Top 11 Agentic AI Security Solutions in 2026: A Practical Guide to Securing AI Agents

If you are evaluating agentic AI security solutions in 2026, you already know the ground has shifted. AI agents no longer just answer questions. They read email, query databases, call APIs, and trigger actions across your environment, often without a human reviewing each step. Every agent you deploy becomes a new non-human identity with credentials, permissions, and an identity blast radius that legacy controls were never built to govern. According to a Cloud Security Alliance survey, 68% of organizations cannot reliably distinguish AI agent activity from human activity, which is a problem when an agent can move at machine speed.

This guide breaks down the top 11 agentic AI security platforms to consider, organized by category, so you can quickly identify which AI agent security tools fit the problem you are actually trying to solve.

What Is Agentic AI Security?

Agentic AI security is the practice of securing autonomous AI agents across their full lifecycle, from the moment an agent is provisioned to the moment it is decommissioned. It addresses risks that traditional application security was never designed for, because an agent does not just return an answer. It takes actions: reading data, calling tools and APIs, connecting to other systems through the Model Context Protocol, and chaining those steps together at machine speed without a human reviewing each one.

In practice, AI agent security spans the prompts an agent receives, the memory it reasons from, the tool calls and MCP connections it makes, the identities and permissions it operates under, and the runtime actions it ultimately takes. The market has organized around three approaches to that problem: identity and access governance that controls what an agent is and what it can reach, runtime security and posture that inspects how an agent behaves once it is running, and broad enterprise platforms that extend existing security coverage to agents. The sections below group the leading agentic AI security solutions by those three approaches.

How We Evaluated These Agentic AI Security Solutions

No single platform wins for every organization, so this guide assesses each one against the criteria that matter most when comparing AI agent security tools, then groups vendors by the problem they solve best rather than ranking them head to head. Four factors carried the most weight:

• Discovery scope: whether the platform finds every agent, including shadow deployments and MCP servers, not just the ones registered in a console.
• Identity and access controls: whether it enforces least privilege and just-in-time access for non-human and agentic identities instead of leaving standing access in place.
• Runtime protection: whether it inspects agent behavior as it happens, catching threats like prompt injection and out-of-scope tool calls.
• Fit with your stack: how cleanly the platform deploys alongside the identity, cloud, and security tools you already run.

Where a vendor lands in this guide reflects which of these it does best. The strongest agentic AI security platforms cover all four, but most lead with one.

Agentic AI Security Solutions Comparison

Agentic Identity and Access Governance

This first group of agentic AI security solutions secures AI agents by governing the identities they operate under. The premise is simple: an agent is only as safe as the access it holds, so the controls live at the identity and entitlement layer. Expect discovery, ownership attribution, least privilege, and just-in-time access for non-human and agentic identities.

1. Linx Security

At a Glance

Founded: 2023 

Headquarters: New York, New York 

Primary control point: Identity, entitlements, & inline enforcement 

Identities covered: Human, non-human & AI agents 

Linx - Best for AI-Native Identity Governance Across Humans, NHIs, and AI Agents

Linx is best for organizations that want to govern human, non-human, and AI agent identities on a single platform, with real-time visibility, inline enforcement, and remediation built in rather than bolted on.

Description and Features

Linx is an AI-native identity security and governance platform that combines deep identity visibility, automated governance, and continuous security enforcement. At its core is the Linx Identity Graph, which normalizes and correlates data across human, non-human, and agentic identities, mapping the full access path from any identity to the resources it can reach. For AI agents specifically, that means you can see what an agent can touch, how it gained that access, whether it has used it, and the blast radius if it is compromised.

Linx applies the same governance disciplines to agents that mature programs already apply to people. Agentic identity governance enforces least privilege and just-in-time access for service accounts, API keys, bots, and AI agents, replacing standing access with right-sized, time-bound grants.

Where most identity platforms observe from the side and report after the fact, the Linx MCP Gateway puts Linx inline on the path of every agent action. The AI client points at a single endpoint, and the gateway decides per tool, per identity, and per tenant whether each call is allowed, blocked, or routed for approval, checking it against the same access-profile graph that governs human access before anything reaches the upstream system. It brokers the upstream credentials so the model never touches a secret, captures the agent's declared intent on sensitive tools, and writes a full audit record of who did what and why. Because every AI action flows through one point, it is also where an organization can apply an org-wide policy or pull a single shutdown switch across all AI tool access. Today agents can request just-in-time access to a tool from within the same session, with grants either auto-approved or sent for human review.

Because Linx unifies governance with identity security posture management, it surfaces dormant agent credentials, over-permissioned identities, and drift automatically, then lets you remediate the root cause directly inside the platform without a separate ticketing loop.

Pros

• Governs human, non-human, and AI agent identities in one platform rather than treating agents as a separate silo.
• AI-native architecture built from the ground up, not a legacy product with AI features added later.
• Identity Graph provides unified, real-time visibility into what every agent can access and the blast radius of a compromise.
• MCP Gateway enforces access inline at the moment an agent acts, allowing, blocking, or routing each tool call for approval rather than reporting on it afterward.
• In-platform remediation closes the gap between finding risk and fixing it.
• Combines identity governance with identity security posture management, so agent risk surfaces automatically.

Cons

• Smaller connector library and partner ecosystem than long-established identity vendors.
• On-premises application coverage is more limited than legacy enterprise platforms.
• As a newer company, Linx has less analyst tenure than vendors that have been in the market for a decade or more.

2. Astrix Security

At a Glance

Founded: 2021 

Headquarters: New York, New York 

Primary control point: Identity & entitlements 

Identities covered: Non-human and AI agents 

Astrix - Best for Purpose-Built Non-Human and Agent Identity Security

Astrix Security is best for security teams that want a dedicated non-human identity platform extended to AI agents, with strong discovery across both sanctioned and shadow deployments.

Description and Features

In May 2026, Cisco announced its intent to acquire Astrix, with plans to integrate its capabilities across Cisco Identity Intelligence, Secure Access, Duo, and Splunk. Astrix built its reputation on securing non-human identities and has carried that focus into the agentic era. Its Agent Control Plane provides discovery, governance, and threat detection through a Discover-Secure-Deploy framework, with a four-method discovery approach that surfaces registered agents, shadow agents, MCP servers, and the NHIs that agents authenticate with. The platform maps each agent to the credentials it holds, the resources it can reach, and the human owner accountable for it, then scores risk by access scope and blast radius.

Pros

• Mature non-human identity foundation extended naturally to AI agents.
• Four-method discovery surfaces shadow agents and MCP servers, not just registered ones.
• Provisions agents with short-lived, scoped credentials and policy at creation.
• Agentless deployment with strong Fortune 500 enterprise adoption.

Cons

• Roots are in NHI security, so full identity governance workflows for human identities are noticeably less robust.
• Runtime behavioral controls are newer than the discovery and posture capabilities.
• Following the Cisco acquisition, roadmap, pricing, and packaging are subject to change as the platform integrates.

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Note: Cisco announced its intent to acquire Astrix in May 2026.

3. Entro Security (SailPoint)

At a Glance

Founded: 2022

Headquarters: Boston, Massachusetts
Primary control point: Identity & entitlements 

Identities covered: Non-human and AI agents 

Entro Security - Best for Securing Agents and the Secrets They Run On

Entro Security is best for organizations that want to govern AI agents alongside the secrets, API keys, and service accounts they depend on, with secrets discovery built into the platform.

Description and Features

SailPoint acquired Entro Security in June 2026. Entro was early in the non-human identity and secrets security category and has extended that foundation to agentic AI. The platform discovers and classifies every secret, non-human identity, and agent across code, cloud, CI/CD, and SaaS, ties each one to its permissions, purpose, and human owner, and monitors behavior in real time through its NHIDR (Non-Human Identity Detection and Response) engine. For agents specifically, Entro surfaces shadow AI and unsanctioned agents, inventories MCP servers, maps agentic identities back to their creators, and enforces Zero Trust and just-in-time access across the agent fleet.

Pros

• Combines secrets security with non-human and agent identity, so agents are governed alongside the credentials they use.
• Deep secrets discovery across code, cloud, CI/CD, and SaaS finds exposed keys and tokens, not just registered identities.
• NHIDR engine adds real-time detection of anomalous agent and non-human identity behavior.
• Maps every agent and secret to a human owner for accountability.
• Agentless architecture deploys quickly without changing developer workflows.

Cons

• Roots are in secrets and NHI security, so human identity governance is outside its core scope.
• Agent runtime controls are newer than its secrets and NHI capabilities.
• Buyers seeking a single platform for human and non-human governance may need to combine tools.

4. Oasis Security

At a Glance

Founded: 2022 

Headquarters: New York, New York 

Primary control point: Access (just-in-time) 

Identities covered: Non-human and AI agents 

Oasis Security - Best for Agentic Access Management

Oasis Security is best for enterprises that want intent-based, just-in-time access for AI agents and machines layered on a strong non-human identity foundation.

Description and Features

Oasis pioneered non-human identity management and has positioned its Agentic Access Management platform around the idea that access is the number one barrier to scaling AI agents safely. The platform discovers, classifies, and governs machine identities across hybrid environments, then grants agents only the access required for a given task, evaluating intent before the first action is taken. Oasis has raised roughly $195 million in total funding, including a $120 million Series B in 2026, and reports that the majority of its customers are Fortune 500 organizations adopting agentic AI.

Pros

• Intent-based, just-in-time access purpose-built for agents and machines.
• Deep non-human identity lifecycle coverage across hybrid environments.
• Governs access before the first action rather than reacting after the fact.
• Strong enterprise traction and significant funding behind the roadmap.

Cons

• Centered on access and NHI lifecycle rather than full human identity governance.
• Runtime threat detection is less central than access enforcement.
• Broad agent framework coverage is still expanding.

AI Agent Runtime Security and Posture

These AI agent security tools protect agents while they run. Instead of governing identity and entitlements, they inspect the prompts an agent receives, the tool calls it makes, and the actions it takes, then block or flag unsafe behavior. They are the natural complement to identity-layer controls, and several have been absorbed into larger platforms over the past year.

5. Zenity

At a Glance

Founded: 2021 

Headquarters: Tel Aviv, Israel 

Primary control point: Runtime behavior 

Identities covered: AI agents 

Zenity - Best for Agent Runtime Protection and Observability

Zenity is best for security teams that want to discover AI agents across platforms and enforce guardrails at runtime, with detection focused on agent intent rather than isolated alerts.

Description and Features

Zenity provides observability, governance, and threat protection for AI agents across platforms. It inventories agents and attributes ownership, applies secure-by-design policies before deployment, and monitors step-level execution at runtime, correlating tool calls, memory access, and control flow to catch malicious or unintended outcomes even when inputs look harmless. Its detection and response engine identifies direct and indirect prompt injection and maps findings to frameworks like OWASP and MITRE ATLAS, with allow, flag, and block policies. Zenity has raised roughly $59.5 million in funding.

Pros

• Strong discovery and ownership attribution across multiple agent platforms.
• Intent-aware runtime detection that looks beyond prompt-level signatures.
• Prompt injection detection mapped to recognized frameworks.
• Preventive guardrails applied before agents reach production.

Cons

• Focused on posture and runtime rather than identity governance and lifecycle.
• Does not replace an access governance platform for least privilege enforcement.
• Best results assume integration across the agent platforms in use.

6. Prompt Security (SentinelOne)

At a Glance

Founded: 2023 (Prompt Security); 2013 (SentinelOne) 

Headquarters: Tel Aviv, Israel; Mountain View, California 

Primary control point: Runtime behavior 

Identities covered: AI agents & GenAI use 

Prompt Security - Best for Runtime AI Protection Inside an Endpoint Platform

SentinelOne is best for organizations standardized on its Singularity platform that want runtime AI and agent protection folded into endpoint and cloud workload security.

Description and Features

SentinelOne acquired Prompt Security in 2025 and has been integrating it into the Singularity platform. Prompt Security provides real-time monitoring of browsers, desktop AI tools, and APIs, giving security teams visibility and control over employee AI use and protecting against prompt injection and data leakage. Folded into an endpoint and cloud security platform, it lets teams address AI runtime risk without adding a standalone product.

Pros

• Runtime AI protection integrated with a broad endpoint and cloud platform.
• Visibility and control over both managed and unmanaged AI use.
• Defends against prompt injection and data leakage in real time.
• Available as SaaS or on-premises.

Cons

• Greatest value comes when SentinelOne is already the platform of record.
• Agent identity governance is not the focus of the acquired capability.
• Integration of the acquired product into the broader platform is ongoing.

7. Aim Security (Cato Networks)

At a Glance

Founded: 2022 (Aim Security); 2015 (Cato Networks) 

Headquarters: Tel Aviv, Israel 

Primary control point: Runtime behavior 

Identities covered: AI agents & GenAI use 

Aim Security - Best for AI Security Delivered Through SASE

Cato Networks is best for organizations that want GenAI and agent security delivered as part of a converged secure access service edge platform.

Description and Features

Aim Security built an enterprise platform for securing generative AI and agent usage, and was acquired by Cato Networks in 2025 in Cato's first acquisition. Folding AI security into a SASE architecture lets organizations apply policy to AI and agent traffic as part of the same fabric that secures their network and cloud access, which appeals to teams that prefer consolidation over point tools.

Pros

• AI and agent security delivered through a converged SASE platform.
• Consolidates AI policy with existing network and cloud access controls.
• Reduces the number of separate consoles for security teams.

Cons

• Most compelling for organizations adopting or already running Cato SASE.
• Standalone AI security roadmap is now tied to a larger platform direction.
• Identity-layer governance for agents is outside its core scope.

8. Lakera (Check Point)

At a Glance

Founded: 2021 

Headquarters: San Francisco, California (Zurich, Switzerland) 

Primary control point: Runtime behavior 

Identities covered: AI agents & GenAI use 

Lakera - Best for AI-Native Runtime Guardrails and Continuous Red Teaming

Lakera is best for teams that want AI-native runtime protection and continuous adversarial testing, now available within the Check Point ecosystem.

Description and Features

Lakera was acquired by Check Point in 2025 in a deal reported at roughly $300 million, becoming the foundation of Check Point's AI security center of excellence. Its platform pairs real-time runtime protection through Lakera Guard with continuous red teaming through Lakera Red, and is known for Gandalf, a large-scale adversarial testing project with tens of millions of attack data points. The product was built AI-native rather than retrofitted, with low-latency guardrails against prompt injection, jailbreaks, and data leakage across LLMs and agents.

Pros

• AI-native runtime guardrails with low latency and high detection accuracy.
• Continuous red teaming pairs prevention with proactive testing.
• API-based delivery means fast time to protection, with on-premises options.
• Backed by deep adversarial research.

Cons

• Roadmap and packaging now sit within Check Point's broader platform.
• Focused on runtime AI risk rather than identity and access governance.
• Buyers outside the Check Point ecosystem should confirm standalone availability.

Enterprise Platforms Extending to AI Agents

The final group includes broad security suites that have added agent coverage to existing portfolios. Compared with the purpose-built agentic AI security platforms above, the appeal here is consolidation: if you already run one of these suites, extending it to AI agents can avoid buying separate AI agent security tools. The tradeoff is that agent-specific depth varies, and capabilities are often newer than those of dedicated tools.

9. Palo Alto Networks (Prisma AIRS)

At a Glance

Founded: 2005 

Headquarters: Santa Clara, California 

Primary control point: Multi-layer 

Identities covered: Human, non-human & AI agents 

Palo Alto Networks - Best for Platform Consolidation Across AI and Identity

Palo Alto Networks is best for large enterprises that want AI security, identity, and agentic workflows consolidated within a single platform strategy.

Description and Features

Palo Alto Networks has assembled AI security across Prisma AIRS, its acquisition of Protect AI, and Cortex AgentiX for agentic security operations. Its 2026 acquisition of CyberArk added unified security for human, machine, and agentic identity, extending the platform from runtime AI protection into identity and privileged access. For organizations already standardized on Palo Alto, the agentic capabilities arrive as part of a familiar platform rather than a separate purchase.

Pros

• Broad coverage spanning AI runtime protection, identity, and agentic operations.
• Identity security strengthened significantly through the CyberArk acquisition.
• Strong fit for existing Palo Alto platform customers.
• Backed by large-scale threat intelligence and enterprise reach.

Cons

• Value is highest when the broader Palo Alto platform is already in place.
• Capabilities span multiple acquired products that are still being integrated.
• May be more platform than mid-market buyers need for agent security alone.

10. Microsoft (Entra Agent ID + Defender)

At a Glance

Founded: 1975 

Headquarters: Redmond, Washington 

Primary control point: Multi-layer 

Identities covered: Human, non-human & AI agents 

Microsoft - Best for Microsoft-Native Enterprises

Microsoft is best for organizations standardized on Microsoft Entra, Defender, and Copilot that want agent identity and protection within the same stack.

Description and Features

Microsoft has extended its Entra identity platform to give AI agents first-class identities in the directory, so agents built in tools like Copilot Studio and Azure AI Foundry can be governed alongside human and workload identities. Defender extends threat protection to AI workloads, and Purview adds data governance for AI usage. For Microsoft-centric enterprises, this keeps agent identity and security inside an environment teams already operate.

Pros

• Agent identities managed within the same Entra directory as users and workloads.
• Native fit for organizations already running Microsoft security and Copilot.
• Threat protection and data governance extend to AI usage across the stack.

Cons

• Strongest within Microsoft-centric environments; coverage thins outside them.
• Agent identity capabilities are relatively new and evolving quickly.
• Cross-platform governance often needs a dedicated tool for full coverage.

11. CrowdStrike (Falcon Next-Gen Identity Security)

At a Glance

Founded: 2011 

Headquarters: Austin, Texas 

Primary control point: Multi-layer 

Identities covered: Human, non-human & AI agents 

CrowdStrike - Best for Unified Identity Security Across Human, NHI, and AI Agents

CrowdStrike is best for organizations on the Falcon platform that want agentic identity protection unified with endpoint, cloud, and identity threat detection.

Description and Features

CrowdStrike Falcon Next-Gen Identity Security unifies protection for human, non-human, and AI agent identities across the hybrid identity lifecycle, combining privileged access management, identity threat detection and response, and agentic identity protection. The platform maps non-human identities to human owners, flags orphaned and over-permissioned agents, and inspects prompts and intent through Falcon AI Detection and Response to catch permission misuse. Its pending acquisition of SGNL is set to extend just-in-time, continuous authorization across cloud and SaaS, replacing standing privileges with access granted only when needed.

Pros

• Agent identity protection unified with endpoint, cloud, and identity threat detection.
• Maps NHIs and agents to human owners for accountability.
• Continuous, risk-aware authorization that targets standing privileges.
• Single-agent architecture for organizations already on Falcon.

Cons

• Most valuable when the Falcon platform is already deployed.
• Some agentic capabilities depend on integrations that are still rolling out.
• Buyers focused purely on governance workflows may want a dedicated IGA platform.

Frequently Asked Questions

What are agentic AI security solutions?

Agentic AI security solutions are platforms that secure autonomous AI agents across their lifecycle, from provisioning to decommissioning. They address risks traditional application security misses: the prompts an agent receives, the tool calls and MCP connections it makes, the identities it operates under, and the actions it takes. The category splits into three approaches: identity and access governance, runtime security and posture, and enterprise platforms that extend existing coverage to agents.

How is securing AI agents different from traditional application security?

Securing AI agents means governing autonomous actions, not just validating inputs and outputs. An agent can chain together APIs, databases, and external services in a single workflow at machine speed, with no human reviewing each step. That shifts the controls that matter toward the identity and permissions an agent holds and how it behaves at runtime, rather than the data it returns.

What is the difference between agent identity governance and agent runtime security?

Identity governance controls what an agent is allowed to access, while runtime security controls how it behaves once it is running. Governance covers discovery, ownership, least privilege, and just-in-time access. Runtime security inspects prompts, tool calls, and actions to block unsafe behavior. The two are complementary: governance shrinks what an agent can reach, and runtime security catches misuse of what remains. Mature programs use both.

Do I need a dedicated tool if I already have an IGA or CASB platform?

You need a dedicated tool only if your existing platform cannot discover, govern, and monitor AI agents. Many IGA and CASB vendors have added agent capabilities, so check whether yours finds shadow agents and MCP servers, enforces least privilege and just-in-time access for non-human identities, and inspects agent behavior at runtime. If it only covers human identities or only inspects content, purpose-built AI agent security tools fill the gap.

When do I need agentic AI security?

You need agentic AI security the moment an AI agent has credentials and can take actions in your environment. At that point an agent carries the same risk as a privileged non-human identity and should be governed like one. Scale is not the trigger. A single over-permissioned agent with production access is enough to warrant discovery, least privilege, and runtime visibility.

Which agentic AI security solutions are best for large enterprises?

For large enterprises, Linx, Entro Security, Palo Alto Networks, Microsoft, and CrowdStrike are the strongest fits. The platform suites suit organizations that want agent security folded into tools they already run, while purpose-built options like Linx, Astrix, and Oasis govern human, non-human, and agentic identities at enterprise scale.

Which agentic AI security platforms are best for mid-market companies?

For mid-market companies, Linx and Zenity are strong fits. These AI-native, cloud-native platforms deliver agent discovery, governance, and control without requiring a dedicated team to deploy or operate them.

What about agentic SOC platforms?

Agentic SOC platforms are a separate category not covered in this guide. They use AI agents to do security work, like automating alert triage and response, whereas the agentic AI security solutions here secure the AI agents your organization deploys. If your goal is protecting the agents running across your business, the platforms above are the relevant set.

What should I look for when evaluating AI agent security tools?

The strongest AI agent security tools combine discovery coverage, identity and access controls, runtime protection, and fit with your existing stack. Confirm the platform finds shadow agents and MCP servers, enforces least privilege and just-in-time access for non-human identities, inspects agent behavior at runtime, and can remediate what it finds rather than only flagging it. Then weigh whether a purpose-built platform or an extension of a tool you already own gives better coverage.

What are the top AI agent security tools in 2026?

The top AI agent security tools in 2026 include Linx Security, Astrix Security, Entro Security, Oasis Security, Zenity, Prompt Security (SentinelOne), Aim Security, Lakera, Palo Alto Networks, Microsoft, and CrowdStrike. They fall into three categories: identity and access governance platforms that control what agents can reach, runtime security tools that protect how agents behave, and enterprise suites that extend existing coverage to agents. The right choice depends on whether your biggest gap is governing agent access, inspecting agent behavior at runtime, or consolidating onto a stack you already run.

How much do agentic AI security solutions cost?

Most agentic AI security solutions use custom enterprise pricing rather than published rates. Cost is driven by the number of identities and agents under management, the breadth of integrations, and which capabilities you enable, since discovery, governance, and runtime protection are sometimes priced as separate modules. When comparing quotes, ask whether professional services are required, whether remediation is included, and what the total looks like with every module you need turned on.

Securing the Agentic Enterprise

The direction of travel is clear. As AI agents take on real work across the enterprise, identity becomes the control plane for agentic AI security, and runtime visibility becomes the safety net. The strongest programs treat every agent as a privileged non-human identity, enforce least privilege and just-in-time access instead of standing access, and watch agent behavior closely once it is in production. The right tool depends on the gap you are closing: identity and access governance, runtime protection, or consolidation onto a platform you already run.

This is where Linx fits for teams that want to govern agents the same way they govern people and machines. Linx unifies visibility, governance, and remediation across human, non-human, and AI agent identities through its agentless Identity Graph, applies modern identity governance and just-in-time access to the agents you deploy, and surfaces over-permissioned or orphaned agent identities so you can fix the root cause directly. Ready to see how it works? Get a demo and learn how Linx provides granular access control and real-time visibility into AI agent actions.