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Passing enterprise security reviews with agents

12 min read

Enterprise buyers like AI agents—but not ungoverned writes. A practical checklist for passing security review without watering your product down to read-only.

Enterprise buyers like the promise of AI agents. What they do not like is ungoverned software that can write into production systems.

If your agent can create tickets, update CRM records, change configs, or call internal APIs, you will eventually face a security review that asks a simple question:

"How do you control and prove what this agent is allowed to do?"

This post is a practical checklist for passing that review without watering your product down into "read-only."

The core objection enterprises have to agents

Enterprises are not rejecting "AI." They are rejecting three specific risks:

  1. Unknown actor: who is actually performing the write?
  2. Unbounded behavior: what stops the agent from doing the wrong thing?
  3. Weak evidence: how do we investigate and prove what happened later?

If you can answer those three, most reviews become straightforward.

1) Treat the agent as a first-class identity

Most early agent products fail security reviews because they behave like a shared bot with a single API key.

Security teams want:

  • a distinct identity for the agent (not a shared human account)
  • the ability to revoke and rotate credentials
  • clear ownership (who is responsible for this agent)

What to be ready to show:

  • "This is the agent identity model"
  • "This is how we authenticate agent instances"
  • "This is how we revoke access immediately"

If you cannot answer "which agent instance did this," you will be pushed into overly restrictive permissions.

2) Start with least privilege that is meaningful

Enterprises do not want "it has access to Salesforce." They want "it can update these fields on these records under these conditions."

Your most convincing security story is policy at the level of:

  • action type
  • resource scope
  • field and threshold constraints
  • environment boundaries (staging vs prod)

What to show:

  • a clear list of actions your agent can perform
  • what it cannot do
  • how scoping works (per customer, per project, per resource)

A strong answer sounds like:

"Our agent can do X on Y, but cannot do Z, and here's the enforcement point."

3) Have an approval story for high-risk actions

Security reviewers will ask:

"What stops the agent from closing incidents, changing permissions, or moving money?"

Even if you do not do those exact actions, the pattern matters.

A pragmatic approach:

  • low-risk actions: auto-allowed within strict limits
  • high-risk actions: require explicit human approval
  • prohibited actions: denied

What to show:

  • where approvals are required
  • who can approve
  • what the approver sees (clear, contextual prompt)
  • how approvals are recorded

If you do not have approvals, enterprise teams will require you to restrict your agent to "suggestions only," which reduces product value.

4) Create an audit trail that is actually usable

Many products say "we log everything." Enterprises hear:

"We will not be able to investigate incidents."

Your audit story should answer:

  • who acted
  • what was attempted
  • what policy allowed or blocked it
  • whether a human approved it
  • whether the write succeeded or failed

What to show:

  • a "receipt" or "action history" view
  • export or integration path (even if it is basic in v0)
  • retention policy and access controls for logs

The quality bar is not "logs exist." It is "security can reconstruct what happened quickly."

5) Be clear about where data flows and where it is stored

This is where most reviews stall.

Be ready to answer:

  • Does customer data leave their environment?
  • Do prompts or tool payloads get stored?
  • What is retained, for how long, and why?
  • Can sensitive fields be excluded?

Strong posture:

  • minimize what you store
  • provide redaction and retention controls
  • keep secrets out of logs by design

Even if you are early, a clear written data-handling policy goes a long way.

6) Secrets and tool credentials must be handled centrally

Enterprises will ask:

  • "Where are tool credentials stored?"
  • "How do you rotate them?"
  • "Can you restrict them to least privilege?"

If your agent runs with a broad customer API key, you will lose trust.

What to show:

  • a credential management approach (vault, KMS, managed secrets)
  • rotation story
  • environment separation (dev/staging/prod)

7) Show you understand isolation boundaries

Even in v0, you need a coherent story for:

  • per-tenant separation
  • production vs staging separation
  • internal admin access controls
  • incident response procedures

You do not need perfect enterprise-grade implementation on day one, but you do need clarity on the boundary model.

8) Provide a deployment model that fits enterprise reality

Many enterprises prefer:

  • private networking (VPC / private link)
  • restricted ingress
  • customer-controlled egress
  • region control

If you cannot offer that in v0, do not pretend you can. Instead:

  • explain what you support now
  • explain what is on the roadmap
  • explain what mitigations exist today

A clean, honest deployment story beats vague enterprise promises.

9) Make your security review package easy to consume

You will win reviews faster if you proactively provide:

  • architecture diagram (agent → control plane → tools)
  • threat model summary
  • data handling and retention summary
  • access control model
  • audit/receipt examples
  • approvals behavior summary
  • incident response contact and SLAs (even if lightweight)

The goal is to reduce the reviewer's workload.

A simple enterprise review checklist (copy/paste)

If you want a concrete "are we ready" checklist:

Identity and access

  • agents have distinct identities
  • credentials are revocable and rotatable
  • ownership is defined

Least privilege and control

  • actions are scoped (not tool-wide)
  • high-risk actions require approval
  • prohibited actions are blocked

Audit and evidence

  • every action is recorded
  • approvals are attributable
  • investigation is fast and reliable

Data handling

  • data collection is minimized
  • sensitive fields can be excluded
  • retention is defined

Secrets and deployments

  • secrets are centrally managed
  • environments are separated
  • networking boundaries are clear

If you can answer these confidently, you will pass most security reviews.

How Relynt helps

Relynt exists because most agent products try to bolt these controls on later.

A purpose-built authorization layer for agent actions gives you:

  • agent identity and traceability
  • least privilege at the action level
  • approvals for high-risk writes
  • signed receipts as audit evidence

That is the difference between "an agent that can do things" and "an agent that an enterprise will let into production."

The takeaway

Enterprise security reviews are not anti-agent. They are pro-control.

If you build agents with:

  • clear identity
  • meaningful least privilege
  • approval gates for high risk actions
  • audit-ready evidence
  • sane data handling

…you can ship automation that enterprises will actually adopt.

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