Tools · Data flow & AI-DLP
AI data loss prevention (DLP) tools
AI data loss prevention (DLP) tools inspect what goes into AI tools and what agents send out: prompts and pastes from employees, agent tool calls and MCP traffic. They classify the data, block, redact or flag anything sensitive before it reaches an outside model or an unapproved tool, and most keep a record for investigation. A team needs one when employees or agents work with customer records, source code or regulated data in AI tools, because a single paste or tool call can send that data to a provider whose retention terms nobody checked.
Data flow & AI-DLP 3
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Harmonic Command (vendor site, opens in a new tab)
generally availableHarmonic Security on the vendor map
Classifies employee and agent AI use by business use case and scores each AI app, including whether the vendor trains on user data. It detects sensitive data about to leave in browser, desktop and MCP-based workflows and intervenes inline with the user or agent.
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Metomic MCP Gateway (vendor site, opens in a new tab)
generally availableSits between AI agents and the tools, databases and models they call, scans the content of each request, and redacts or blocks sensitive data before it reaches an external model or unapproved tool. It also finds shadow AI and keeps an audit trail.
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Nightfall AI Security (vendor site, opens in a new tab)
generally availableClassifies the data moving through agent tool calls, MCP traffic and employee AI use, and blocks sends outside policy while keeping lineage for investigation. It deploys to endpoints through MDM.
Recent launches
- Purview data security on the network with Entra Global Secure Access (Microsoft) · generally available
- Claude Enterprise inference hooks (Anthropic) · beta
- Varonis Agent Intent-Based Access Control · generally available
Announced in the last 90 days. Each launch on New tools links the vendor's own announcement.
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Questions to ask vendors
Neutral questions for a request for proposal (RFP) or a security questionnaire. No product here is named as the answer.
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Does inspection cover agent tool calls and MCP traffic, or only what people type or paste into chat apps?
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How is data classified: fixed patterns, trained classifiers, or both? What false-positive rate do you measure?
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On a hit, can policy block, redact or warn, and can the person or agent carry on with the redacted version?
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Where is inspected content processed and stored, and for how long?
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How is employee privacy handled? Monitoring that reads message content creates its own governance problem.
More questions, grouped by topic: Questions to ask AI agent security vendors.
Related incidents
- SalesBleed flaws in Salesforce Agentforce allowed zero-click data exfiltration and Slack phishing
- CoSnitch flaws let one click pull data out of Microsoft Copilot's connected apps
- Atlassian Rovo could be prompt-injected into sending Jira and Confluence data to attackers
- AI coding agents exposed 13,000 internal images, including billing records, on GitHub
Every record in the AI agent incident database links the sources that reported it.
Missing a product, or found an entry that is out of date? Write to [email protected]. A submission is read, never paid for, and does not guarantee a listing. The glossary defines the terms used here.