Generative AI is quickly becoming a foundational layer of modern enterprise operations. As adoption accelerates, organisations are also discovering that these tools introduce new and complex security risks that require innovative solutions. Here are the top providers for AI security.

1. Darktrace

Darktrace stands out as a leading solution in the generative AI security space, bringing decades of AI expertise to the challenge of securing enterprise AI systems. Its approach uses self-learning AI that observes every device, user and interaction to develop an understanding of what normal behaviour looks like for each organisation. This philosophy is critical in the context of generative AI security, as most solutions define threats based on previously observed attack patterns, an approach that fails to detect novel or highly targeted attacks.

Darktrace begins by learning from observations, allowing it to identify subtle anomalies that signal emerging threats. Cyber AI Analyst powers this capability, learning from real analyst behaviour to form hypotheses, test them and reach conclusions much like a human would.

Key Features

Darktrace’s solution delivers several capabilities that address the complex challenges of generative AI security:

• Self-learning AI with no prior assumptions: Learns normal patterns for an organisation and spots subtle deviations in behaviour that indicate threats, enabling it to detect novel attacks that rule-based systems miss.
• Two-level analysis reduces false positives: Identifies anomalous events, then uses Cyber AI Analyst to investigate every alert and determine whether it is part of a wider incident, reducing the number of reports to just 2 or 3 critical incidents.
• Seamless integration: Integrates easily with almost any environment, often in a single click from the customer portal and deploys in the cloud or on-site.

2. Knostic   

Knostic is an enterprise AI security company enforcing “need-to-know” access for generative AI, especially large language models. Its mission is to prevent sensitive organisational data from being exposed through AI interactions.

Knostic operates at the AI knowledge layer, analysing LLM responses and applying context-aware policies so users receive only information appropriate to their role and intent. This reduces risks like data leakage, oversharing or unauthorised exposure of internal knowledge. Knostic continuously evaluates responses and blocks those that violate least-privilege principles.

Key Features

Knostic’s solution centres on three core capabilities:

• Real-time policy generation and anomaly detection: Automatically generates access policies for AI tools and detects anomalies.
• AI access control and data leak detection: Monitors copilots and search tools to detect oversharing and prevent sensitive information from being exposed to external AI models.
• Automated compliance and exposure reporting: Generates actionable reports that show where sensitive data was exposed, who triggered it and how it aligns with internal security policies.

3. Lasso Security

Lasso Security is an enterprise AI security platform for generative AI systems, agents and applications. Its goal is to provide organisations with visibility and control, while preventing data exposure, model misuse and AI-specific attacks.

Built for the evolving nature of generative AI, Lasso unifies discovery, risk assessment, governance and real-time protection for both internal and customer-facing applications. It continuously monitors AI interactions, detects risks such as prompt injection or data leakage and enforces security policies at runtime. Lasso ensures AI systems stay within intended boundaries, remain compliant and reduce the risk of shadow AI use.

Key Features

Lasso’s solution provides three distinctive capabilities for enterprise AI security:

• Shadow AI discovery: Uses comprehensive discovery capabilities to give security teams complete oversight of AI tools, agents and applications across the enterprise.
• Behavioural threat detection: Analyses the intent behind agent actions rather than relying solely on predefined patterns.
• Automated AI red teaming: Tests vulnerabilities through automated red teaming, helping security teams identify weaknesses before adversaries can exploit them.

4. Harmonic Security

Harmonic Security is a generative AI governance platform securing employee and agent AI use across the enterprise. It operates at the browser extension, desktop client and MCP gateway level, where it provides oversight of AI usage that never touches the corporate network and would otherwise bypass network security controls.

It uses a zero-touch approach to minimise friction while maintaining security. Instead of blocking, it uses pre-trained models to nudge users toward safer behaviour in daily workflows. Harmonic eases the security team’s workload by automatically classifying risky AI services and distinguishing safe from dangerous apps, enabling organisations to confidently approve trusted tools and restrict risky ones.

Key Features

Harmonic’s approach emphasises on-device protection and context-aware governance:

• On-device monitoring across four AI surfaces: Sits directly on devices to monitor browser-based AI tools, embedded AI features in SaaS applications, native desktop apps and autonomous agent actions across AI tools.
• Context-aware classification with guided responses: Reads the meaning of work, classifying interactions by intent and providing context-aware coaching.
• Real-time governance of prompts and file uploads: Responds to risky AI interactions, allowing security teams to block, warn with context or log silently depending on the sensitivity of the data involved.

Choosing the Best Generative AI Security Platforms

This evaluation features platforms selected for their ability to address the risks introduced by large language models, AI assistants and agent-based workflows. The assessment examines each solution across five critical criteria — generative AI-specific security focus, data protection capabilities, policy enforcement and governance, threat detection and enterprise readiness and scalability.

Generative AI has transformed how organisations operate, as it enables employees to automate tasks, generate content and analyse data with speed and accuracy. While these capabilities boost productivity, they also significantly expand the attack surface and introduce different security challenges that conventional tools cannot address.

Among the most pressing concerns are generative AI security risks like data leakage, where employees may inadvertently share sensitive information with external AI models and prompt injection attacks, which manipulate AI systems into performing unintended actions. Companies that struggle to monitor employees’ use of AI tools without official approval risk amplifying business security they cannot track or control, which these platforms aim to protect.

Securing the Future of AI Innovation

Generative AI represents a transformative opportunity for business, but realising its potential requires a security strategy that specifically addresses the risks it introduces. Tools from a different era cannot adequately protect companies from data leakage, shadow AI or the evolving attack vectors that target AI systems. As companies continue to integrate generative AI into their workflows, evaluating specialised security solutions becomes a business imperative and a technical necessity.