AI agents are already in your environment. Identity is the control point.
AI agents act for your teams but run on their own, at machine speed. They reach systems, call tools and cross your environment faster than anyone can review by hand.
Most organizations cannot see which agents are running, what they can reach, or what they have already done. Traditional identity tooling was never designed for an identity that acts without a person at the keyboard. Zero Standing Privileges is the operating model — OmniPriv is how you get there.
A new identity class needs a new level of control
An AI agent is owned by a person but is not that person. It authenticates like a machine identity, acts on its own, and may touch a dozen systems to complete a single task — reading a ticket, querying a database, opening a pull request, rotating a key.
That combination breaks the assumptions most access models rest on. Standing privilege, session-based review and manual sign-off all assume a human is the one doing the clicking. OmniPriv treats every agent as a first-class identity: its own verifiable credentials, its own permissions, its own audit trail.
- A verifiable identity of its own — never a borrowed human account
- An explicit tool allowlist, so it can only call what the task requires
- A data scope that bounds which records and resources it can read
- Human approval before any high-risk action is allowed to execute
The window between compromise and containment keeps shrinking
Attackers are getting faster, and the same automation that helps your teams also helps them find and exploit weaknesses before anyone can respond. What does not change is what they are after: credentials, access, and the systems sitting behind them.
This is not a moment to wait and see. Scoped agents, injected credentials and recorded sessions remove the standing privilege that makes a breach worth pursuing in the first place.
How OmniPriv secures AI agents
Securing AI agents is an identity problem. OmniPriv solves it across four areas: visibility, runtime enforcement, credential protection and session accountability.
Visibility
You cannot govern what you cannot see. OmniPriv inventories the agents, MCP servers and tools running in your environment, maps what each one can reach, and surfaces shadow AI that nobody registered.
Runtime enforcement
Checking access at the door is not enough. OmniPriv evaluates every action — each tool call, query and command — against policy before it runs. Anything outside policy is blocked before it executes rather than interrupted partway through, and prompt-injection attempts are stopped at the same boundary.
Credential protection
Agents are routinely granted more access than any single task needs. OmniPriv sits as a proxy between the agent and the databases, servers and cloud services it connects to. Access is scoped to the task, issued just-in-time, and the agent never holds the raw credential. With no standing access, there is nothing to steal.
Session accountability
Every action ties back to a specific identity — the person directing the agent, or the service account it runs under. OmniPriv records each session in full, and behavioural analytics surface risky patterns and explain what happened. When an auditor asks what your agents did, you have an answer.
Governance you can point at
Agent security is not a policy document. These are the controls running behind it.
The controls are in place. Put them to work.
OmniPriv secures every identity in your environment — human, machine and AI.
Every agent governed. Every credential protected. Every session recorded and explained.
Nothing standing. Nothing shared. Nothing unrecorded.
Frequently Asked Questions
Common questions about governing autonomous AI agents under privileged access management.
AI agent governance is the practice of giving every autonomous agent a verifiable identity, an explicit set of permitted tools, a bounded data scope and a recorded session history — so an agent can do its job without holding privileges nobody is watching.
Each MCP agent is registered as its own identity rather than borrowing a human account or sharing a service account. Credentials are issued to that identity just-in-time and revoked when the task ends.
A tool allowlist names the specific tools and MCP servers an agent is permitted to call. Everything else is refused at policy evaluation, which limits how far an agent can reach if it is manipulated or misconfigured.
Yes. Actions classified as high risk are held for human approval before they execute. OmniPriv approval workflows support multiple approvers and time-based conditions, and no requester can approve their own request.