Security and governance
Give AI agents governed access to real business data.
ObjectOS comes in three editions, ObjectOS Community, Cloud and Enterprise. It lets agents read, analyze, and move work forward inside explicit boundaries for identity, permissions, tools, approvals, and audit. On ObjectOS Enterprise, data stays on your infrastructure; on every edition, every AI action is constrained by the ObjectStack runtime.
- Agent
- inherits user identity
- Tool
- governed access path
- Audit
- approval and evidence
How agents act
AI agent safety model
ObjectOS does not treat the model as an administrator. Agents work through business objects and use declarative tools to query, analyze, or trigger actions. Tool input is validated, every call is checked against the same permission system, and the in-product AI changes a record only after the user confirms it.
- 01
Acts as a user
An agent represents a signed-in user, not an unrestricted service account. If the user cannot see a record, the agent cannot see it either.
- 02
Uses governed tools
Agents call structured query, action, and metadata tools instead of holding raw database credentials or dumping whole tables into prompts.
- 03
Waits for a person
The in-product AI proposes a record change with the old and new values, and runs it as the user only after that user confirms. On ObjectOS Cloud, an AI Builder change to a live app that already holds records is saved as a draft for a person to publish.
- 04
Leaves evidence
Record reads and writes, approvals, rejections, and permission changes are written to the audit log. Per-call audit of the in-app AI’s tool calls is part of AI governance on Enterprise.
Where data lives
Data residency
ObjectOS Enterprise does not require moving business data into our cloud: the ObjectStack runtime connects to your databases, storage, and identity systems, so residency follows your deployment boundary.
| Data | Location | Leaves boundary? |
|---|---|---|
| Business records | Your database | No |
| Users, sessions, OAuth tokens | Your database | No |
| Audit logs | Your database | No |
| Uploaded files | Local disk, S3, or R2 | No |
| Secrets and settings | Your secret manager or encrypted settings store | No |
| AI request context | Your chosen model provider or local model | Only if you configure an external model |
Go deeper
The two pages behind this one
This page is the entry point for a security review. Two pages go further: the trust center collects the review materials, and the permissions page shows the access model as metadata a reviewer can read.
Trust center
Data residency, deployment paths, identity, approvals, audit, and the security review packet a reviewer should receive before sign-off.
Open the trust centerPermissions & security
Role, row, and field-level control declared beside the objects it protects, with the permission set a reviewer reads as a diff, enforced on people and agents alike.
Open the permissions pageWhere it runs
Deployment boundary
ObjectOS Enterprise can operate ObjectStack inside your network: one Node.js runtime, your database, your secrets, and your ingress. Stricter environments can use file-backed artifacts and offline images.
VPC / private network
Run in your cloud account or private network with only required HTTP/HTTPS and database connectivity.
Local servers
Run with Docker, systemd, or your own platform while connecting local databases, object storage, and identity.
Air-gapped
Use offline container images and a local objectstack.json artifact with no cloud control plane or public internet requirement.
Local models
Point AI services at Ollama, vLLM, or internal model endpoints to keep business context inside your boundary.
FAQ
Security review FAQ
Does ObjectOS phone home?
Self-managed ObjectOS validates its license online; Enterprise air-gapped licenses validate offline. Beyond that, unless you explicitly configure integrations such as OIDC, email, AI providers, webhooks, or external storage, no business data leaves your deployment. The open-source ObjectStack runtime has no telemetry, no license check, and no update ping.
What goes to a model provider?
Only the context required for the model task: conversation context, tool definitions, and necessary tool output. You can use an external model or configure a local model endpoint.
How do we limit agent writes?
Use read-only data sources, object permissions, field permissions, action permissions, and flow approval steps for business decisions. Agents cannot bypass runtime permissions. The in-product AI changes one record at a time after the user confirms it, and cannot delete records or edit them in bulk; on ObjectOS Cloud, an AI Builder change to a live app that already holds records is saved as a draft for a person to publish.
Who owns TLS, database encryption, and secrets?
Those are deployment responsibilities. The ObjectStack runtime provides authorization, audit, API key hashing, and settings encryption; your infrastructure owns TLS, at-rest database encryption, backups, and secret injection.
Is it suitable for regulated environments?
ObjectOS provides the technical primitives: access control, audit, data residency, and isolated deployment. Certification depends on your running deployment, not a binary alone.
Found a vulnerability?
Vulnerability disclosure
Report security problems in ObjectOS Cloud, ObjectOS Enterprise, the open-source ObjectStack runtime and packages, or this website privately by e-mail. Please do not open a public GitHub issue, discussion, or pull request for a security problem.
- Report to
- [email protected]
- Acknowledgement
- Within one business day
- Languages
- English or Chinese
What to include
- The product and version affected: for Cloud, the date and time you tested; for a self-managed deployment, the image or package version.
- Steps to reproduce, with a proof of concept if you have one.
- The impact you observed: what an attacker could read, change, or run.
- Whether you have shared the finding with anyone else, and when you plan to publish it.
- How to reach you, and the name you want credited, if any.
What happens next
- We acknowledge your report within one business day.
- We confirm or rule out the issue and keep you updated while we fix it.
- Once a fix is available, we agree a public disclosure date with you and credit you if you want.
Safe harbour
We consider good-faith security research under this policy authorized, and we will not bring or support legal action against you for it. Good faith means you:
- Test only accounts and environments you own or have permission to use, and stop as soon as you reach data that is not yours.
- Do not view, keep, change, or delete other people’s data beyond the minimum needed to show the issue.
- Do not run denial-of-service, spam, social-engineering, or physical attacks.
- Give us reasonable time to fix the issue before you disclose it publicly.
Next step
Let agents work with business data without crossing the boundary.
Confirm how agents identify users, access objects, trigger actions, enter approval, and leave audit evidence before connecting them to production data.