Harmonic Security Alternatives

Harmonic Security has carved out a position in AI governance and control, specializing in shadow AI discovery and on-device enforcement for enterprises navigating generative AI adoption. Founded in 2023 with approximately $26M in funding, the platform spans shadow AI discovery, intent-aware detection, and inline coaching and control across browser, desktop, and agent environments. However, organizations requiring comprehensive data exfiltration prevention that spans SaaS applications, endpoints, email, browsers, and AI workflows often need solutions with broader coverage. This guide examines seven alternatives that address the full spectrum of AI data security challenges in 2026, starting with Nightfall AI, an AI-native platform that delivers real-time visibility and control over data movement by humans and AI agents.

Key Takeaways

• AI/ML-based detection can reduce false positives versus legacy approaches: AI/ML-based detection can reduce false positives compared to regex- and rules-heavy DLP approaches; Nightfall delivers 95% precision out of the box, dramatically reducing false positives and alert fatigue
• Unified platforms reduce operational complexity: Managing data protection across SaaS, endpoints, browsers, and AI tools through a single policy engine eliminates the silos that come with point solutions
• MCP server visibility is now essential: As AI agents gain access to enterprise systems through Model Context Protocol workflows, platforms covering local stdio and remote Streamable HTTP MCP transports become critical for governance
• Autonomous operations accelerate response: Platforms with AI-powered analysts that investigate threats, optimize policies, and generate reports through natural language cut manual investigation time significantly
• Real-time control beats visibility alone: Solutions offering inline blocking with real-time enforcement enable organizations to stop sensitive data movement at the moment of action rather than discovering exposures after the fact

1. Nightfall AI

Nightfall AI delivers an AI data security platform that governs how data is accessed, moved, and exposed across human activity and AI agent workflows. Nightfall AI launched publicly in November 2019 after starting as Nightfall.ai in 2018. The company disclosed $20.3M in launch funding in 2019 and a $40M Series B in 2022, with investors including Bain Capital Ventures, Venrock, WestBridge Capital, Pear VC, and Webb Investment Network, along with cybersecurity leaders Kevin Mandia, Freddy Kerrest, and Doug Merritt. The platform provides enterprises real-time visibility and control over data movement.

How Does Nightfall AI Work?

Nightfall uses one detection brain across SaaS, endpoints, AI agents, and MCP workflows. The platform distinguishes legitimate business activity from real exfiltration without slowing teams down. Key highlights:

• Deployment: API-based SaaS integrations deploy in minutes, with a 10-minute setup for the first SaaS app or endpoint deployment and full endpoint coverage across macOS and Windows devices reachable within a week
• Detection: ML detectors for PII, PHI, secrets, credentials, and financial data, plus LLM classifiers across 20+ categories with 95% precision out of the box
• Control: Real-time actions including block, coach, override, manual approval, and automated approval workflows
• Remediation: Granular options to redact, delete, revoke, quarantine, and encrypt sensitive content

Coverage and Integration

Nightfall provides comprehensive protection across the surfaces where sensitive data moves:

• SaaS Applications: Slack, Google Drive, Gmail, GitHub, Jira, Confluence, Microsoft 365, Salesforce, Zendesk, and Notion
• AI Applications: ChatGPT, Microsoft Copilot, Gemini, Deepseek, Perplexity, Claude, and Grok through the AI applications integration
• Endpoints and Browsers: macOS and Windows support with Chrome, Firefox, Edge, and Safari coverage
• MCP Workflows: Local stdio and remote HTTP/SSE MCP workflows, IDE hooks, risk scoring, tool classification, and prompt injection detection through MCP security

Nyx: Autonomous DLP Analyst

Nightfall's Nyx autonomous analyst transforms how security teams operate. The AI-powered analyst autonomously investigates threats, optimizes policies, and generates reports through natural language interactions. Nightfall's ROI calculator models a 6x ROI scenario and assumes an 85% reduction in manual investigation time through AI-based detection, investigation, and response.

What Makes Nightfall AI Unique

• Unified Policy Engine: One policy across endpoint, SaaS, and AI agents provides consistent enforcement and eliminates administrative overhead
• AI-Powered Data Lineage: Traces data from source to destination across systems, assessing risk based on context and movement patterns
• High Accuracy Detection: Nightfall's 100+ AI-based models classify content with 95% accuracy, compared with the 5-25% typical of legacy solutions, dramatically reducing false positives
• Inline Blocking: Real-time blocking and lightweight enforcement with millisecond overhead enable prevention at the moment of action

Best For: Organizations seeking a unified AI data security platform that governs both human and AI agent data movement across SaaS, endpoints, email, browsers, and MCP workflows with autonomous operations and high-precision detection.

2. Strac

Strac positions itself as a DLP-centric solution with data security posture management capabilities, offering coverage across SaaS, cloud, endpoint, GenAI, and MCP workflows.

Core Capabilities

• Data loss prevention across multiple surfaces
• SaaS and cloud application monitoring
• Endpoint protection for macOS and Windows
• GenAI and MCP DLP coverage
• Browser protection capabilities

Deployment Approach

Strac emphasizes deployment through API-based integrations, enabling organizations to establish coverage. The platform focuses on contextual machine learning for detection.

Integration Coverage

The platform provides protection across standard enterprise applications and extends coverage to AI tools including ChatGPT, Copilot, Claude, Perplexity, and Cursor. MCP DLP coverage addresses emerging agent workflows.

Best For: Organizations looking for comprehensive DLP coverage across traditional SaaS applications and emerging AI tools with MCP workflow support.

3. DoControl

DoControl specializes in SaaS security and data access governance, with a focus on managing file-sharing risks at scale across cloud collaboration platforms.

Key Features

• Contextual risk scoring for data access decisions
• Bulk remediation capabilities for handling legacy exposure
• Deep integration with major SaaS platforms
• Identity-based access controls
• Workflow-based remediation processes

SaaS Integration Focus

DoControl provides deep integration with Google Drive, Box, Slack, and SharePoint, focusing on the files and permissions that create exposure in cloud collaboration environments. The platform focuses on identifying and remediating overshared content.

Remediation at Scale

One of DoControl's capabilities is bulk remediation. The platform supports remediation at scale, including bulk actions across large volumes of files and Google Shared Drive permissions through streamlined workflows.

Best For: Organizations with extensive SaaS file-sharing environments requiring bulk remediation capabilities and identity-based access governance.

4. Cyera

Cyera is an AI-native data security platform with DSPM, discovery and classification, DLP, and AI-security capabilities across cloud, SaaS, on-prem/hybrid, and AI environments.

Platform Capabilities

• Deployment for cloud environments
• Data discovery and classification
• Data security posture management
• Visibility across major cloud providers
• AI-powered classification capabilities

Cloud-First Architecture

Cyera's architecture emphasizes cloud-native operation, providing organizations with visibility into where sensitive data resides across their environments.

Posture Management Focus

Cyera combines DSPM with DLP/Omni DLP and AI-security controls. Rather than being posture-only, its DLP provides centralized data-risk intelligence and policy decisioning that works alongside existing controls, and it can block risky user or agent actions.

Best For: Organizations prioritizing cloud data discovery and posture management who need visibility into sensitive data locations across multi-cloud environments.

5. Varonis

Varonis delivers data security and access governance with deep behavioral analytics capabilities, supporting organizations with complex access control requirements across both cloud and on-premises environments.

Core Capabilities

• Behavioral analytics for threat detection
• Access intelligence and permission management
• Full-stack AI security features
• Microsoft 365, SharePoint, and OneDrive integration
• On-premises file share support

Behavioral Analytics

Varonis emphasizes behavioral analytics to identify anomalous user activity that could indicate insider threats or compromised accounts. This approach focuses on patterns of access rather than content inspection alone.

Market Recognition

Varonis was named a Gartner Peer Insights Customers' Choice for Data Security Posture Management in 2025 and announced the same recognition again in 2026 for the third consecutive year. The 149-review, 4.9 out of 5 figure is associated with Gartner Peer Insights as of early 2025, not G2; current G2 data shows 66 reviews and a 4.6 out of 5 rating.

Enterprise Scale

Varonis supports large enterprises with complex permission structures, providing visibility into who has access to what data and how those permissions change over time.

Best For: Enterprises with significant on-premises infrastructure and complex access governance requirements seeking behavioral analytics-driven threat detection.

6. Lasso Security

Lasso Security provides end-to-end agentic AI security, addressing the full lifecycle from discovery through runtime protection with specialized capabilities for AI agent environments.

Platform Scope

• AI Bill of Materials (AI-BOM) inventory for all AI assets
• Security posture management for AI systems
• Automated red teaming with a 300K+ payload library
• Runtime protection
• Intent-based detection capabilities

Agentic AI Focus

Lasso Security specifically targets the security challenges introduced by autonomous AI agents, providing visibility into agent behavior and the ability to detect malicious or unintended actions.

Detection Performance

Lasso's award profile describes its AI Detection and Response capability, which detects anomalous agent behavior at runtime, and its Intent Deputy capability for intent-based threat detection. Lasso was recognized in The Hacker News Cybersecurity Stars Awards 2026 as a winner in the Agentic AI Security category.

Red Teaming Capabilities

Automated red teaming with a 300K+ payload library, including OWASP Top 10 and MITRE coverage, enables continuous security testing of AI systems without requiring dedicated security research resources.

Best For: Organizations with significant AI agent deployments requiring specialized security testing, posture management, and runtime protection for autonomous AI systems.

7. Prompt Security (acquired by SentinelOne)

Prompt Security, acquired by SentinelOne in 2025, operates in the AI data security category, focusing on protecting organizations from risks associated with generative AI adoption and usage. SentinelOne announced a definitive agreement to acquire Prompt Security in August 2025 and completed the acquisition in September 2025, and now presents it as part of the SentinelOne AI security platform.

Core Focus Areas

• GenAI security and governance
• Prompt-level protection capabilities
• AI application monitoring
• Data leakage prevention for AI tools
• Policy enforcement for AI usage

AI Security Specialization

Prompt Security concentrates specifically on the security challenges introduced by generative AI tools, providing controls around how employees interact with AI applications and what data flows into those systems.

Enterprise AI Governance

The platform addresses the governance requirements that emerge as organizations scale their AI adoption, helping security teams maintain visibility and control over AI usage patterns.

Best For: Organizations focusing specifically on generative AI security controls and governance for employee AI tool usage, now delivered as part of the SentinelOne AI security platform.

Why Nightfall AI Stands Out for AI Data Security

Purpose-Built for AI-Era Data Movement

Nightfall AI was architected from the ground up for the reality that AI has changed both how data moves and who moves it. Data now flows through employees, copilots, agents, MCP servers, SaaS apps, email, and endpoints at machine speed. Legacy DLP was built for human-driven data movement, but AI agents now move data autonomously. Nightfall addresses both human risk and AI agent risk in one unified platform.

Comprehensive Visibility and Control Across Supported Surfaces

While some alternatives focus on shadow AI discovery or SaaS file governance, Nightfall provides comprehensive coverage:

• SaaS Applications: Real-time and historical scanning across 13 apps with granular remediation
• Endpoints: Lightweight macOS and Windows endpoint agents and browser plugins, with an endpoint footprint of approximately 1% CPU and 50MB RAM
• AI Applications: Protection across ChatGPT, Copilot, Gemini, Claude, and other AI applications
• MCP Workflows: Coverage for local stdio, remote HTTP/SSE, and shadow MCP detection through MCP security capabilities
• Email and Browsers: Browser and email controls including supported-browser coverage (Chrome, Firefox, Edge, and Safari), upload/download controls, clipboard controls, print/USB controls, and email encryption capabilities

Control-First Architecture

Nightfall's strongest differentiation is that visibility alone is not enough. The platform provides real-time controls including block, coach, override, manual approval, and automated approval. This enables security teams to govern data movement to shadow AI while still enabling AI adoption and business productivity. Visibility without control is just a dashboard.

AI-Native Detection Engine

Nightfall's detection engine delivers 95% precision out of the box, compared with the 5-25% typical of legacy DLP. The platform includes:

• ML detectors for PII, PHI, secrets, credentials, and financial data
• LLM classifiers across 20+ categories
• Continuous learning that automatically improves detection and reduces false positives over time
• Prompt injection detection for AI agent traffic

Autonomous Operations with Nyx

The Nyx autonomous DLP analyst represents a fundamental shift in how security teams operate. Rather than drowning in alerts and manual investigations, teams can interact with Nyx through natural language to:

• Surface risky users and prioritize investigations
• Receive policy recommendations based on organizational patterns
• Analyze incidents with full context including HRIS/IdP metadata
• Generate reports for executive stakeholders

Nightfall's ROI calculator models a 6x ROI scenario and assumes an 85% reduction in manual investigation time through autonomous operations.

Proven Enterprise Scale

Over 100 organizations run on Nightfall, including Gusto, DraftKings, Grafana Labs, Grab, Nubank, and Decagon. API-based SaaS integrations deploy in minutes, with a 10-minute setup for the first SaaS app or endpoint deployment and full endpoint coverage across macOS and Windows devices within a week, allowing security teams to achieve value quickly rather than spending months on implementation.

Consolidation Advantage

Nightfall eliminates the need to manage separate tools for DLP, insider risk, and AI governance. One platform, one detection brain, and one policy engine across supported surfaces reduces operational burden and vendor management complexity. For organizations evaluating alternatives to point solutions, Nightfall's unified approach delivers both security effectiveness and operational efficiency.

Ready to see how Nightfall governs data movement across humans and AI agents? Request a demo to experience the platform's capabilities firsthand.

Frequently Asked Questions

What makes Nightfall AI a distinct alternative to Harmonic Security?

Harmonic Security is an AI governance and control platform focused on shadow AI discovery, intent-aware detection, inline coaching and control, and data-leak prevention across browser, embedded AI, desktop and native AI apps, and agent and MCP workflows, spanning over 1,000 AI surfaces. Nightfall AI provides broader coverage as a unified AI data security platform that governs data movement across SaaS applications, endpoints, email, browsers, and AI agent workflows including MCP servers. While Harmonic specializes in AI governance and control at the point of AI use, Nightfall provides comprehensive data protection with real-time controls to block, coach, or allow sensitive data movement across supported surfaces.

How do AI-native DLP solutions differ from traditional data loss prevention?

Traditional DLP relies on regex patterns and static rules, which can generate significant false positives. AI-native solutions like Nightfall use ML detectors and LLM classifiers that understand context; Nightfall delivers 95% precision out of the box, compared with the 5-25% typical of legacy DLP. More importantly, legacy DLP was designed for human-driven data movement through known channels, while AI-native platforms can detect and control data movement by autonomous AI agents, copilots, and MCP workflows that operate at machine speed.

Can Nightfall AI help with compliance requirements like HIPAA and PCI?

Nightfall includes purpose-built ML detectors for PHI, PCI, PII, and other regulated data types. The platform's granular remediation actions including redact, delete, revoke, quarantine, and encrypt support compliance workflows for HIPAA, PCI DSS, GDPR, and other regulatory frameworks. Real-time detection, remediation, and reporting capabilities help reduce compliance risk and support workflows for regulated data types such as PHI, PCI, and PII.

What types of AI agent activities can Nightfall AI monitor and control?

Nightfall covers local stdio and remote HTTP/SSE MCP workflows, IDE hooks, and agent traffic across AI applications. The platform provides risk scoring and tool classification across read, read/write, and destructive actions. Prompt injection detection identifies malicious attempts to manipulate AI agents. This coverage includes Claude Desktop, Cursor, VS Code, Claude Code, local stdio MCP discovery, remote HTTP/SSE MCP discovery, and custom MCP integrations; Nightfall also covers ChatGPT and other AI applications through its AI app and browser and endpoint controls.

Is Nightfall AI only for large enterprises, or can smaller organizations benefit?

Nightfall's structured pricing tiers make the platform accessible beyond large enterprises. The platform offers rapid deployment with API-based SaaS coverage in minutes and a 10-minute setup for the first SaaS app or endpoint deployment, reducing the implementation burden that traditionally made DLP impractical for smaller security teams. The autonomous Nyx analyst further reduces operational requirements by automating investigations and policy optimization.

How does Nightfall AI's detection engine achieve 95% precision?

Nightfall's detection engine combines over 100 AI-based models, including LLM-based file classifiers, computer vision models, and pre-trained detectors for sensitive data types, with LLM classifiers that understand context across 20+ categories. Unlike regex-based detection that triggers on pattern matches regardless of context, Nightfall's models evaluate the full context of data movement to distinguish legitimate business activity from actual risk. Nightfall's platform learns continuously and automatically improves detection and false-positive reduction over time.