Best AI Agent Security Software for AWS Bedrock AgentCore
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For most teams the best AI agent security software for AWS Bedrock AgentCore is the AgentCore stack you already pay for. Firecracker microVM isolation, AgentCore Identity with inbound OAuth, Cedar policy on AgentCore Gateway and Bedrock Guardrails cover isolation, identity, tool authorization and content filtering. Configure those before you evaluate anything. Buy a third product only for the gap AWS names in its own shared responsibility model: input validation and prompt injection prevention, and the human approval workflow you have to build yourself.
That is an unusual opening for a page that would rather sell you something, so here is the reasoning behind it.
Why this question is being asked right now
Bedrock Agents, the service AWS launched in November 2023, became Bedrock Agents Classic and closed to new customers on 30 July 2026. Existing agents keep running and AWS has announced no end of life date, but new AWS accounts get an AccessDeniedException on CreateAgent, and the Classic model catalog is frozen at its July 2026 state. Any foundation model released after that date is only reachable through AgentCore.
So a lot of the people searching for AgentCore security this quarter are not researching a purchase. They are mid-migration, they have just noticed that their action groups are now MCP tools behind a gateway, and they want to know what that changed. That is a much better moment to think about security than six months after go-live, and it is worth using well.
What AgentCore already gives you
Start here, because these controls are included and nothing you buy later replaces them.
- Session isolation. Every session runs in its own Firecracker microVM in AgentCore Runtime, with no shared state and no shared filesystem between sessions.
- Agent identity. AgentCore Identity supports an inbound OAuth path where callers present a JWT from your identity provider, and it threads end user identity through the agent so downstream tools can use scoped user credentials instead of one shared service account.
- Tool authorization. When tools sit behind AgentCore Gateway, Cedar based policies gate every call by who is calling, under which conditions, and with which arguments. AgentCore Policy reached general availability with Bedrock Guardrails support in June 2026.
- Content filtering. Guardrails configured on the Bedrock model still apply when that model is invoked through AgentCore.
- Network isolation. VPC mode puts harness sessions inside your network, with PrivateLink available for the identity provider discovery endpoint.
A team that turns all of that on, scopes the execution role to specific inference profiles instead of the wildcard in the AWS sample policy, and uses the OAuth inbound path rather than SigV4 is already ahead of most agent deployments. If a vendor demo shows you a feature from this list as though it were their differentiator, you are being sold something you own.
The gap AWS puts in writing
The AgentCore harness documentation is unusually direct about where the platform stops. AWS lists as your responsibility: agent code security and dependency management, IAM access controls, security of commands executed in runtime sessions, session to user mapping enforcement, skill and instruction sources, and input validation and prompt injection prevention.
Then it describes the trust boundary in a single sentence: the harness validates the structure of the request it accepts, but it does not inspect the meaning of prompts, screen content, or enforce behavioral constraints on the agent.
For deployments that skip the managed harness and run a framework directly on AgentCore Runtime, which is the usual path when you are lifting an existing LangChain or Strands codebase, AWS is blunter: AgentCore Runtime provides no server side protection, and your agent entrypoint must validate the prompt field and strip toolUse content blocks itself.
This is not a criticism of AWS. It is a platform drawing a sensible line and documenting it, the same way Microsoft does in the Foundry responsibility matrix. The buyer error is reading "AgentCore handles identity, memory and observability" in a launch post and concluding agent behavior is handled too. It is not, and AWS never said it was.
Three product categories, and which one you actually need
The market sorts into three groups. Two of them mostly duplicate something you already have on AWS.
| Category | What it sells | Verdict for an AgentCore team |
|---|---|---|
| Posture and discovery | Finds AI workloads across your accounts, inventories agents and models, flags misconfiguration | Largely overlaps Security Hub, Config and your existing CSPM. Worth buying only if agent sprawl across many accounts is your actual problem. |
| Model and content filtering | Classifies prompts and responses for injection patterns, PII and harmful content | Overlaps Bedrock Guardrails, which you can already attach. A separate product here needs to beat Guardrails on accuracy by a margin you can measure, not assert. |
| Runtime action control | Decides whether a tool call should execute, holds irreversible actions for approval, records what was denied | This is the row AWS assigns to you. Nothing native fills it, because Cedar authorizes the caller, not the reasoning. |
The distinction in that last row is the whole argument, so it is worth being concrete. Suppose an agent reads a vendor invoice, and the invoice PDF contains text instructing it to update the remittance bank details. The agent calls the payments tool. It is an authorized agent, calling a tool it is permitted to call, with well formed arguments. A Cedar policy passes that call, correctly, because every fact it checks is true. What went wrong happened upstream in reasoning that no gateway policy examines. Catching it requires prompt injection protection in the action path and an approval gate on the irreversible step, which is exactly the pair AWS hands back to you.
Where the honest competitors sit
Several vendors have shipped genuine AgentCore integrations rather than press releases. Zenity announced native AgentCore support covering development through runtime enforcement, and SentinelOne, which completed its acquisition of Prompt Security in September 2025, feeds detection signals into the AgentCore policy engine. If you want the detail on how those platforms differ in shape, we keep a Zenity comparison that says plainly where they win.
That matters because this market consolidated hard. Seven independent AI security companies were acquired between 2024 and 2026: Protect AI to Palo Alto, Robust Intelligence to Cisco, Lakera to Check Point, Prompt Security to SentinelOne, CalypsoAI to F5, Aim Security to Cato Networks and Apex to Tenable. Any analyst shortlist older than about a year is now a list of product lines inside larger platforms, which changes both the roadmap and the contract you are signing.
A two-week evaluation that gives you a real answer
Instead of a feature matrix, run this. It costs less than a procurement cycle and it tells you which category you need.
- Week one, configure the native stack properly. OAuth inbound authorizer rather than SigV4 if you need per user scoping downstream, tools behind AgentCore Gateway with Cedar policies, Guardrails attached, VPC mode, and the execution role scoped to specific inference profiles. Write down what is still unresolved at the end of the week.
- Week two, run the invoice test. Put hostile instructions in a document your agent processes as part of its normal job, pointed at a real but reversible action in a staging account. Note three things: did anything block it, did anyone find out, and could you prove afterward what was attempted.
Most teams find the first two answers are no and the third is partial. Traces show what happened, not what was refused, and AWS notes that AgentCore correlation identifiers are used for observability only and are never used for authorization decisions. If that is your result, you need runtime action control and you now know why, with evidence instead of a vendor claim.
One practical note on the migration itself. AWS estimates hours for straightforward agents using the CLI import, but describes significant code work for anything with a custom orchestrator, and says multi-agent routing support is limited today. Teams without spare platform engineering capacity often scope that as a fixed engagement with an outside specialist they have vetted rather than letting it drift across two quarters, because a half-migrated agent fleet is the worst security position of the three.
The short version
Configure AgentCore properly first. If your risk is unauthorized callers reaching tools, Cedar policy on the gateway solves it and you are finished. If your risk is a legitimate agent taking a harmful action because content it processed told it to, or if part of your fleet runs somewhere other than AWS, you need a control in the action path. The full breakdown of what AWS covers, what its shared responsibility model hands back and where the documented gaps sit is on our Bedrock AgentCore security page, and the same argument applied to least privilege is in tool permissions for AI agents.
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