilities include:

• Centralized app inventory: See all internal applications, who built them, and what systems they connect to in one dashboard.
• Granular access controls: Define who can build apps, access specific data sources, and deploy to different environments.
• Complete audit trail: Track every user action, data access, and application change with built-in logging.
• Standardized security policies: Automatically apply consistent security controls across all internal development.
• Network-level control: Deploy within your infrastructure to maintain data boundaries and compliance requirements.

Ready to see how Superblocks can help you gain visibility into your internal stack? Schedule a demo with one of our product experts.

Frequently asked questions

What are the biggest risks from citizen developer tools?

The biggest risks from citizen developer tools are that they often bypass security controls. These tools can access production data, lack audit logs, and expose systems when the creator leaves.

Can GenAI agents introduce shadow IT?

Yes, GenAI agents introduce shadow IT. Employees use AI tools to generate code, create workflows, and build integrations that process sensitive company data, often outside IT’s view.

Are firewalls enough to detect shadow apps?

No. Firewalls are not enough to detect shadow apps because many use existing corporate accounts or free tiers of approved services. This makes them invisible to traditional network monitoring.

How do audit logs help reduce risk?

Audit logs reduce risk by providing visibility into who did what, when, and where. This visibility enables IT to investigate security incidents, ensure compliance with data protection regulations, and identify unauthorized access patterns

What are the red flags of unapproved internal software?

Red flags of unapproved internal software include applications that allow unrestricted data access, lack user activity logging, and are deployed without going through standard approval processes.

Should teams use a centralized platform for internal tooling?

Teams should use a centralized platform for internal tooling because it gives IT visibility and lets teams build securely with pre-approved components and policies.

How does Superblocks prevent shadow IT?

Superblocks prevents shadow IT by centralizing app development and access within a governed, auditable platform. It provides features such as role-based access controls (RBAC), comprehensive audit logs, and system-wide visibility.