Best AI Agent Security Tools and Platforms (2026)
TL;DR · the short version
AI agent security splits into two jobs: enforcing policy on agents at runtime, and deciding what that policy should be. Zenity and Noma Security each describe a platform for the first job; their own homepages (read 4 November 2026) claim discovery, runtime policy enforcement and threat detection. PlayCISO (ours) covers the second: labs, planners and checkers for tool permissions, approval tiers, credential brokering, egress containment and vendor boundary tests, plus a Free governance benchmark. The vendor statements are their own claims, not our testing.
AI agent security is two jobs: enforcing policy on agents at runtime, and deciding what that policy should be. Zenity and Noma Security each describe a platform for the first job. PlayCISO (ours) helps with the second, through labs, planners and checkers for tool permissions, approvals, credentials and containment. You can use both: decide the policy, then enforce it.
Disclosure: PlayCISO publishes this page and is listed below, labelled "ours". The Zenity and Noma statements are the vendors' own claims from their homepages, read on 4 November 2026; we did not test either product. PlayCISO is not a runtime enforcement platform.
The shortlist at a glance (as of 4 November 2026)
| Option | Job it does | What its page says (read 4 Nov 2026) |
|---|---|---|
| Zenity | Runtime agent security and governance (vendor claim) | "the first platform built specifically for agent security and governance"; stages Surface (discovery), Enforce (policy) and Protect (detection and response); threats mapped to OWASP and MITRE ATLAS |
| Noma Security | Runtime agent governance and pre-deployment testing (vendor claim) | "The Agent Security & Governance Platform"; "Agent governance happens at runtime"; evaluates each agent action against its session context and can stop, steer or escalate it |
| PlayCISO (ours) | Deciding and rehearsing the controls | Labs, planners and checkers listed below; one Free benchmark; several need a plan |
What each one is
Zenity
Zenity's homepage (read 4 November 2026) says it "secures long-horizon AI agents" and governs "how it's built, what it can access, and what it does". It describes three stages: Surface for discovery, Enforce for policy and Protect for detection and response, with threats mapped to OWASP and MITRE ATLAS. That is the vendor's positioning; the page does not show independent test results.
Noma Security
Noma's homepage (read 4 November 2026) calls its product "The Agent Security & Governance Platform that helps enterprise security teams enable agent adoption without losing control". It says governance "happens at runtime", that it evaluates each agent action against the wider session (whom the agent acts for, what data it can reach) and can stop, steer or escalate, and that it offers pre-deployment testing for supply chain risks, misconfigurations and multi-turn attacks. Again, vendor claims.
PlayCISO (ours)
We do not sit in your agents' path. We help you decide and rehearse the controls that a platform or your own code must enforce:
- AI Agent Governance Benchmark (Free): your kill switch, tracing, policy and shadow-agent answers beside two published surveys.
- Agent Credential Broker Lab (Free): keep secrets out of the agent's reach.
- Agent Tool Scope Lab (needs a plan): choose the decision and scoping control for each tool grant.
- Agent Egress Containment Lab (needs a plan): decide what an agent's executor may reach.
- Agent Action Approval Policy Builder: rate action risk and get an approval policy document.
- Agent Governance Plane (needs a plan): a nine-component reference architecture with a self-score. See also the write-up.
- Agent Vendor Boundary Test Kit: a printable test plan for managed agent products.
A control plane checklist to use with any vendor
- Identity: each agent has its own identity, not a shared service account.
- Permissions: narrowest tool scopes; write, send, pay and delete are separate grants.
- Secrets: credentials brokered per call, never placed in the prompt or memory.
- Policy: enforced at the tool boundary, outside the model.
- Approval: a human gate for high-risk actions, with a named approver.
- Audit: a replayable trace of every tool call and a tested kill switch.
How we compared
- We separated runtime enforcement platforms from decision and training tools because they solve different problems.
- For Zenity and Noma we quote their own homepages, read 4 November 2026. We did not run either product and make no effectiveness claims.
- No prices: neither page we read gave one we could use.
- PlayCISO is ours. Items marked Free are Free; others need a plan.
Frequently asked questions
What are the best AI agent security tools and platforms?
Two commercial platforms describe agent security as their core product: Zenity ("the first platform built specifically for agent security and governance", with discovery, policy enforcement, and detection and response stages) and Noma Security ("The Agent Security & Governance Platform", with runtime governance and pre-deployment testing). Those are the vendors' own descriptions, read on 4 November 2026. PlayCISO (ours) is not a runtime platform: it offers labs, planners and checkers that help you decide permissions, approvals and containment before you buy or build one.
How do you design a control plane for AI agents (permissions, secrets, policy, audit trails)?
Give each agent its own identity, grant the narrowest tool permissions that do the job, keep secrets out of the agent's context by brokering credentials per call, enforce policy outside the model at the tool boundary, route risky actions to a human approval, and record a trace of every tool call that you can replay. Our reference architecture and the labs below walk each component.
How do you restrict which actions an AI agent is allowed to take?
List each tool the agent can call, rate the risk of each action (read, write, send, pay, delete, deploy), and set an approval tier per action. Enforce it in code at the tool layer, not in the prompt, because a prompt instruction can be overridden by injected text. Log denied actions; they show you what the agent tried.
Do I need an agent security platform, or are labs and checklists enough?
Labs and checklists build the judgement to specify what you need and to test a vendor's claims. A runtime platform enforces policy across many agents at scale. Small deployments with a few agents can often start with scoped permissions, approval gates and tracing. Ask any vendor to demonstrate a blocked action in your environment.
How can I test whether an AI agent product contains an attacker who controls the agent?
Use a boundary test plan: check what credentials the agent can read, what it can reach on the network including DNS and metadata endpoints, what it can change, whether actions are audited, and whether you can stop it. Our Agent Vendor Boundary Test Kit lists defensive checks for managed agent products.
Sources
- Zenity homepage, read 4 November 2026
- Noma Security homepage, read 4 November 2026