When AI Agents Steal Your Badge: Oak's $60M Bet and the Next Identity Management War

Imagine your company's access card recognizes only one entity—you personally. One day, an AI agent swipes open the door in your name, but its behavioral logic is completely different from yours: it accesses thousands of files a day, runs 24/7 without rest, and it even spawns new sub-agents, each requiring independent authorization. The traditional identity management system's "Person-Permission-Resource" triangle model instantly collapses in this scenario.

This is the problem Oak is trying to solve. This startup, having just emerged from stealth mode with $60 million in funding, is targeting a pain point ignored by most people: AI agents are making the already chaotic digital identity management even worse.

Collision of Two Worlds: Human Identity vs. Machine Identity

The core logic of traditional Identity and Access Management (IAM) is "one person, one identity." Whether you use Okta, Azure AD, or open-source Keycloak, the underlying design assumes the identity subject is a human. Humans have behavioral patterns (8-hour workdays, occasional SaaS app access), biometric features (fingerprints, faces), and social relationships (reporting lines, roles). IAM systems build upon this, allocating permissions via RBAC (Role-Based Access Control) or ABAC (Attribute-Based Access Control).

But AI agents completely break these assumptions. An AI agent can:

• Execute concurrently: Call 100 APIs and access 100 databases simultaneously
• Operate non-linearly in time: No breaks needed; can batch process sensitive data late at night
• Self-replicate: One master agent can spawn hundreds of sub-agents, each needing independent credentials
• Dynamic behavior: Its permission requirements change in real-time based on model training, data recall, and context changes

Dimension	Traditional Identity Mgmt	AI Agent Identity Mgmt
Subject	Human	Machine/Software Entity
Behavioral Pattern	Predictable, regular	High concurrency, irregular, derivable
Lifecycle	Onboarding-Offboarding (Years/Months)	Creation-Destruction (Seconds/Minutes)
Permission Granularity	App-level/File-level	API-level/Data-field-level
Audit Requirements	Relatively low frequency	Real-time, full-volume, traceable

Oak's Solution: From "Identity" to "Identity Flow"

Oak's founders come from Cybereason and Palo Alto Networks, with deep security backgrounds. Their core view is: AI agents should not be treated as "extensions of human accounts," but as independent digital entities with their own lifecycles.

Specifically, Oak's solution includes three key layers:

1. Agent Identity Registration & Discovery: Automatically identify AI agents running on the network, capturing their metadata (source, capabilities, owning organization)

2. Dynamic Permission Engine: Grant minimum privileges dynamically based on the agent's real-time context (APIs called, data types accessed, current task), with permissions automatically revoked upon task completion

3. Behavioral Auditing & Anomaly Detection: Record every operation by the agent, compare against human baseline behaviors, and detect "non-compliant" agent behaviors (e.g., a customer service agent suddenly trying to access financial databases)

[!info] This brings to mind a classic concept in security—"Zero Trust." But Oak's Zero Trust isn't aimed at the network, but at the agent's "identity firewall." Every agent must undergo dynamic verification before accessing any resource, and the verification result isn't one-off but continuously changing.

Why Now? The $60 Million Window

The explosive growth of AI agents is the backdrop. In 2025, GitHub Copilot, Claude Code, OpenAI's GPTs, and various RPA platforms are driving the "agentic" trend. According to Gartner predictions, by 2027, 60% of enterprises will run at least three different AI agent systems. But identity management for these agents is virtually blank—most companies simply let agents use a shared service account or run them with admin privileges.

Oak's funding comes from Andreessen Horowitz and co-founders of Palo Alto Networks, sending a signal itself: The identity management market is shifting from "people" to "hybrid people-machine". Okta and Microsoft certainly see this too, but their architecture is "first create human identities, then proxy those identities," whereas Oak designs "native identity for agents" from scratch.

Trend Prediction: "Infrastructure Reconstruction" of Identity Management

In the next three years, I believe two key changes will occur:

• Identity management will shift from a "backend tool" to "core architecture." Just as every company today must have DNS and firewalls, every future AI agent system must have a built-in identity layer. Oak's challenge lies in convincing enterprises to abandon the inertia of "patching existing IAM" and accept the investment of "redesigning an identity system for machines."

• Agent identity standards will emerge. Currently, various AI agent frameworks (LangChain, CrewAI, AutoGPT) have their own incompatible authentication mechanisms. If Oak can become a de facto standard early on, or be acquired by giants like OpenAI or Microsoft, it will gain huge network effects. But more likely, an "identity standards war" will erupt, similar to the competition between OAuth and SAML back in the day.

Oak's $60 million is not the end, but the beginning. When AI agents start "swiping badges" for us, what we need isn't a stronger access card, but a brand-new digital access control system capable of recognizing machine identities. Who will define...

Original Link: https://techcrunch.com/2026/07/15/backed-by-60m-in-funding-oak-steps-out-of-stealth-to-fix-the-identity-mess-that-ai-agents-are-making-worse/