7 Best Agentic AI Security Platforms to Stop Shadow Agents & Over-Permissioned NHIs

Autonomous AI agents now push code, spin up cloud resources, and fetch sensitive records — often with no one watching.

Across a typical enterprise, non-human identities outnumber employees 80 : 1. Every stray token is a breach path waiting to open.

Regulators see the same risk. In May 2026, the Five Eyes alliance warned of “cascading failures,” while a June 2025 Gartner report predicted that 40 percent of agent-driven projects will be cancelled by 2027 because of runaway cost, fuzzy ROI, or weak controls.

We put those defenses to the test, cut through the noise, and found seven platforms worth your time in 2026. Let’s walk through what we learned — and how you can choose the right stack for your team.

Why identity became the AI blast radius

Every autonomous agent carries a “passport,” the API key or service account that lets it roam your cloud. In many companies, these non-human identities now outnumber employees 80 : 1 (ITPro, April 2026).

That imbalance flips the security model. We once wrapped controls around people with onboarding forms, MFA prompts, and quarterly training. Today the busiest “users” appear in seconds, inherit wide-open privileges, and keep them until someone steps in.

An over-permissioned agent can delete tables at 2 am, siphon chat logs, or merge its own code with no review. Attackers no longer need a phishing kit; stealing the robot that already holds the keys is faster.

First rule of AI defense: treat every agent credential as a high-impact privilege. Rotate it, watch it, and narrow what it can touch. When an agent makes a bad choice — or is tricked into one — the blast radius stops where that identity stops.

The same report highlights that 71 percent of service tokens are never rotated on schedule, leaving a leaked key live for months and greatly widening the blast radius.

Get identity right and you limit damage before the first prompt lands; skip it and every other control is a patch on a balloon that has already popped.

The threat picture: from boardroom hype to real-world alarms

A year ago, agentic AI risk felt like conference chatter. Today you can find it on government letterheads.

In May 2026, the Five Eyes cybersecurity agencies warned that unchecked AI agents pose a “clear and present danger” to critical infrastructure, according to a joint advisory published by the Five Eyes cybersecurity agencies.

Five Eyes agentic AI joint advisory official document cover

Lawmakers are moving just as fast.

European Union: Article 12 of the final EU AI Act requires every high-risk agent to keep tamper-proof logs for at least six months.
Singapore: The January 2026 Model AI Governance Framework for Agentic AI calls for controls across the agent lifecycle but leaves verification methods open.
United States: The SEC Investor Advisory Committee in July 2025 recommended rules that make public companies spell out where and how they use AI.

Attackers did not wait for the ink to dry. Security teams have documented:

jailbreak prompts that drained private Git repos,
poisoned PDFs that rewrote audit logs, and
loop exploits that convinced payroll bots to send raw salary files.

The lesson is blunt: your perimeter is no longer the network; it is every token your agents hold. Align controls to that reality now, or plan to write the breach report later.

How we picked the “Magnificent Seven”

Ranking tools only matters when the criteria are visible. We set two rules: mirror the attack chain your team faces each day and keep the math transparent.

Attack-chain focus. A rogue agent starts with a credential, pivots through excess permissions, then damages production. That path gave us seven evaluation pillars.
Weighted by spend. CISO surveys show identity controls and real-time detection consume nearly half of 2026 AI-security budgets, so those pillars earn the most points.

Scoring model

Identity and secrets governance (25 percent) – Can the product find, rotate, and right-size every agent key?
Runtime threat detection (20 percent) – Does it catch abnormal behavior and block data exfiltration?
Shadow-agent discovery (15 percent) – How quickly can it reveal bots no one admitted deploying?
Permission and RBAC control (15 percent) – Fine-grained guardrails that keep agents inside the fence.
Compliance and audit trail (10 percent) – Evidence a regulator will accept on a tough day.
Integration breadth (10 percent) – Works where your agents already live, from GitHub to Okta to AWS.
Enterprise readiness and pricing (5 percent) – Stability, support, and a plan that rewards early pilots.

We blended analyst notes and more than 30 customer interviews, then calculated a weighted composite for each vendor. A June 25, 2025 Gartner forecast warns that over 40 percent of agentic-AI projects will be cancelled by 2027 without stronger risk controls.

This is not a beauty contest. It is a risk map so you can wire agents into production with confidence.

1. Entro Security: tame every agent key before it misbehaves

The five failure modes security teams see most (shadow agents, over-permissioned NHIs, prompt pivots, rogue MCP servers, and missing audit trails) stem from ungoverned credentials, as detailed in Entro’s June 2026 breakdown of agentic AI risks. Entro unifies security across AI agents, the non-human identities behind them, and the secrets they hold — mapping each agent to the API keys and service accounts it owns, then tightening those privileges in real time.

Onboarding is built around fast discovery: connect Entro to your clouds, Git repos, and vaults and it surfaces non-human identities and hard-coded tokens that traditional secret scanners miss, then attributes each one back to an accountable owner or team.

What it does

Live discovery – Connects to clouds, Git repos, and vaults to surface every secret and the agent that owns it, with ownership and lineage attached.
NHIDR™ detection – Non-Human Identity Detection and Response watches usage patterns; if a key suddenly touches a new resource or spikes in volume, Entro flags the anomaly and can quarantine the credential while it alerts Security.
Auto-rightsizing – Downgrades over-privileged credentials to least privilege and schedules rotation, no ticket required.
Shift-left coverage – Comments on pull requests when a secret appears in code, stopping leaks before merge.

Deployment and pricing

Entro ships as SaaS, with a hybrid option for regulated workloads. Licensing is tied to the number of non-human identities, so cost rises with risk, not traffic.

Where it shines

When identity sprawl is the problem, Entro gives you one place to see every agent, every key, and the human or team that owns it — plus the right-sizing and rotation to shrink that footprint quarter over quarter. If service-account sprawl keeps you up at night, it is the single dashboard, and kill switch, for every agent credential.

Watch-outs

Entro does not filter live prompts. Pair it with a runtime firewall (see Wallarm) for end-to-end coverage.

Best for: Security teams swimming in service accounts who need instant visibility, automatic least-privilege, and audited rotation without touching code.

2. Rubrik Agent Cloud: hit rewind on bad agent actions

When an autonomous agent deletes rows, rewrites configs, or floods an API, Rubrik Agent Cloud lets you press Rewind and restore the data in seconds.

Rubrik Agent Cloud product homepage screenshot highlighting Rewind capability

What it does

Continuous snapshots. RAC shadows every agent action and stores immutable copies on Rubrik Security Cloud, the same architecture used for ransomware recovery.
One-click rollback. You can revert to the last clean point without downtime; live demos show recovery in minutes.
Behavior alerts. Policies flag spikes in deletes or off-hours key use, and RAC can quarantine the workload while snapshots stay available for forensics.
Identity traceability. Integrations with Active Directory and Okta map each change to a service identity or human sponsor, closing the audit loop.

Deployment and pricing

RAC ships as a SaaS extension of Rubrik Security Cloud. Current Rubrik customers add rollback with no new hardware, while new buyers license RAC by protected data footprint.

Where it fits

If your board measures risk in minutes of downtime or rows lost, RAC provides a data-grade safety net for agentic AI. It will not stop prompt injections, so pair it with a runtime firewall such as Wallarm for prevention, but it sharply limits impact when prevention fails.

Best for: Enterprises that already rely on Rubrik backups or that need provable, instant recovery when an agent goes rogue.

3. Zenity: your AI control tower

If you run more than one agent, you probably run hundreds across Microsoft 365 Copilot, Salesforce Agentforce, AWS Bedrock, and home-grown frameworks. Zenity puts each flight on the same radar and allows take-off only when policy says it is safe.

What it does

Continuous discovery. Zenity scans Microsoft 365, Salesforce, Google Workspace, ChatGPT Enterprise, and custom apps, surfacing shadow agents with ownership, permissions, and risk score in hours, not weeks after the first scan.
Correlation engine. Rather than 50 low-signal alerts, Zenity links prompt → tool call → data touchpoint → response and raises one high-confidence incident, cutting false positives for Fortune 500 customers.
Intent-based governance. Security teams write policies such as “customer data must stay in tenant.” Zenity enforces each rule automatically and logs every deny for audit.
Rich context. Each alert tags business owner, data class, and originating Jira ticket, turning a 2 am page into a quick Slack to the right team.

Deployment and cost lens

Zenity is SaaS with optional hybrid collectors. Licensing is tiered by the number of managed agents, and Fortune 500 references appear on Microsoft AppSource.

Where it fits

Zenity will not sandbox code or roll back data, so pair it with Edera for isolation or Rubrik for recovery. When visibility and policy across a growing AI fleet keep you up at night, Zenity serves as the control tower before traffic doubles again.

Best for: Global enterprises juggling many AI initiatives that need one console to see, govern, and audit them all.

4. Wallarm Protect AI: real-time guard for prompt attacks

Prompt attacks can slip “ignore your rules” into a chat or hide a system prompt in HTML. Wallarm Protect AI sits in that traffic and blocks the bad request before it reaches the model.

What it does

Inline filtering. Every request moves through Wallarm’s cloud or container proxy, which checks payloads against a signature set tuned for prompt injection and jailbreak patterns.
Behavior analytics. If an agent that usually calls four internal APIs suddenly hits ten new endpoints, Wallarm throttles or blocks the traffic. Product benchmarks list an average processing time of 1.339 ms.
Allow-list enforcement. You can declare the only tools an agent may reach; anything outside that list returns an instant HTTP 403.

Deployment and scale

Deploy a sidecar container in Kubernetes or point a DNS CNAME for SaaS apps. The same engine scales from one endpoint to millions of requests without code changes.

Where it fits

Wallarm will not discover shadow agents or rotate keys, so pair it with identity governance such as Entro for a layered defence. When the goal is clean traffic and zero data leaks in real time, Wallarm offers a lightweight API-first solution.

Best for: Teams running customer-facing chatbots or workflow agents that must stay online yet never leak data or run unauthorised commands.

5. Operant MCP Gateway: guardrails for tool-using agents

Your agents call chains of tools through the Model Context Protocol (MCP). Operant MCP Gateway drops into that stream to discover every server, map each tool, and block off-policy calls in real time.

What it does

Instant inventory. After deployment, Operant lists all MCP servers, agents, and tools across cloud and on-prem environments in less than 5 minutes.
Trust zones and least privilege. Security teams define zones such as read-only data or prod shell. The gateway lets an agent work in only one zone at a time and blocks cross-zone calls before the request leaves the gateway.
Payload inspection. Operant parses structured MCP payloads; if a code-exec tool receives rm -rf /, the gateway quarantines the request and posts a Slack alert that includes prompt, tool, user, and a recommended fix.

Deployment and scale

Run a single Docker container and add an API token to start routing traffic. The cloud console handles analytics, while a hybrid mode keeps sensitive payloads on-prem for regulated workloads.

Where it fits

Operant governs runtime tool use but does not manage secrets or roll back data. Pair it with Entro for identity and Rubrik for recovery to cover the full stack. For teams orchestrating complex, multi-tool workflows, it offers the quickest path to zero-trust boundaries without rewriting agent code.

Best for: Engineering and security teams running large MCP pipelines that need real-time guardrails and rich context without heavy infrastructure.

6. Adversa AI: always-on red teaming for your models

Even strong guardrails need proof. Adversa AI supplies that proof by running a continuous, automated red team against your models and agents.

What it does

Continuous attack library. The platform draws from more than 5,000 academic papers and real exploits, refreshed weekly to reflect the latest attacks.
Live dashboard. Findings arrive with reproducible prompts, success rate, potential impact, and severity so developers can patch while security leaders track trend lines.
Auto-update feed. New exploits posted on forums or arXiv roll into the next test cycle without manual tuning.

Where it fits

Adversa covers 60-plus vulnerability classes across agents, models, and MCPs, often surfacing issues before users see them. The platform does not sit inline, so combine it with a runtime shield such as Wallarm for live blocking while Adversa keeps the attack library ahead of the curve.

Best for: Teams shipping high-stakes AI in finance, health, or brand-sensitive chatbots that need daily evidence the agent will not say or do the one thing that grabs headlines.

7. Edera Safe Agents: sandbox first, ask questions later

When an AI agent moves from suggesting code to running code, the blast radius expands quickly. Edera Safe Agents limits that risk by cloning a hardware-isolated micro-VM for every high-privilege action, then destroying it seconds after completion.

What it does

Ephemeral micro-VMs. On an execute-script call Edera spins up a fresh micro-VM, injects only the needed secrets, runs the task, captures output, and destroys the instance. Vendor benchmarks list a 0.8 ms spawn time using copy-on-write forking.
Stateless or stateful modes. Select a disposable sandbox for a single analytics job or a controlled, persistent volume for multi-step workflows; either way, data stays fenced from the rest of your cloud.
Deterministic audit. Each run records sandbox hash, script checksum, resource list, and a SHA-sealed stdout transcript so auditors can replay events without touching production.
Compliance choices. A GovCloud edition keeps all artifacts inside ITAR-compliant US regions to satisfy federal isolation rules.

Trade-offs

Cold-boot latency introduces a sub-second delay, and Edera does not explain why an agent misbehaved; it only stops the fallout. Pair it with Operant for policy control or Rubrik for rollback to cover the full lifecycle.

Best for: Defense, healthcare, and critical infrastructure teams where “AI ran rm -rf /” would be career ending and every risky action must stay inside a disposable box.

Quick-pick decision guide

If you have budget or patience for one new control this quarter, match your main pain point to the first tool, then add layers as the program matures.

Your immediate headache	First tool to deploy	Why it helps (one metric)
“No idea which bots exist.”	Zenity (enterprise view) or Entro discovery	Moves from discovery to governed in hours
“Keys are everywhere, half have full power.”	Entro	Rightsizes and rotates 100 percent of non-human identity keys on the first pass
“Our chatbot faces the public internet.”	Wallarm Protect AI	Blocks prompt injection with 1.339 ms average processing time
“Agents run multi-step workflows that scare auditors.”	Operant MCP Gateway	Enforces trust-zone policy at the first tool call
“Downtime or data loss is unacceptable.”	Rubrik Agent Cloud	One-click rollback fixes agent mistakes in minutes
“Need proof the model will not say something awful.”	Adversa AI	Draws on more than 5,000 academic works, covering 60-plus vulnerability classes
“Agents execute live code near production.”	Edera Safe Agents	Spins up a micro-VM with 0.8 ms spawn time

Most mature stacks converge on three layers: identity governance, runtime defense, and rollback. Start where the risk keeps you up at night, then expand.