Nightfall vs. Forcepoint

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 across both data in motion and data at rest.

Frictionless deployment and maintenance

Deploy in hours, not weeks. Nightfall introduces no friction for end-users.

AI-native intelligence

Nightfall is the only 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.

"Forcepoint's SaaS version is missing features and doesn't meet our requirements.
The on-prem versions requires us to setup and manage the infrastructure, which means significant cost and effort for us."

Director of Information Security, Tech company

Comprehensive Coverage

No more visibility gaps when data traverses across SaaS.

Nightfall covers SaaS, endpoints, GenAI apps, and unmanaged devices — Forcepoint’s coverage is rooted in older on-prem deployments and limited in SaaS contexts.
Coverage for data in motion, data at rest, and posture management - Forcepoint’s detection is heavily reliant on scanning traffic, missing deeper SaaS data at rest.

Usable and Lightweight

Eliminate end-user frustrations and complex rollouts.

Deploy in hours, not weeks — Nightfall is primarily API-native and our agent is extremely lightweight. Forcepoint’s legacy on-prem infrastructure adds operational overhead and maintenance, and it slows adoption.
Nightfall empowers users to prevent breaches with real-time, in-app guidance. Forcepoint offers limited user engagement and remediation options.

"The issue is that Forcepoint is not user-friendly. It is not easy to use. They need to redesign the interface."

IT Security Engineer, Tech company

"We recently moved off Forcepoint because the overhead and noise rates were too high. The solution was worse than the problem it tried to solve."

CISO, Financial services

AI-Native Intelligence

Marry data lineage and content classification with high accuracy.

Nightfall's AI-driven data lineage tracks sensitive data across SaaS, endpoints, and unmanaged devices. Forcepoint’s reliance on static content scanning is prone to high false positives and lacks the context to remediate sophisticated risks.
LLM-powered data classification pinpoints sensitive content with high accuracy, allowing for granular policies.

Lower Overhead

Get more out of the box with Nightfall.

Automate data protection with policies that can take action natively inside of SaaS apps. Forcepoint’s workflows are limited by legacy rules and on-premises infrastructure.
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. Forcepoint

Features

Nightfall AI

Forcepoint

DLP Coverage

Nightfall AI

SaaS, email, endpoints, GenAI apps, and unmanaged devices

Forcepoint

Primarily on-premises, endpoints, web, email

Data at Rest

Nightfall AI

Coverage across common SaaS

Forcepoint

Limited and fragmented

Automation

Nightfall AI

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

Forcepoint

Relies on manual or limited policy actions

Data Lineage

Nightfall AI

Data lineage across SaaS, endpoints, and unmanaged devices

Forcepoint

No true data lineage – focuses on file/content only

Ease of Deployment

Nightfall AI

Lightweight, API-first, fast deployment

Forcepoint

Multi-console, on-prem infrastructure, complex setup

Human Firewall

Nightfall AI

Real-time user coaching and remediation

Forcepoint

Lacks robust user-engagement features

AI-Powered Content Classification

Nightfall AI

Yes, high accuracy detection across PII, PHI, PCI, secrets and credentials and more powered by LLMs, with comprehensive file type support

Forcepoint

No, limited context and rules-based scanning approach

False Positive Reduction

Nightfall AI

Model annotations and end-user feedback improve accuracy over time

Forcepoint

High false positives due to content-only detection

Robust Support & Partnership

Nightfall AI

Dedicated customer success and product operations teams committed to your success

Forcepoint

Acquired by private equity (TPG), so expect price increases and slowed innovation

Total Cost of Ownership (TCO)

Nightfall AI

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

Forcepoint

Security team needs to invest more time in tuning and investigating alerts.

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

Schedule a live demo

Speak to a DLP expert. Learn the platform in under an hour, and protect your data in less than a day.

Legacy DLP 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. Forcepoint

Security Posture

Depth of insight

Scalability

Coverage

Impact

Accuracy

Total Cost of Ownership (TCO)

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