--- title: "Secure Gen AI" id: "29933" type: "page" slug: "secure-gen-ai" published_at: "2026-04-10T10:16:29+00:00" modified_at: "2026-07-13T07:36:48+00:00" url: "https://www.kitecyber.com/solutions/secure-gen-ai/" markdown_url: "https://www.kitecyber.com/solutions/secure-gen-ai.md" excerpt: "Secure Gen AI & AI Agents Secure the AI and theagents running on your endpoints GenAI is the fastest-growing data-leak […]" --- - Secure Gen AI & AI Agents # Secure the AI and the agents running on your endpoints **GenAI** is the fastest-growing data-leak channel in your organization — and AI agents take it further. Tools like **Claude Code**, **Copilot**, and **Codex** run directly on your devices with the user’s full privileges: terminal, filesystem, and CLI access. Kitecyber gives you the visibility, detection, and real-time control to use them safely. [Start Free Trial](https://www.kitecyber.com/free-trial-subscription/) [Request A Demo](https://www.kitecyber.com/request-a-demo/) - Discover agents - Detect sensitive data - Block exfiltration [https://www.capterra.in/software/1072155/Kitecyber](https://www.capterra.in/software/1072155/Kitecyber) [https://www.getapp.com/finance-accounting-software/a/kitecyber/](https://www.getapp.com/finance-accounting-software/a/kitecyber/) [https://www.softwareadvice.com/product/524332-Kitecyber/](https://www.softwareadvice.com/product/524332-Kitecyber/) [https://www.g2.com/products/kitecyber/reviews/kitecyber-review-11297499](https://www.g2.com/products/kitecyber/reviews/kitecyber-review-11297499) ## Trusted by Renowned Customers & Partners - The Reality ## GenAI is expanding your attack surface right now Employees use ChatGPT, Gemini, Copilot, and dozens of other AI tools every day — some sanctioned, many not. In nearly every session, sensitive data moves in ways your security team cannot see. Now AI agents add a new dimension: they don’t just receive prompts, they act on the endpoint. - AI Agents on the Endpoint ## Agents run with your users’ full privileges An AI agent on a laptop inherits the signed-in user’s access. It can read and write files, run shell commands, call CLIs and APIs, and reach internal systems — faster than any human, and usually invisibly to network-centric tools. - Terminal & shell - Filesystem read / write - CLI & automation - Credentials & tokens - SaaS & APIs ### Sensitive data in prompts & uploads Customer records, source code, and secrets get pasted into prompts or read by an agent — and leave before anyone realizes they should have been blocked. ### No visibility into agent activity Without endpoint-level insight, teams don’t know which agents run where, what they touch, or where their output goes. ### Prompt injection turns agents hostile A poisoned web page or document can hijack an agent into exfiltrating data or running unintended actions on connected systems. - Product Features ## How Kitecyber secures GenAI & AI agents Endpoint-first visibility and real-time control over how data moves across endpoints, SaaS, and GenAI tools — with the product screens to match. - Discover ## Endpoint-first AI & agent discovery Kitecyber’s endpoint agent surfaces every AI application and agent accessed from a managed device — browser tools, desktop apps, CLIs, and embedded AI features — so shadow and unsanctioned usage no longer hides. - ACCESS VISIBILITY ## See what each agent can reach Because Kitecyber lives on the endpoint, it sees the same terminal, filesystem, CLI, and network access your agents do — giving you a clear picture of exactly what an agent can touch. - DATA LINEAGE ## Track data across prompts & files Follow how data moves from its origin through to GenAI interactions, with a clear record of what was shared, when, by whom, and through which agent or tool. - REAL-TIME CONTROL ## Block uploads & risky prompts in real time When a user or agent tries to upload a classified document or send sensitive data into a prompt, Kitecyber intercepts the action and applies policy — block, warn, or log — before it leaves the device. - GOVERNANCE ## Context-aware policy & compliance Apply guardrails that adapt to the user, device, [data classification](https://www.kitecyber.com/glossary/data-classification/) , and AI tool in use, and keep an audit-ready record mapped to SOC 2, ISO 27001, GDPR, and HIPAA. - UNIFIED DLP ## One policy across endpoint, SaaS & GenAI Instead of separate tools for [endpoint DLP](https://www.kitecyber.com/glossary/endpoint-dlp/) , [cloud security](https://www.kitecyber.com/glossary/cloud-security/) , and AI monitoring, manage one policy with consistent enforcement across every data channel. - Why Traditional Tools Fall Short ## Legacy stacks weren’t built for GenAI or agents ### No prompt-level visibility Traditional DLP inspects files and email. It was never built to inspect conversational prompts or watch an agent act on the endpoint in real time. ### Fragmented endpoint & cloud tools When [endpoint security](https://www.kitecyber.com/glossary/endpoint-security/) , CASBs, and web filters run as separate consoles, agent-driven leaks fall through the gaps between them. ### Detection comes too late Log analysis and periodic review find leaks after the data has already reached an external model. Real-time prevention needs a different architecture. - Benefits ## Use AI productively, without losing control ### Real-time protection Catch exposure at the moment of interaction, not hours later. ### Less data-leak risk Consistent policy across every AI tool cuts incidents and investigations. ### Simpler operations One platform instead of three or four reduces alert fatigue and training. ### Better compliance Audit-ready logging and documentation for your AI governance posture. 1 ### Discover The endpoint agent inventories every AI agent and the skills it loads. 2 ### Analyze Connections, SaaS reach, and skill files are analyzed for risk and data exposure. 3 ### Detect Sensitive-data access and movement by each agent is flagged in real time. 4 ### Enforce Policies block risky exfiltration and capture an audit trail for compliance. - Get Started ## Take control of GenAI & agent data risk The goal isn’t to block AI — it’s to use it safely. See exactly which agents run on your endpoints, what data they touch, and stop unapproved transfers before they leave the device. [Request A Demo](https://www.kitecyber.com/request-a-demo/) [Start Free Trial](https://www.kitecyber.com/free-trial-subscription/) ## FAQ's ## Frequently asked questions [What is Secure Gen AI?](#collapse-63098cb6a56ac5d923a5) Secure Gen AI refers to the controls, policies, and technologies that prevent unauthorized data exposure when employees and systems interact with generative AI tools. It includes prompt inspection, data loss prevention, [access control](https://www.kitecyber.com/glossary/access-control/) , and usage monitoring across both sanctioned and unsanctioned AI applications. [What are the biggest Gen AI security risks?](#collapse-96023976a56ac5d923a5) The primary risks are data leakage through prompts and file uploads, shadow AI usage by employees, prompt injection attacks, and AI agents with excessive system access. Each of these can result in sensitive data being exposed to third-party systems without authorization. [How does data leakage happen through Gen AI tools?](#collapse-31e476f6a56ac5d923a5) Data leakage occurs when employees enter sensitive information into AI prompts or upload confidential files to AI platforms. Many Gen AI tools retain this data for model training or store it in ways that fall outside your organization's data governance controls. [What is prompt injection?](#collapse-a8ee7786a56ac5d923a5) Prompt injection is an attack technique where malicious instructions are embedded in content that an AI model processes. These instructions can manipulate the model into revealing data, bypassing controls, or taking unintended actions on connected systems. [How common is sensitive data in Gen AI prompts?](#collapse-fba6d7f6a56ac5d923a5) According to Harmonic's 2025 research, approximately 4.37% of all Gen AI prompts contain sensitive data, and nearly 22% of uploaded files contain confidential information. Check Point's 2025 research found that 1 in 35 prompts carries a high data leakage risk. [What is shadow AI and why is it a security risk?](#collapse-62ed51b6a56ac5d923a5) Shadow AI refers to the use of AI tools by employees without formal approval or security review. It is a risk because security teams have no visibility into what data is being shared, which tools are in use, or whether those tools meet your organization's data handling requirements. Proofpoint found that 44% of organizations currently lack this visibility. [What are Gen AI security best practices?](#collapse-39b10286a56ac5d923a5) The core practices are restricting sensitive data sharing, implementing automated [data classification](https://www.kitecyber.com/glossary/data-classification/) , monitoring and logging AI interactions, controlling access to AI tools based on role, and providing employees with regular training on AI-related risks. [How does Kitecyber help secure Gen AI usage?](#collapse-c0e2c2c6a56ac5d923a5) Kitecyber may provide endpoint-first visibility into AI tool usage, real-time prompt inspection, [data lineage](https://www.kitecyber.com/glossary/data-lineage/) tracking, and unified DLP policy enforcement across endpoints, SaaS platforms, and Gen AI tools. This could give security teams a single platform to manage AI data risk without deploying multiple separate products. [Can Kitecyber help with AI compliance requirements?](#collapse-25fb42b6a56ac5d923a5) Kitecyber is designed to support compliance with data protection frameworks including GDPR, HIPAA, and CCPA by providing audit-ready logging of AI interactions, policy documentation, and demonstrable controls over how sensitive data is handled in AI environments. [Why do traditional DLP tools fall short for Gen AI?](#collapse-8ff1f3e6a56ac5d923a5) Traditional DLP tools were designed to inspect files, emails, and structured data transfers. They were not built to analyze conversational inputs, monitor real-time AI interactions, or enforce policy at the prompt level. This creates coverage gaps specifically in the Gen AI layer where much of today's data leakage is occurring.