Agentic AI

Zero trust identity and access for AI agents

Octelium is a free and open source, self-hosted zero trust access platform. An agent gets an identity of its own rather than a copy of someone's credentials, reaches resources through a proxy that holds the secrets, has each tool call and each inference request authorized on its own, and leaves an audit trail that names it.

  • Free and open source
  • Designed for self-hosting
  • MCP and LLM gateway modes

Every request from a human, a browser, a CLI, a workload or an AI agent is authenticated against your identity providers, authorized per request at the application layer by the Octelium Service in front of the resource, exported to your SIEM and observability stack whether it is allowed or denied, and only then routed to the upstream HTTP API, database, SSH server, Kubernetes cluster, LLM or MCP server.

Signing in once, then reaching Services with and without a client

  • A browser opens grafana.acme.com and is redirected to the Cluster sign-in page at acme.com/login.
  • jane signs in with a passkey verified by a biometric on the device, and the browser returns to the Grafana dashboard at grafana.acme.com with no client installed.
  • In a terminal, octelium connect -d opens the browser at acme.com/callback/success/approval, where the same browser session approves the login with one click.
  • ~ ❯ octelium connect -d
  • Please authenticate yourself using Octelium web Portal
  • Waiting for you to approve the login in your browser. Press Ctrl-C to cancel.
  • You are now authenticated as jane
  • Octelium has started running in detached mode.
  • ~ ❯ curl -s my-api/v1/users/42 | jq
  • {
  • "id": 42,
  • "name": "Jane Doe",
  • "email": "jane@acme.com"
  • }
  • ~ ❯ psql -h pg-prod -d shop
  • psql (17.4)
  • Type "help" for help.
  • shop=> SELECT * FROM orders LIMIT 3;
  • id | status | total
  • -----+---------+--------
  • 981 | paid | 129.00
  • 982 | shipped | 48.50
  • 983 | paid | 310.25
  • (3 rows)
  • shop=> \q
  • ~ ❯ ssh bastion
  • Welcome to Ubuntu 24.04.1 LTS (GNU/Linux 6.8.0-1021-aws x86_64)

Requests authorized one by one against CEL rules in the HTTP, LLM and Kubernetes modes

  • HTTP: the HTTP Service billing is configured as follows.
  • kind: Service
  • metadata:
  • name: billing
  • spec:
  • mode: HTTP
  • config:
  • authorization:
  • inlinePolicies:
  • - spec:
  • rules:
  • - effect: ALLOW
  • condition:
  • all:
  • of:
  • - match: '"finance" in ctx.user.spec.groups'
  • - match: ctx.request.http.method == "GET"
  • - match: ctx.request.http.path.startsWith("/invoices")
  • jane, a member of the finance Group, runs curl -i billing/invoices/42 and gets HTTP/1.1 200 OK Content-Type: application/json {"id":42,"status":"paid","total":1290}. The access log records ALLOWED GET /invoices/42 with POLICY_MATCH.
  • jane, a member of the finance Group, runs curl -i -X DELETE billing/invoices/42 and gets HTTP/1.1 403 Forbidden X-Octelium-Unauthorized: true Content-Length: 0. The access log records DENIED DELETE /invoices/42 with NO_POLICY_MATCH.
  • LLM: the LLM Service openai is configured as follows.
  • kind: Service
  • metadata:
  • name: openai
  • spec:
  • mode: LLM
  • config:
  • authorization:
  • inlinePolicies:
  • - spec:
  • rules:
  • - effect: ALLOW
  • condition:
  • any:
  • of:
  • - match: '"ai-admins" in ctx.user.spec.groups'
  • - all:
  • of:
  • - match: '"ai-agents" in ctx.user.spec.groups'
  • - match: ctx.request.llm.operation == "GENERATE"
  • - match: ctx.request.llm.model == "gpt-5-mini"
  • support-bot, a member of the ai-agents Group, runs curl openai/v1/responses --json '{"model":"gpt-5-mini","input":"Hello"}' and gets { "id": "resp_68e8e1f0c4d0", "object": "response", "created_at": 1791628935, "status": "completed", "model": "gpt-5-mini-2025-08-07",. The access log records ALLOWED RESPONSES gpt-5-mini with POLICY_MATCH.
  • support-bot, a member of the ai-agents Group, runs curl openai/v1/responses --json '{"model":"gpt-5","input":"Hello"}' and gets {"error":{"message":"Octelium: unauthorized request","type":"permission_error","param":null,"code":"octelium_unauthorized"}}. The access log records DENIED RESPONSES gpt-5 with NO_POLICY_MATCH.
  • Kubernetes: the KUBERNETES Service k8s-prod is configured as follows.
  • kind: Service
  • metadata:
  • name: k8s-prod
  • spec:
  • mode: KUBERNETES
  • config:
  • authorization:
  • inlinePolicies:
  • - spec:
  • rules:
  • - effect: ALLOW
  • condition:
  • all:
  • of:
  • - match: '"sre-agents" in ctx.user.spec.groups'
  • - match: ctx.request.kubernetes.verb in ["get", "list"]
  • - match: ctx.request.kubernetes.namespace == "production"
  • - not: ctx.request.kubernetes.resource == "secrets"
  • ops-agent, a member of the sre-agents Group, runs kubectl get configmaps -n production and gets NAME DATA AGE app-config 4 12d feature-flags 2 3d kube-root-ca.crt 1 12d. The access log records ALLOWED list configmaps · production with POLICY_MATCH.
  • ops-agent, a member of the sre-agents Group, runs kubectl get secrets -n production and gets Error from server (Forbidden): Octelium: Unauthorized request. The access log records DENIED list secrets · production with NO_POLICY_MATCH.
Secretless access

Credentials an agent never holds

Application-layer credentials are stored in the Cluster as Secrets and injected into the upstream connection once a request is authorized. This is the part of the problem that grows fastest with agentic systems, because the number of non-human identities holding credentials grows faster than the number of people.

Read about secretless access

Upstream credentials injected per request by identity in the HTTP, SSH and PostgreSQL modes

  • HTTP: the HTTP Service stripe proxies https://api.stripe.com and picks the upstream credential of every request with dynamic configuration rules.
  • elena, a member of the finance-eu Group, runs curl -s stripe/v1/account | jq '{id, country}' without holding any credential. The rule "finance-eu" in ctx.user.spec.groups selects the eu config, so Octelium injects the Secret stripe-eu and the upstream authenticates the request as acct_1Pq8EuGmbH2bXvK3. The terminal shows { "id": "acct_1Pq8EuGmbH2bXvK3", "country": "DE" }
  • pay-agent, a member of the finance-us Group, runs curl -s stripe/v1/account | jq '{id, country}' without holding any credential. The rule "finance-us" in ctx.user.spec.groups selects the us config, so Octelium injects the Secret stripe-us and the upstream authenticates the request as acct_1Nf2UsQ7cLm4RtW9. The terminal shows { "id": "acct_1Nf2UsQ7cLm4RtW9", "country": "US" }
  • SSH: the SSH Service web-01 proxies ssh://10.0.4.21 and picks the upstream credential of every request with dynamic configuration rules.
  • sam, a member of the sre Group, runs ssh web-01 without holding any credential. The rule "sre" in ctx.user.spec.groups selects the root config, so Octelium injects the Secret root-key and the upstream authenticates the request as root. The terminal shows Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.14.0-1015-aws x86_64) root@web-01:~# id uid=0(root) gid=0(root) groups=0(root)
  • noah, a member of the developers Group, runs ssh web-01 without holding any credential. The rule "developers" in ctx.user.spec.groups selects the deploy config, so Octelium injects the Secret deploy-key and the upstream authenticates the request as deploy. The terminal shows Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.14.0-1015-aws x86_64) deploy@web-01:~$ id uid=1001(deploy) gid=1001(deploy) groups=1001(deploy)
  • PostgreSQL: the POSTGRES Service orders-db proxies postgres://10.0.2.8:5432 and picks the upstream credential of every request with dynamic configuration rules.
  • priya, a member of the backend Group, runs psql -h orders-db orders without holding any credential. The rule "backend" in ctx.user.spec.groups selects the rw config, so Octelium injects the Secret pg-rw and the upstream authenticates the request as app_rw. The terminal shows psql (17.2) Type "help" for help. orders=> UPDATE orders SET status = 'shipped' WHERE id = 42; UPDATE 1
  • bi-agent, a member of the analytics Group, runs psql -h orders-db orders without holding any credential. The rule "analytics" in ctx.user.spec.groups selects the ro config, so Octelium injects the Secret pg-ro and the upstream authenticates the request as app_ro. The terminal shows psql (17.2) Type "help" for help. orders=> UPDATE orders SET status = 'shipped' WHERE id = 42; ERROR: permission denied for table orders

Signing in with a passkey and opening the Portal

  • The sign-in page of the Cluster at acme.com/login offers login with Okta, with GitHub, or with a passkey.
  • jane@acme.com chooses Login with a Passkey and verifies it with a biometric on the device through native WebAuthn.
  • The browser is redirected to the Portal at portal.acme.com/services, which lists the Services the User can access:
  • grafana.monitoring: Grafana dashboards, Web App, Namespace monitoring.
  • aws-postgres.production: Amazon RDS for PostgreSQL, PostgreSQL, Namespace production.
  • k8s-prod: Production EKS cluster, Kubernetes, Namespace default.
  • bastion.production: SSH bastion host, SSH, Namespace production.
  • github-mcp: GitHub MCP server, MCP, Namespace default.
  • openai: OpenAI API, AI / LLM, Namespace default.
AccessLogOTLP
ALLOWlinus@acme.compg-prod.dbPOSTGRESquery: select id, email from users limit 50
ALLOWci-runnerprod-k8sKUBERNETESverb=list resource=pods namespace=production
DENYagent-07tools-mcpMCPtools/call name=transfer policy=mcp-tools
ALLOWjane@acme.combastionSSHsession recorded, upstream user=deploy
ALLOWagent-07openaiLLMCHAT_COMPLETIONS model=gpt-5-mini tokens=1284
Deployment and scale

Self-hosted, Kubernetes-native and fully programmable

Run the Cluster on Kubernetes infrastructure you control, scale the data plane horizontally, manage resources declaratively, automate the platform through APIs and SDKs, and optionally deploy containerized Service upstreams with the Cluster itself.

Read the management guide

Cluster resources applied declaratively from YAML with octeliumctl and managed programmatically with the Go, TypeScript, Python and Rust SDKs

  • GitOps: cluster.yaml in the main branch of the ~/octelium repository describes the desired state of the Cluster. Its diff reads as follows, with + for added, ~ for changed and - for removed lines.
  • + kind: Group
  • + metadata:
  • + name: payments
  • + spec: {}
  • + ---
  • + kind: User
  • + metadata:
  • + name: alice
  • + spec:
  • + type: HUMAN
  • + email: alice@acme.com
  • + groups: ["payments"]
  • ---
  • kind: User
  • metadata:
  • name: bob
  • spec:
  • type: HUMAN
  • ~ groups: ["payments"]
  • ---
  • kind: Service
  • metadata:
  • name: billing
  • spec:
  • mode: HTTP
  • config:
  • upstream:
  • ~ url: http://10.0.3.24:8080
  • - ---
  • - kind: Service
  • - metadata:
  • - name: billing-legacy
  • - spec: ⋯
  • - ---
  • - kind: User
  • - metadata:
  • - name: john
  • - spec: ⋯
  • ~/octelium ❯ octeliumctl apply --prune .
  • Group: payments Created
  • User: alice Created
  • User: bob Updated
  • Service: billing.default Updated
  • Service: billing-legacy.default Deleted
  • User: john Deleted
  • Cluster Core resources successfully applied
  • 2 resources created
  • 2 resources updated
  • 2 resources deleted
  • Go: main.go uses the octelium-go SDK to list the Users of the Cluster and update the email and Policies of linus.
  • client, err := octelium.New(ctx)
  • if err != nil {⋯}
  • conn, err := client.Conn(ctx)
  • if err != nil {⋯}
  • api := corev1.NewMainServiceClient(conn)
  • users, err := api.ListUser(ctx, &corev1.ListUserOptions{})
  • if err != nil {⋯}
  • for _, u := range users.Items {
  • fmt.Println(u.Metadata.Name)
  • }
  • user, err := api.GetUser(ctx, &metav1.GetOptions{Name: "linus"})
  • if err != nil {⋯}
  • user.Spec.Email = "linus@acme.com"
  • user.Spec.Authorization = &corev1.User_Spec_Authorization{
  • Policies: []string{"db-readonly"},
  • }
  • if _, err := api.UpdateUser(ctx, user); err != nil {⋯}
  • fmt.Println("updated", user.Metadata.Name)
  • ~/app ❯ go run .
  • alice
  • bob
  • linus
  • updated linus
  • TypeScript: main.ts uses the @octelium/sdk SDK to list the Users of the Cluster and update the email and Policies of linus.
  • const client = await OcteliumClient.create({
  • domain: "acme.com",
  • auth: {⋯},
  • });
  • const users = await client.coreV1.listUser(ListUserOptions.create());
  • for (const u of users.response.items) {
  • console.log(u.metadata?.name);
  • }
  • const { response: user } = await client.coreV1.getUser(
  • GetOptions.create({ name: "linus" }),
  • );
  • user.spec!.email = "linus@acme.com";
  • user.spec!.authorization = User_Spec_Authorization.create({
  • policies: ["db-readonly"],
  • });
  • await client.coreV1.updateUser(user);
  • console.log("updated", user.metadata?.name);
  • await client.close();
  • ~/app ❯ npx tsx main.ts
  • alice
  • bob
  • linus
  • updated linus
  • Python: main.py uses the octelium-sdk SDK to list the Users of the Cluster and update the email and Policies of linus.
  • async with await OcteliumClient.create() as client:
  • users = await client.core_v1.list_user(ListUserOptions())
  • for u in users.items:
  • print(u.metadata.name)
  • user = await client.core_v1.get_user(GetOptions(name="linus"))
  • user.spec.email = "linus@acme.com"
  • user.spec.authorization.policies = ["db-readonly"]
  • await client.core_v1.update_user(user)
  • print("updated", user.metadata.name)
  • ~/app ❯ python main.py
  • alice
  • bob
  • linus
  • updated linus
  • Rust: main.rs uses the octelium SDK to list the Users of the Cluster and update the email and Policies of linus.
  • let client = Client::from_env().await?;
  • let mut api = client.core_v1();
  • let users = api.list_user(ListUserOptions::default()).await?;
  • for u in users.into_inner().items {
  • println!("{}", u.metadata.unwrap_or_default().name);
  • }
  • let options = GetOptions {
  • name: "linus".into(),
  • ..Default::default()
  • };
  • let mut user = api.get_user(options).await?.into_inner();
  • let spec = user.spec.get_or_insert_default();
  • spec.email = "linus@acme.com".into();
  • spec.authorization.get_or_insert_default().policies = vec!["db-readonly".into()];
  • let user = api.update_user(user).await?.into_inner();
  • println!("updated {}", user.metadata.unwrap_or_default().name);
  • ~/app ❯ cargo run -q
  • alice
  • bob
  • linus
  • updated linus
Requirements

What an autonomous agent needs, and what issues it

An agent that can act on real systems needs the same things a new employee needs, on a shorter timescale and in larger numbers. These are the requirements, next to the mechanism in an Octelium Cluster that provides each one.

  1. 01

    An identity of its own

    An agent is a workload User, not a shared service account and not a copy of a person's session. It has its own groups, its own Policies, its own Session and its own entries in the audit trail, which is what makes revoking one agent a contained action.

    Read more
  2. 02

    A way to prove that identity without a stored secret

    Agents authenticate with federated OpenID Connect assertions issued by the platform running them, such as GitHub Actions, a cloud provider or a Kubernetes cluster, so no long-lived token has to sit in the environment they run in. Authentication tokens and OAuth2 client credentials remain available where assertions are not.

    Read more
  3. 03

    Access to resources it never holds credentials for

    Upstream credentials stay in the Cluster and are injected after a request is authorized, which covers HTTP API keys, SSH passwords and private keys, database passwords, kubeconfigs and mTLS certificates. A prompt injection cannot exfiltrate a credential the agent never had.

    Read more
  4. 04

    Authorization on the tool call, not on the connection

    The MCP mode parses JSON-RPC messages, so the method, the tool name and the tool arguments are each available to a Policy. Discovery can be open while individual tools are restricted, and an argument can be bounded rather than a tool allowed outright.

    Read more
  5. 05

    Authorization on the inference request

    The LLM mode normalizes the operation, requested model, streaming flag, declared tools, input modalities and declared output-token maximum, so which model an agent may use and under what conditions is a policy decision rather than which key it was given.

    Read more
  6. 06

    Bounds that hold regardless of the prompt

    Request body size, streamed event size, estimated input tokens, declared output tokens and declared tool count are enforced by the gateway before a request leaves the Cluster, independently of what the agent was asked to do.

    Read more
  7. 07

    Somewhere isolated to run

    Cordium, built on Octelium, provides reproducible sandboxes for agents and developers on the same Kubernetes infrastructure. Processes inside a Workspace reach authorized Services through the Workspace identity, with no secrets placed inside the sandbox.

    Read more
  8. 08

    A record of what it actually did

    Every request produces an identity-aware AccessLog naming the User and Session alongside the tool called, the arguments, the model used and the tokens consumed, streamed in real time over OpenTelemetry to your own log management and SIEM providers.

    Read more

Most of this is not specific to AI. It is ordinary identity and access management, applied to identities that are created faster, act more often and are harder to interview afterwards.

Questions

Frequently asked

How does an AI agent authenticate?
As a workload User, using the same identity model as a human User. It can present an authentication token, use the standard OAuth2 client credentials flow against the Cluster's token endpoint, use an access token directly as a bearer token, or authenticate secretlessly with a federated OpenID Connect assertion issued by the platform running it, such as GitHub Actions, a cloud provider or a Kubernetes cluster. No proprietary SDK is required.
Can individual tool calls be authorized?
Yes. The MCP mode understands JSON-RPC messages, so the method and the tool, prompt or resource name are separate normalized fields, and the parsed request body is available for arguments that have no normalized field. That lets tools/list stay open for discovery while tools/call is restricted per tool, per group and per argument value.
What stops an agent from leaking a credential?
It never receives one. Upstream credentials are stored in the Cluster as Secrets and injected into the upstream connection after a request has been authorized, and downstream Authorization, X-Api-Key and Api-Key credentials are stripped before proxying. The agent authenticates as itself and reaches the resource through the proxy, so there is no provider API key, database password or SSH key inside its environment to exfiltrate.
Can different agents have different privileges on the same resource?
Yes. Dynamic configuration selects the upstream, the upstream account and the credential per request from identity and request context, so a release agent and a research agent can share one Service URL while reaching different backends with different rights. Policies attach to a Service, a Namespace, a User, a Group or a Credential.
Where do agents actually run?
Wherever you run them. If you want the execution environment as well, Cordium is a free and open source sandbox platform built on Octelium and on the same Kubernetes infrastructure. Workspaces are built from OCI images, Dockerfiles, git repositories or devcontainers, run rootless, and reach authorized Services through the Workspace identity with no secrets inside the sandbox.
Are prompts and tool arguments recorded?
It depends on the mode and is configurable per Service. MCP request and response bodies are captured by default, because inspecting JSON-RPC messages is usually the point of the audit, and can be disabled. LLM request and response bodies are not captured by default, because prompts and outputs commonly contain sensitive data, and can be enabled where the audit backend and its retention policy are appropriate for them.
Get started

Run Octelium on your own infrastructure

Install a self-hosted Cluster and start applying identity-aware access control to your Services.