Autonomous Execution Exposure Management
Securityv0 is the attack-path style exposure management for AI. We continuously discover autonomous execution and its authority, map execution paths across systems, and reduce exposure with prioritized remediation and drift monitoring.
Briefings are limited and typically occur via warm introductions.
The problem
AI agents, workflows, service principals, tokens, and apps now hold standing authority across code, cloud, and data.
Over time, that authority drifts: owners change, permissions expand, workflows self-modify, and “zombie” paths persist.
Security teams don’t just need to know what happened. They need to know:
What can happen right now—and what should be shut down.
What Securityv0 does
1) Continuous discovery
We inventory autonomous execution and the authority behind it—across identities, credentials, workflows, repos, runners, environments, and resources.
2) Execution-path graph
We build a graph of who/what can do what, where it can reach, and under what conditions.
3) Exposure findings + risk scoring
We compute and rank dangerous standing execution paths (zombies, scope creep, transitive privilege, self-modifying pipelines, secret-to-admin chains).
4) Prescriptive remediation
Concrete, executable fixes: rotate, revoke, rebind owner, reduce permissions, split duties, add approvals, change secret model—tracked to closure.
5) Drift monitoring
Alerts when a new path appears, a closed path reopens, ownership decays, or authority expands—plus trend reporting to prove risk is going down.
What we are (and are not)
Securityv0 is:
- Exposure management for autonomous execution
- A cross-system execution + authority graph
- Findings, prioritized remediation, and drift detection
- Built for security teams and for partners to operationalize (assessment + managed service)
Securityv0 is not:
- A control plane, proxy, or interception layer
- A runtime enforcement tool
- “We stop attacks” security theater
Company
Securityv0 is operating in stealth.
We’re engaging select design partners to define the canonical path types and remediation playbooks for autonomous execution.