Why the Future of DLP Is Invisible, Invincible, and Inexpensive

Legacy DLP solutions, as well as CASB and app-native DLP solutions, face significant challenges in providing comprehensive coverage across modern SaaS, AI apps, and endpoints. Lack of visibility, clumsy deployments, and expensive implementations are common drawbacks of using these tools — and they leave big gaps in data loss prevention. 

Even today, we’re still seeing the same problems that have persisted for decades in today’s DLP solutions. Security leader and Nightfall investor Enrique Salem shares some insights into why the first generation of DLP failed to deliver on its promise:

"I think the experience of what was created with the first generation was the right idea with the wrong implementation. The first major issue with DLP 1.0 was false positives and the lack of accuracy. The second challenge was that, given DLP works with unstructured data, users had to write regular expressions every time they wanted to block something. These two operational problems — false positives and excessive maintenance — fundamentally limited the effectiveness of DLP. While we tried to innovate with better algorithms for pattern matching and reduce the reliance on regexes, tuning those algorithms often led to an increase in false positives. We faced a frustrating balance where we wanted to reduce false positives but also needed to lessen the burden on customers. Unfortunately, the solutions we introduced to address one problem often exacerbated the other. Ultimately, that equation just didn't work."

Salem’s framework of the 3 I’s of DLP — invisible, invincible, and inexpensive — is what sets Nightfall apart from existing DLP solutions that rely on regexes and rule-based detectors.

The main problems of legacy DLP

1. Lack of visibility across endpoints, and SaaS, and AI apps

Traditional DLP wasn't built for today's SaaS-based and AI-powered workplace. Sensitive information lives and moves across possibly hundreds of applications with completely different permission and access settings. Security teams have no unified way to see which files are publicly accessible, externally shared, or exposed in AI systems.

Existing DLP solutions like CASB rely on outdated network-based monitoring that fails to capture activity within SaaS applications, leaving blind spots in detecting insider risk.

It’s hard to tell who has access to data, what data they have access to, and why they’re moving it or even have access to it. How can security teams distinguish legitimate workflows from high-risk activity?

2. Reactive security

Unfortunately, security is often seen as a passive exercise, with generic, one-size-fits-all policies and annual employee training sessions. Responding to critical moments when users make decisions that impact sensitive data exposure and malicious data exfiltration by insiders requires much more than reactive security measures.

Sifting through noisy alerts to review risk per incident consumes valuable time and resources, and can even leave exposure risks out in the open or unresolved. 

3. Low confidence 

Many DLP solutions rely on static rules or regexes, which miss important information about how data is moving around environments and who can access and move the data.

Pattern based content inspection with legacy DLP creates floods of false positives when detecting sensitive data. There’s no way to track the content’s origin and destination, or any user activities that happen prior to exfiltration - and that means, there’s no way to prevent exfiltration from happening. Security teams waste hours tuning policies while actual sensitive content slips through undetected: PHI, secrets and credentials, PCI, and PII.

How the 3 I’s add up to stronger DLP

Each of the 3 I’s is a key aspect of data security:

1. Invisible = seamless

DLP should be invisible, meaning it works behind the scenes to provide easy remediation and alerting that makes sense for the security team and end users. Nightfall’s frictionless deployment of seamless, API-based integration into workflows, lightweight agents, and browser plugins provide comprehensive coverage across all exposure and exfiltration threat vectors: SaaS, GenAI apps, and endpoints, with additional visibility into unmanaged devices.

Remediation is built into workflows with real time alerts that allow end users to take action when they see something suspicious, instead of reporting a potential incident to a security team and waiting for something to happen.

2. Invincible = high confidence

False positives and noise are the enemy of good DLP. Nightfall’s AI-powered content inspection and detection goes beyond basic regex and pattern matching for a 95% reduction in false positives compared to traditional DLP. Create custom policies to scan by domain, type of sensitive data, users and user groups, and more. Automated data lineage provides a complete record of all data movement up to the point of data exfiltration or sensitive data exposure.

3. Inexpensive = low total cost of ownership for IT operations

A streamlined security tech stack saves time, and most of all, money. Nightfall’s complete coverage for endpoints and SaaS is simple and flexible, with fast deployment and frictionless operation. Security teams can see full context on data access and movement and triage and remediate incidents within the Nightfall console, Slack, or email alerts.Connecting with infosec platforms are easier than ever: Okta, Entra ID, Google Directory, MDM solutions, and API/SIEM/SOAR integrations all work seamlessly with Nightfall.

The 3 I’s of DLP in action: How Nightfall secures sensitive data for financial services

A financial services firm found employees were downloading customer financial data to do analysis work in unauthorized cloud applications. Compliance violations went undetected for months, eventually leading to steep financial penalties. 

Invisible

The Nightfall agent monitors file uploads, cloud storage sync and clipboard activity with less than 1% CPU and memory usage and no user impact. Nightfall is built on modern endpoint security frameworks that are more stable to eliminate crashes or other compatibility issues with operating systems. Teams can get their work done without the agent slowing down network traffic, while the agent is completely hidden from the GUI experience.

Invincible

The unified console detects all financial data movement across the firm’s endpoints, SaaS, and gen AI apps with AI-powered risk scoring that prioritizes true exfiltration and exposure risks. Nightfall's 100+ pre-trained ML detectors for PII and PCI automatically identify sensitive data in 150+ file types, even in complex embedded documents and archives.

Inexpensive

The firm saves time with Nightfall’s streamlined deployment and begins automated scanning with higher accuracy than other DLP solutions thanks to detectors that scan for both context and content. Security hygiene is also improving thanks to educating employees and providing self-remediation for incidents. Overall, SecOps has less busywork on their plate and can focus their budget and bandwidth on bigger projects. ‍

See Nightfall in action

Nightfall is an all-in-one DLP platform that enables modern organizations to prevent sensitive data exposure and exfiltration risks. It’s a new, AI powered approach that goes beyond traditional DLP. 

Get a demo to learn how to automatically stop sensitive data sharing and exposure like NHIs, PHI, PCI, and PII across SaaS and Gen AI in real time.