Nightfall AI
AI-native DLP platform to control data across AI agents, MCP servers, endpoints, and SaaS.
For enterprises running AI agents or MCP servers, Nightfall is the DLP that covers those vectors natively at 95% precision. The Claude Compliance API integration and autonomous Nyx analyst give it a unique edge. Pricing is not public and requires a demo, so it's for security teams with dedicated budget, not small startups.
Verified 2h ago · liveness 78/100 · cite: rightaichoice.com/tools/nightfall-ai
- Security teams in healthcare, fintech, legal, manufacturing needing AI-native DLP
- Organizations deploying AI agents and MCP servers requiring granular data access control
- Teams overwhelmed by legacy DLP false positives seeking >90% detection accuracy
- Enterprises wanting to enable Shadow AI safely with real-time blocking and coaching
- Fully air-gapped, on-premises environments with no SaaS or AI tool usage
- Small teams with limited budget and no dedicated SecOps (pricing is enterprise-grade)
- Organizations needing a simple endpoint DLP without AI/agent coverage
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Skip Nightfall AI if you have no AI agent or MCP server usage, if you need a simple endpoint-only DLP, or if you're a small team without a dedicated security budget—pricing is enterprise-grade and requires a sales conversation.
Data Discovery and Classification add-on is billed per TB per year (1TB, 3TB, 5TB, 20TB packs) after a 150GB included allowance—going over can add thousands to your bill.
Nightfall's pricing is not public, but it's enterprise-grade, fitting mid-market and Fortune 500 companies with dedicated security budgets. Compared to legacy DLP like Microsoft Purview or Palo Alto Networks, Nightfall offers native AI agent coverage and higher precision, justifying a premium for AI-forward orgs. For small teams, cheaper alternatives like Satori or data security posture management tools might be more budget-friendly.
In short
Nightfall AI — AI-native DLP platform to control data across AI agents, MCP servers, endpoints, and SaaS. Best for Security teams in healthcare, fintech, legal, manufacturing needing AI-native DLP, Organizations deploying AI agents and MCP servers requiring granular data access control, Teams overwhelmed by legacy DLP false positives seeking >90% detection accuracy. Contact Sales pricing.
Viability Score
How well maintained and how widely used is Nightfall AI? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: August 2026
How we score →Key Features
- AI-based content classification with 95% precision
- Data lineage tracking from source to destination
- Shadow AI prevention for ChatGPT, Copilot, Gemini, Claude, Deepseek, Perplexity, Grok
- Hook-level interception for AI agents (prompts, MCP tool calls, tool responses, shell)
- MCP server discovery, inventory, and shadow-MCP detection
- Prompt injection blocking for agentic AI
- Automated remediation for 80% of incidents
- Real-time scanning and auto-quarantine in Slack
- PHI/PCI/PII blocking in outbound Gmail and endpoints
- Employee coaching with real-time violation alerts
- Browser plugins for Chrome, Firefox, Edge, Safari
- Nyx autonomous DLP analyst for threat investigation
- LLM-based file classifiers for documents and source code
- Claude Compliance API integration
- Revoke inappropriate data access in SaaS
About Nightfall AI
Nightfall AI is an AI-native data loss prevention (DLP) platform that gives security teams real-time visibility and control over sensitive data as it moves across modern vectors: AI agents, MCP servers, endpoints, and SaaS. Built for the era of agentic AI, it addresses what legacy DLP can't see—AI apps as exfiltration vectors, agents acting without human involvement, and data movement that lacks business context. Unlike traditional pattern-matching tools that achieve only 5-25% accuracy, Nightfall uses 100+ AI-based detectors, LLM-based file classifiers, and computer vision models to deliver 95% detection precision out of the box, slashing false positives and alert fatigue. Core products include Data Exfiltration Prevention, Data Detection & Response, Data Discovery & Classification, and Nyx, an autonomous DLP analyst that sees, reasons, and acts on threats. Nightfall also provides MCP & AI Agent Security, which intercepts at the hook level to block prompt injections and exfiltration via MCP tool calls. Coverage spans Shadow AI apps like ChatGPT, Copilot, Gemini, and Claude, plus endpoints, browsers, email, and over a dozen SaaS integrations deployable via API in hours. With data lineage tracking, Nightfall reconstructs the full journey of a file—even if renamed or synced to a personal account—to catch sophisticated exfiltration. Automated remediation handles 80% of incidents, and employee coaching features provide real-time violation alerts with the option to submit business justifications. The platform integrates with Claude's Compliance API for enterprise conversation monitoring. Nightfall is positioned as the AI-native replacement for legacy DLP in regulated industries like healthcare, finance, legal, and manufacturing. Compared to Microsoft Purview or Palo Alto Networks, it offers native coverage of AI agent and MCP vectors, plus higher detection precision, making it the better fit for organizations prioritizing AI adoption without sacrificing security.
Behind the Verdict
Nightfall is the DLP to reach for when your data is moving through AI agents and MCP servers, not just email and endpoints. The hook-level interception on Cursor, Claude Code, and VS Code is something legacy DLP simply doesn't have, and the local and remote MCP discovery plus shadow-MCP detection fills a real gap. If you're rolling out Claude Enterprise or Cowork, the Compliance API integration is a differentiator—it gives you audit and enforcement on conversations and files that other tools can't see. But Nightfall isn't for everyone. The pricing is custom and enterprise-grade, so small teams without a dedicated SecOps budget will find cheaper, simpler alternatives. If your stack is entirely on-prem and air-gapped, Nightfall's SaaS-centric approach won't fit. And if you already have a mature Microsoft Purview deployment and no AI agent usage, the lift may not be worth it. Compared to Microsoft Purview, Nightfall is more precise out of the box (95% vs 5-25% accuracy for legacy tools), but Purview is bundled with Microsoft 365 and might be 'good enough' for some. Nightfall's advantage is native AI agent and MCP coverage, which Purview lacks. Palo Alto Networks has DLP too, but it's not AI-agent native. The real trade-off is speed of deployment versus cost: Nightfall can be live in hours, but you pay for that agility. Where it bites: the pricing page lists packages but not dollar amounts—you have to schedule a demo to get a quote. That's a friction point for buyers who want to compare ahead of a sales call. Also, LLM model responses are monitor-only, not blocked, so you have to weigh that gap. In practice, Nightfall is a strong pick for regulated industries (healthcare, finance, legal) that need to enable AI safely without drowning in false positives. If you have the
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Real-world workflow fit
Concrete scenarios for the personas Nightfall AI actually fits — and what changes day-one when you adopt it.
A customer reports a potential data leak. The analyst needs to detect if sensitive financial data has been exposed via AI apps like ChatGPT.
Outcome: Nightfall's Shadow AI Prevention blocks the upload of financial forecasts to ChatGPT, prompts the user for justification, and logs the incident with full lineage for compliance reporting.
The CISO wants to ensure PHI is not leaked through email or cloud storage to maintain HIPAA compliance.
Outcome: Nightfall's Data Detection & Response auto-redacts PHI in outbound Gmail, blocks it before delivery, and provides employee coaching with real-time alerts, reducing breach risk and alert fatigue.
The team uses AI coding assistants like Claude Code. The engineer needs to prevent secrets from being exfiltrated via MCP servers.
Outcome: Nightfall's AI Agent Security hooks intercept MCP tool calls, block exfiltration attempts, and inventory local MCP servers, with OpenTelemetry audit trails for Claude Code sessions.
Use Cases
- Prevent secrets and credentials from leaking in Slack messages or GitHub commits.
- Auto-redact PHI in Gmail or Google Drive to maintain HIPAA compliance.
- Block intellectual property from being uploaded to unauthorized AI apps like ChatGPT.
- Revoke over-permissioned sharing of sensitive files in Google Drive and OneDrive.
- Monitor and block data exfiltration via USB drives, clipboard, print on managed endpoints.
- Investigate data exfiltration incidents using Nyx autonomous analyst with full lineage.
- Secure AI agent tool calls to Salesforce, preventing data exposure through MCP servers.
- Detect and block prompt injection attacks targeting Claude and other agentic AI.
Models Under the Hood
as of 2026-08-15
Limitations
- Pricing is not publicly listed; you must contact sales for a custom quote.
- AI agent security hooks for Cursor, Claude Code (IDE and CLI), and VS Code are available on macOS and Windows only.
- In AI agent hooks, LLM model responses are monitor-only—Nightfall can block prompts and tool calls but not the response content.
- Data Discovery and Classification add-on costs extra per TB, which can increase total cost for large data volumes.
- The platform requires integration work, though API-based SaaS deployments can be done in hours.
- It is not designed for fully on-premises, air-gapped environments.
as of 2026-08-15
Verification history
We have re-verified Nightfall AI 17 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
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Where the pricing makes sense
The company stage and team size where Nightfall AI's pricing actually pencils out — and where peers do it cheaper.
Nightfall's pricing is not public, but it's enterprise-grade, fitting mid-market and Fortune 500 companies with dedicated security budgets. Compared to legacy DLP like Microsoft Purview or Palo Alto Networks, Nightfall offers native AI agent coverage and higher precision, justifying a premium for AI-forward orgs. For small teams, cheaper alternatives like Satori or data security posture management tools might be more budget-friendly.
Setup time & first value
How long it actually takes to get something useful out of Nightfall AI — broken out by persona, not the marketing-page minute.
For SaaS integrations like Slack, Google Drive, and Gmail, you can be up and running within hours via API. Endpoint agents and browser plugins deploy quickly via Jamf or Intune. AI agent hooks require configuration but can be active in a day. Full-scale deployment with Data Discovery scanning may take a few days to index all data.
Switching to or from Nightfall AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Microsoft Purview: Export existing DLP policies and rules, run a parallel deployment using Nightfall's API to map detection categories, then switch enforcement gradually.
- ↗To Microsoft Purview: Export Nightfall detection logs and policies, manually recreate rules in Purview, and run a transition period with both tools active.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Nightfall AI
Common stack mates teams adopt alongside Nightfall AI, with the specific reason each pairing earns its keep.
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Cyberhaven
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Alternatives to Nightfall AI
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Runtime data security for AI agents and SaaS apps — block, mask, and restrict in real time.
Veza
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Cyberhaven
AI-native data security platform for the agentic enterprise, with DSPM, DLP, and IRM.
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