ShadowLock

ShadowLock is a comprehensive shadow AI detection and governance platform purpose-built for Managed Service Providers (MSPs) and internal IT teams. It addresses the rapidly growing risk of employees using unapproved artificial intelligence tools with sensitive corporate data, often without any visibility or control from the organization. According to Gartner (2025), 69% of organizations suspect employees are using prohibited AI, while Salesforce reports that over 50% of AI use at work happens without employer approval. ShadowLock provides real-time visibility and policy enforcement across the entire AI attack surface, covering critical blind spots that traditional managed-device controls miss entirely. These blind spots include browser-based AI extensions, desktop AI applications, locally running large language models (LLMs) like Ollama and LM Studio, and personal accounts on public AI chatbots such as ChatGPT, Claude, and Gemini. The platform operates through three integrated layers: a silently deployed Windows endpoint agent, a self-configuring browser enforcement extension, and a Microsoft 365 AI app detection scanner. A centralized, multi-tenant dashboard allows MSPs to audit, block, or govern AI activity across every client organization from a single pane of glass, complete with audit-ready compliance reports. ShadowLock is private by design, featuring no keystroke logging and zero transmission of actual content, ensuring organizations can govern AI use without compromising employee privacy or creating additional data liability.

Multi-Layered Detection and Enforcement

ShadowLock provides comprehensive coverage across the three primary vectors of shadow AI use. The Windows endpoint agent deploys silently via existing RMM tools, monitors AI activity, scans for installed browser extensions, detects local AI desktop applications, and locks down AI features built into Chromium-based browsers. The browser enforcement layer self-configures once the agent is installed, intercepting pastes, file uploads, and sensitive data typed directly into prompts. It enforces data-sharing opt-out settings on each AI tool and applies organizational policies with clear, user-facing messages. The Microsoft 365 scanner connects to tenant environments to detect and report on AI app integrations activated without security review.

Real-Time Sensitive Data Interception

The browser extension actively intercepts and classifies risky data being submitted to AI tools before it leaves the endpoint. When an employee attempts to paste customer records, credentials, confidential documents, or protected health information into a public AI chatbot, the extension evaluates the content against policy rules. It can block the submission entirely, warn the user, or allow it with audit logging. This proactive interception prevents data exfiltration at the point of action, rather than relying on after-the-fact log analysis. The system classifies over 100 different AI tools, services, and desktop applications, with the library continuously growing.

Silent RMM-Based Deployment

ShadowLock is designed for MSP operational efficiency, deploying to Windows endpoints silently through existing Remote Monitoring and Management (RMM) tools without requiring any user interaction or dedicated security engineering resources. The agent installs without disrupting end-user workflows or requiring reboots. Once deployed, it self-configures the browser enforcement layer automatically. This zero-touch deployment model is critical for MSPs managing hundreds or thousands of endpoints across multiple client organizations, enabling rapid scaling of AI governance without per-device manual configuration or complex rollout procedures.

Multi-Tenant Governance Dashboard

The centralized, multi-tenant dashboard provides MSPs and IT teams with unified visibility and control over AI activity across every client organization from a single interface. Administrators can view real-time AI usage statistics, identify which tools are being used and by whom, and drill down into specific incidents. Policy controls allow for granular configuration of which AI tools are permitted, which data types trigger blocks, and how violations are handled per client or user group. The dashboard generates audit-ready compliance reports suitable for HIPAA, GDPR, CCPA, and other regulatory frameworks, providing defensible evidence of governance controls.

Healthcare HIPAA Compliance Enforcement

Healthcare organizations and their MSPs face significant risk when employees paste protected health information (ePHI) into public AI chatbots like ChatGPT or Claude without a Business Associate Agreement (BAA) in place. ShadowLock detects and blocks the submission of patient data, medical records, and clinical information to unapproved AI tools. The platform provides audit trails demonstrating proactive controls, which is critical for HIPAA compliance and breach notification avoidance. This use case is particularly vital for medical practices, hospitals, and healthcare IT providers managing multiple covered entities.

MSP Client Risk Mitigation

MSPs face growing liability exposure when client organizations experience AI-related data incidents. If a client suffers a data breach through unauthorized AI use and the MSP had endpoint management scope, the question becomes whether the MSP should have known and prevented the activity. ShadowLock provides MSPs with the tools to demonstrate due diligence across all managed clients. The multi-tenant dashboard enables proactive monitoring, policy enforcement, and audit-ready reporting that protects both the client and the MSP from legal and reputational damage.

Intellectual Property Protection

Organizations handling proprietary source code, trade secrets, product plans, and confidential contracts face substantial IP risk when employees submit this material to public AI tools. Failing to control access to trade secrets through AI submissions can weaken legal protections and IP rights. ShadowLock intercepts and classifies submissions of source code, legal documents, financial data, and product specifications to AI coding assistants like GitHub Copilot and Cursor, as well as general-purpose chatbots. This prevents inadvertent exposure of competitive intellectual property and maintains legal defensibility of trade secret protections.

GDPR and Privacy Framework Compliance

Organizations operating under GDPR, CCPA, or other privacy frameworks must ensure that customer personal identifiable information (PII) is not processed through unapproved vendors. When employees use personal accounts on AI tools, there is no Data Processing Agreement (DPA), no lawful basis for processing, and no compliant transfer mechanism for cross-border data flows. ShadowLock detects and blocks the submission of customer PII to unauthorized AI tools, providing the governance controls necessary to demonstrate compliance with data protection regulations and avoid regulatory fines.

How does ShadowLock protect employee privacy while monitoring AI usage?

ShadowLock is private by design and does not perform keystroke logging or transmit the actual content of employee interactions. The browser extension and endpoint agent classify data being submitted to AI tools based on content patterns and policies, but the actual content is never sent to ShadowLock servers. Only metadata about the event, such as which tool was used, the data classification, and the policy action taken, is logged for audit purposes. This approach provides governance without creating a new privacy liability or monitoring employee communications.

Can ShadowLock be deployed without disrupting existing endpoint management?

Yes, ShadowLock is designed for seamless deployment through existing RMM tools without requiring dedicated security engineering resources. The Windows agent deploys silently, installs without requiring user interaction or system reboots, and self-configures the browser enforcement layer automatically. The agent integrates with standard RMM platforms used by MSPs, enabling rapid scaling across hundreds or thousands of endpoints with minimal operational overhead. There is no need for changes to existing endpoint security stacks or network infrastructure.

What types of AI tools and applications does ShadowLock detect and govern?

ShadowLock detects and governs over 100 AI tools, services, and desktop applications, with the library continuously expanding. This includes public AI chatbots (ChatGPT, Claude, Gemini), AI browser extensions (sidebar assistants, email rewriters), desktop AI apps (Claude Desktop, ChatGPT app, Ollama, LM Studio), AI coding assistants (GitHub Copilot, Cursor), embedded SaaS AI features (Microsoft Copilot, AI writing tools), and meeting transcription AI (Otter.ai, Fireflies). The platform also detects AI features built into Chromium-based browsers like Chrome, Edge, Brave, and Firefox.

Does ShadowLock work for organizations using Microsoft 365 and cloud-based AI tools?

Yes, ShadowLock includes a dedicated Microsoft 365 AI app detection scanner that connects to tenant environments to identify and report on AI integrations activated within the Microsoft ecosystem. This covers AI features embedded in approved SaaS applications, such as Copilot in Microsoft 365 apps, as well as third-party AI app integrations that users may have authorized through their Microsoft accounts. The scanner provides visibility into AI usage that occurs entirely within cloud applications, complementing the endpoint and browser-based detection layers.