Nightfall AI vs. Virtru

Why is it important to secure sensitive data in the modern enterprise?

In today's rapidly evolving digital landscape, securing sensitive data has become imperative for modern enterprises. The stakes are higher than ever due to several key factors:

• Proliferation of sensitive data across platforms: With the widespread adoption of cloud-based apps, sensitive data—including Personally Identifiable Information (PII), Payment Card Industry (PCI) data, Protected Health Information (PHI), secrets, and Intellectual Property (IP)—is all too easily sprawled across multiple platforms. This includes SaaS applications, Generative AI (GenAI) apps, email, and endpoints, all of which significantly expand the potential attack surface.
• Escalating financial risks: The cost of data breaches has skyrocketed. According to IBM, a single leaked secret can cost organizations an average of $4.88 million. This financial impact extends beyond immediate losses to include regulatory fines, legal fees, and long-term reputational damage.
• Regulatory compliance mandates: With stringent data protection regulations such as ISO 27001, HIPAA, and PCI-DSS, organizations face increasing pressure to ensure continuous compliance or risk severe penalties and loss of customer trust. 
• Evolving threats: As cyber threats become more sophisticated, the risk of both external attacks and insider threats has intensified, necessitating robust protection mechanisms.‍
• Trust and reputation: In an era where data breaches make major headlines, it’s paramount to maintain customer trust and corporate reputation. A single data leak can erode years of built-up trust and severely impact an organization's market position.

To address these critical challenges, data security solutions with data leak prevention (DLP) features have emerged as a vital component of enterprise security strategies. An effective data security program should cover data security across multiple dimensions, including the following. 

1. Data Detection and Response: Proactively identify and prevent the sprawl of sensitive data across communication and collaboration platforms. 
2. Data Security Posture Management: Mitigate risks associated with improper sharing or permission settings.
3. Data Exfiltration Prevention: Defend your data against both inadvertent leaks and insider threats.
4. Data Encryption: Enable secure data sharing through automated, context-aware encryption.‍
5. Data Discovery and Classification: Scan historical data at rest and automatically remediate sensitive data.

In today’s increasingly complex digital ecosystem, securing sensitive data isn’t an option—it's a necessity. For modern businesses who are aiming to protect their “crown jewels,” maintain compliance, and safeguard their reputation, it’s imperative to implement a robust data security solution that covers SaaS apps, GenAI apps, email, and endpoints.

How do I choose the right data security solution to protect my sensitive data from leakage and exfiltration?

When selecting a data security tool for DLP, several key criteria should guide your decision:

1. Detection platform: Evaluate the accuracy and sophistication of the solution's detection capabilities, including its ability to identify sensitive data across various formats and contexts.
2. Comprehensive coverage: Ensure the tool protects data across all relevant platforms, including SaaS apps and GenAI apps as well as email and endpoints. 
3. Ease of use: Consider the solution's user experience and how easily it can be deployed and managed by your team on a daily basis.
4. Automated data protection: Look for features that automate remediation actions to reduce manual workload and improve response times.
5. API-driven cloud architecture: Prioritize solutions built on modern, scalable cloud infrastructures that can seamlessly integrate with your existing platforms.
6. Human-centric approach: Choose a tool that balances robust protection with user productivity in order to minimize false positives and unnecessary friction.
7. Security workflow integration: Assess how well the solution integrates with your existing SIEM/SOAR tools, as well as if it can enable a unified response strategy.‍
8. Total cost of ownership: Consider not just the initial price, but also ongoing costs like maintenance, updates, and potential scalability.

Let's examine how Nightfall AI and Virtru measure up against these critical factors to help you make an informed decision for your organization's data security needs.

How does Nightfall compare to Virtru?

Detection platform

Nightfall AI

• Deploys state-of-the-art ML-trained detectors in discovering PII, PCI, PHI, passwords, API keys, and intellectual property (IP) with high precision and recall, ensuring minimal noise and fewer missed detections.
• Detects sensitive data in 50+ file types, including docs, images, spreadsheets, HTML, PDFs, logs, images, and zip archives.
• Leverages columnar information in spreadsheets and CSVs for improved accuracy.
• Utilizes a sophisticated combination of PII and medical entity detection models, enhanced with GenAI, to accurately detect PHI and minimize noisy alerts.

Virtru

• Limited customization for detection rules, as well as difficulties with fine-tuning detection criteria for specific organizational needs.
• Non-sensitive content is often flagged, creating a high number of false positives that require manual intervention and disrupt productivity.
• Legacy detection capabilities are rule-based, often missing contextual nuances.
• Detection accuracy varies, especially with non-standard file formats like images and archive files.

Comprehensive coverage

Nightfall AI

• Offers comprehensive use case and platform coverage for SaaS, GenAI, email, and endpoints. 
• Supports 5 use cases: 
  1. Prevent secret sprawl: Detect and remediate secrets, passwords, and credentials that are shared or exposed in insecure locations like Slack or GitHub.
  2. Safeguard personal information: Pinpoint PII, PCI, and PHI with high accuracy to maintain compliance and keep personal data safe and private.
  3. Prevent data exfiltration: See the full lineage of sensitive data that’s inadvertently or maliciously moved out of a company environment, and take immediate action.
  4. Secure AI usage: Maintain data privacy by safeguarding sensitive data from use in homegrown and third party AI apps. 
  5. Encrypt sensitive data automatically: Encrypt sensitive data in outbound communications and at-rest applications in order to protect corporate data.
• Provides broad security coverage of business-critical SaaS applications, including M365 Teams, OneDrive, Slack, Jira, Confluence, Zendesk, Salesforce, GitHub, Google Workspace, and more.
• Has a unified workflow across SaaS and GenAI apps, as well as cloud email systems and endpoints. 
• Offers several robust administrative controls like setting expiration dates and blocking email forwarding; supports keyword-based encryption, with full visibility of encryption events in the console.

Virtru

• Coverage is limited to email, with very limited coverage for SaaS apps.
• Strong integration with Gmail and Microsoft Exchange Online, but no support for use cases such as data exfiltration, data security posture management (DSPM), or data classification on SaaS apps or endpoints.
• Focuses on data in transit, with a lack of any “reflection mode” functionality  for protecting email data in mailboxes or other SaaS apps.

Ease of use

Nightfall AI

• Intuitive and user-friendly interface with encryption options directly embedded within the Gmail UI. 
• Simple policy creation and management, with options to manage tailored policies by users, user groups, teams, and more.
• Quick and easy setup process to integrate with SaaS apps in minutes.
• Clear and actionable alerts via Slack, Teams, email, or enterprise systems via Webhooks.

Virtru

• Initial configuration process is time-consuming and requires technical expertise.
• Administrators report a steep learning curve in navigating and efficiently using the management interface.
• Process of managing encryption keys and access rights is cumbersome, particularly for external collaborators with the gateway-based deployment.
• Frequent need for re-authentication and reloading, causing disruptions to end-user workflow.

Automated data protection

Nightfall AI

• Flexible remediation options including automated, manual, and employee remediation (with Human Firewall). 
• Automated, policy-driven encryption considers the full context of the email in addition to presence of sensitive content. 
• End-user remediation and inline coaching automates incident response and nurtures a secure-by-design culture across organizations.
• Immediate, real-time, and delayed remediation actions are fully customizable by SaaS apps, endpoints, and GenAI apps.

Virtru

• Fewer options for automatic threat response compared to competitors.
• Users report a lag between policy creation and its effective implementation across the system.
• Absence of complex, condition-based automated workflows for sophisticated protection scenarios.
• Users frequently mention the need for manual checks and actions, which reduce overall efficiency.

API-driven cloud architecture

Nightfall AI

• API-first, enterprise-scale architecture integrates easily with SaaS apps, GenAI apps, and endpoints. 
• No impact to source apps with low-latency, best-in-class detection at petabyte scale.

Virtru

• Limited options for developers to create custom integrations or extensions.
• Large organizations experience performance issues when scaling up to very high volumes of encrypted data.
• Customer reviews mention slowdowns or failures when dealing with large encrypted attachments.
• Lack of seamless integration with popular cloud storage services like Google Drive.

Human-centric approach

Nightfall AI

• No impact to end-user productivity.
• Educational approach helps users understand acceptable usage of sensitive data.
• Option to involve end-users in the remediation process when appropriate.
• Option for users to report false positives, resulting in improved model fit and reduced noise over time.

Virtru

• New users often find the encryption process confusing initially, leading to adoption resistance.
• Few options for end-users to tailor the tool to their specific workflows or preferences.
• Non-Virtru users often face difficulties in accessing encrypted content, leading to communication delays.
• Limited options for users to report issues or suggest improvements directly within the tool.

Security workflow integration

Nightfall AI

• Seamless integration with leading SIEM and SOAR tools (e.g. Azure Sentinel and Splunk) via webhooks and REST APIs.

Virtru

• Lack of comprehensive integration with security tools.
• Lack of advanced features for seamless incorporation into sophisticated SecOps workflows.
• Difficulties in generating comprehensive audit logs for compliance purposes.
• Low granular control over security rules and policies.

TL;DR

Compared to Virtru, Nightfall AI offers a more comprehensive, AI-driven data protection solution with superior detection accuracy, coverage, ease of use, and integration capabilities. While Virtru focuses primarily on email encryption, Nightfall provides broad data protection across multiple platforms and use cases.

For customers specifically looking to encrypt outgoing emails, Nightfall is better than Virtru for the following reasons:

1. Advanced detection: Nightfall uses state-of-the-art ML-trained detectors for more accurate identification of sensitive data, thereby reducing false positives and missed detections.
2. Comprehensive coverage: While Virtru is email-centric, Nightfall protects data across various SaaS apps, including email systems, to provide a more unified workflow.
3. User-friendly experience: Nightfall offers an intuitive interface with encryption options embedded directly in the Gmail UI. Nightfall also has an intuitive secure reader experience, whereas Virtru users often face challenges with re-authentication and external recipient access.
4. Automated protection: Nightfall provides more flexible and advanced automated remediation options, which consider the full context of emails for policy-driven encryption.
5. Scalability: Nightfall's API-first architecture ensures better performance at scale, while Virtru users face challenges with large volumes of encrypted data and attachments.
6. Integration: Nightfall offers seamless integration with security ecosystems, including SIEM and SOAR tools, which Virtru lacks.‍
7. Customization: Nightfall allows for more granular policy management and user customization than Virtru.

In summary, Nightfall provides a more robust, flexible, and user-friendly approach to data protection, extending beyond just email to offer comprehensive security across multiple platforms and use cases.

Looking for an enterprise DLP solution with intuitive workflows, seamless automation, and comprehensive data protection across SaaS, email, endpoints, and more? Nightfall’s got you covered. Click here to schedule a demo today.