Nightfall vs. Cyberhaven

Innovative security teams are switching to Nightfall – the all-in-one data loss prevention platform that increases visibility and lowers overhead.

Four reasons innovators are switching

Comprehensive coverage

Nightfall covers Endpoints, SaaS, and GenAI apps, MCP and AI agents across data in motion and data at rest.

Frictionless deployment and maintenance

Deploy in hours. Nightfall introduces no friction for end-users.

AI-native intelligence

Nightfall is a comprehensive, AI-native solution with both data lineage and LLM powered content classification.

Lower overhead

Nightfall’s automation and remediation capabilities are built for security teams that do more with less. No clunky UX.

"A key gap with Cyberhaven is they lack SaaS integrations. We need more granular tooling and visibility beyond the endpoint alone."

CISO, Tech company

Comprehensive Coverage

No more visibility gaps when data traverses across SaaS.

Nightfall covers SaaS, endpoints, GenAI apps, MCP & AI agents and unmanaged devices - Cyberhaven support is limited on SaaS, MCP & AI agents.
Coverage for data in motion, data at rest, and posture management.

Usable and Lightweight

Eliminate end-user frustrations and complex rollouts.

Deploy in hours - Nightfall’s endpoint agent is extremely lightweight and also has API based coverage.
Nightfall empowers users to prevent breaches with real-time, in-app guidance and self-remediation. Cyberhaven offers limited user engagement and remediation options.

"We recently got Cyberhaven installed, and it adds a constant overhead to any file IO operations. We've found that it really hurts any PC with less than 32 GB of RAM."

IT Operations Admin, Healthcare company

"Cyberhaven's detection has let us down. It has been quite weak and produces tons of false positives, especially for secrets detection."

Director of Information Security, Tech company

AI-Native Intelligence

Marry data lineage and content classification with high accuracy.

Nightfall's AI-driven data lineage tracks sensitive data across SaaS, endpoints, GenAI apps, MCP & AI agents and unmanaged devices. LLM-powered data classification pinpoints sensitive content with high accuracy, allowing for granular policies.
Publicly available technical documentation suggests that certain of Cyberhaven’s content classification workflows may rely on rules-based detection methods.

Lower Overhead

Get more out of the box with Nightfall.

Automate data protection with policies that can take action natively inside of SaaS apps. Cyberhaven's remediation is not granular and it only performs actions on the endpoint.
Nightfall is the #1 rated DLP on G2 in multiple categories, including Fastest Implementation, Best Estimated ROI, and Easiest to Do Business With.

Nightfall vs. Cyberhaven

Features

Nightfall AI

Cyberhaven

DLP Coverage

Nightfall AI

GenAI apps, endpoints, browsers, SaaS apps, MCP and AI agents and unmanaged devices. PaaS and IaaS

Cyberhaven

Vendors built primarily around endpoint protection often find it more difficult to deliver the breadth of coverage that organizations increasingly require across SaaS, AI agents, cloud, and unmanaged environments - many customers find they need to supplement endpoint-first solutions with additional tooling to achieve comprehensive protection.

Data at Rest

Nightfall AI

Coverage across common SaaS

Cyberhaven

Cyberhaven’s data at rest capabilities may be more limited in scope compared to Nightfall’s coverage across common SaaS applications

Automation

Nightfall AI

Real-time remediation in the SaaS app and on the endpoint

Cyberhaven

Cyberhaven’s native remediation capabilities within SaaS applications appear limited compared to Nightfall’s real-time, in-app remediation

Data Lineage

Nightfall AI

Data lineage across SaaS, AI apps, endpoints, MCP and AI agents and unmanaged devices

Cyberhaven

Data lineage across SaaS, endpoints, IaaS and PaaS datastores

Ease of Deployment

Nightfall AI

Lightweight, API-first, lightweight agent deployment with no policies needed to identify risk

Cyberhaven

Agent-first architectures can introduce additional complexity during deployment and ongoing management.

Human Firewall

Nightfall AI

Real-time user coaching and remediation

Cyberhaven

More limited range of real-time coaching and self-remediation options compared to Nightfall’s in-app capabilities

AI-Powered Content Classification

Nightfall AI

Yes, high accuracy detection across PII, PHI, PCI, secrets and credentials and more with pre-trained ML models, LLM based file classifiers and custom entity detectors.

Cyberhaven

Publicly available technical documentation suggests that certain of Cyberhaven’s content classification workflows may rely on rules-based detection methods.

False Positive Reduction

Nightfall AI

Model annotations and end-user feedback improve accuracy over time

Cyberhaven

Cyberhaven’s native ability to annotate false positives appears limited compared to Nightfall’s annotation workflows.

Trustworthy and Reliable

Nightfall AI

Robust security and compliance with trust portal and help center

Cyberhaven

In December 2024, Cyberhaven disclosed a security incident.

Total Cost of Ownership (TCO)

Nightfall AI

All-in-one coverage, ease of use, and automation give time back to your security team.

Cyberhaven

Protecting data shouldn’t mean drowning your security team in alerts which may impact total cost of ownership.

Features

Pros

Cons

Cloud DLP

Shift-left security that detects and protects data at the source, before proliferation and wide disclosure

Does not block data movement.

Network DLP

Inline (in the middle) scanning all web traffic

Compromised end-user privacy as all data is decrypted and scanned, much of which should remain private (e.g. credentials, private keys)

Endpoint DLP

Last line of defense (command and control)

Compromised end-user privacy for anything that should remain private that is on disk (e.g., private keys)

Features

Pros

Cons

Cloud DLP

Real-time and historical data insight with context and granular remediation actions

Limited by cloud provider functionality / API limitations (e.g. download activity data)

Network DLP

Real-time of data in transit on the network

Only data in transit, no insight of historical data

Endpoint DLP

Monitoring at the endpoint for file activity from downloads to removable media

Limited to what is saved on endpoint disk

Features

Pros

Cons

Cloud DLP

Powerful data protection that does not depend on the availability of a device (computer / network) or resources (CPU, memory and bandwidth)

Limited to specific SaaS / Cloud apps

Network DLP

Not limited by endpoint resources

Singular point of failure and bottleneck on the network; adds latency and availability of network and bandwidth

Endpoint DLP

Covers managed endpoints

Limited interoperability with endpoint OS / updates / other agents and highly dependent on endpoint resources (CPU, memory, bandwidth)

Features

Pros

Cons

Cloud DLP

All users and system accounts, APIs and BYODs

Does not cover shadow IT

Network DLP

User and system accounts and sometimes BYOD

API connection data movement is not monitored

Endpoint DLP

All managed endpoints

No coverage of BYOD, API, or third party unmanaged devices

Features

Pros

Cons

Cloud DLP

Business-enabling with no blocking of end-users

Does not block users

Network DLP

Can block users and monitor shadow IT beyond sanctioned apps

Offers blocking only and may break applications with network filtering

Endpoint DLP

Can block user actions

Can block users and will require security intervention.

Features

Pros

Cons

Cloud DLP

Continuously improving high accuracy from machine learning

Network DLP

Regular express and rules-based

Limited complexity due to network requirements for low latency and responsiveness

Endpoint DLP

Regular express and rules-based

Limited complexity due to low latency requirements (CPU, memory) on endpoint

Features

Pros

Cons

Cloud DLP

Real-time coverage in minutes - no agent, device, or network installation or configuration

1-2 weeks of tuning for appropriate insight

Network DLP

Deployment and maintenance is highly expensive, complex and resource intensive

Endpoint DLP

Deployment and maintenance is expensive, complex and resource intensive; re-deployment is required for every new endpoint

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Tracing data movement is not enough.

Data lineage is not enough.

Innovative security teams are switching to Nightfall – the all-in-one data loss prevention platform that increases visibility and lowers overhead.

Comprehensive coverage

Frictionless deployment and maintenance

AI-native intelligence

Lower overhead

Comprehensive Coverage

Usable and Lightweight

AI-Native Intelligence

Lower Overhead

Nightfall vs. Cyberhaven

Security Posture

Depth of insight

Scalability

Coverage

Impact

Accuracy

Total Cost of Ownership (TCO)

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