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AI-Powered, Real-time Person-Based Continuous Verification

AI-native Mimoto provides person-based continuous verification and automated response to stop active inauthentic user malicious activity and agentic attack, for use cases such as continuous assurance for insider threats, nation-state threats, and remote workers/offshore developers.

Mimoto’s core capabilities are continuously recognizing and responding in real-time when a user is being impersonated by a person or agent, a session is taken over, or a credential is shared or compromised. Additionally, its ability to distinguish between humans and agents enables it to discover homegrown agentic AI introduced into enterprise environments and divert agents pretending to be people in web applications or on website.

Mimoto’s Continuous Identity Authentication extends identity verification beyond the login event and throughout the duration of user activity, answering a significant User Pillar requirement in the DoD Zero Trust Capability Execution Roadmap, which has a stated outcomes of authenticating and authorizing users continuously within and across sessions and pairing this with a requirement to use behavioral and contextual telemetry to strengthen risk-based access. Mimoto fulfills this stated mandate which is lacking in most environments.

By integrating behavioral analytics and dynamic trust assessments into existing Zero Trust architectures, the Mimoto strengthens resilience against credential-based attacks while maintaining mission effectiveness. With Mimoto, identity changes from a static, point-in-time event to become a continuously evaluated security signal — one that feeds risk-based access decisions, automated response, and enterprise analytics.
While the Zero Trust model is rigorous about what is connecting, it’s comparatively silent about who is actually present once a session is underway. Mimoto was designed to address the vulnerabilities Zero Trust and other legacy solutions don’t address:

  • Authentication proves possession, not presence.
  • Session artifacts carry identity forward unexamined.
  • Policy engines evaluate attributes, not people.
  • Device health is mistaken for user legitimacy.
  • Step-up authentication is triggered by events, not by identity drift.
  • Privileged access is checked at the vault door, not during the session.
  • Federation imports another authority's point-in-time decision.
  • Walk-away and shared-terminal scenarios generate no signal.
  • Human accounts increasingly carry non-human operators.

Each of these gaps shares a single root cause: the architecture verifies the artifact of identity — a credential, a token, an assertion — rather than the person the artifact is supposed to represent.

Mimoto is designed to answer three important questions:
Is it a human?
Is it the right human?
Is the right human doing the right thing?

FAQ

Does Zero Trust ensure the person or agent accessing systems and devices is the correct user?

While the Zero Trust model is rigorous about what is connecting, it’s comparatively silent about who is actually present once a session is underway. Mimoto was designed to address the vulnerabilities Zero Trust and other legacy solutions don’t address:

  • Authentication proves possession, not presence.
  • Session artifacts carry identity forward unexamined.
  • Policy engines evaluate attributes, not people.
  • Device health is mistaken for user legitimacy.
  • Step-up authentication is triggered by events, not by identity drift.
  • Privileged access is checked at the vault door, not during the session.
  • Federation imports another authority's point-in-time decision.
  • Walk-away and shared-terminal scenarios generate no signal.
  • Human accounts increasingly carry non-human operators.
How can nation-state threats posing as qualified worker be caught?

Mimoto catches and responds in real-time to nation-state threats by recognizing and responding in real-time when: 1. a user is being impersonated; 2. a remote worker or contracted developer has changed; 3. a credential is shared or compromised; 4. the new employee is different than the person who interviewed in the hiring process; and 5. when a sanctioned laptop is in a laptop farm.

How can you catch an agentic attack before damage is done?

Catching an agentic attack before damage is done requires recognizing and responding in real-time to a combination of advanced pattern matching that recognizes the user (human, machine, or agent) and anomaly detection. There are five steps in an agentic attack - jailbreak, recon, exploit, harvest, and extract. All five steps must be addressed for full cybersecurity protection.