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Intelligence integrations

SecOpsAI supports two separate model-assisted operating modes. Both use the same versioned, read-only intelligence contract and both keep raw scanner output, packet data, package artifacts, credentials, and private keys outside model context.

Choose the correct mode

Mode Where the model runs Authentication Best use
Local Codex bridge Codex CLI on the operator's Mac or Linux sensor Existing local ChatGPT sign-in Private local analysis and Mission Control actions
ChatGPT app ChatGPT calls the hosted SecOpsAI MCP server SecOpsAI OAuth plus the user's ChatGPT account Conversational access to authorized findings, assets, and research cases

ChatGPT authentication pays for and identifies the model session. SecOpsAI OAuth separately decides which SecOpsAI data that person may read. One never replaces the other.

Local Codex bridge

The bridge accepts only named SecOpsAI actions. It does not expose an arbitrary prompt or shell endpoint. Core builds a minimized context, the bridge runs Codex in an ephemeral read-only sandbox, and the structured result returns to the durable job record for human review.

Check the local installation and ChatGPT sign-in:

cd /Users/chrixchange/secopsai
.venv/bin/python -m secopsai.cli intelligence bridge doctor

List the approved actions:

.venv/bin/python -m secopsai.cli intelligence actions

Queue an explanation for one finding:

.venv/bin/python -m secopsai.cli intelligence enqueue \
  --action explain_finding \
  --target-id FND-EXAMPLE

Process one queued request:

.venv/bin/python -m secopsai.cli intelligence bridge run --once

Install the bridge as a user-level background service:

.venv/bin/python -m secopsai.cli intelligence bridge service install
.venv/bin/python -m secopsai.cli intelligence bridge service status
.venv/bin/python -m secopsai.cli intelligence bridge service logs

The installer creates ~/Library/LaunchAgents/ai.secopsai.codex-bridge.plist on macOS or ~/.config/systemd/user/secopsai-codex-bridge.service on Linux. It does not copy or persist a ChatGPT credential. Codex continues to own its local authentication state.

Automated research investigations

Mission Control's Run Investigation Pipeline action uses the same durable bridge queue. Core first performs bounded package collection and deterministic static analysis, then creates three read-only jobs: case analysis, analyst brief, and publication-safety review. The bridge receives normalized case context, hashes, manifests, static indicators, and comparison results. It never receives the quarantined artifact, raw registry responses, local quarantine paths, secrets, or customer telemetry.

Bridge results return to Core as review proposals. They do not become evidence until an operator accepts them, and model-generated text is stored only as an analyst-reviewed case note. A bridge failure leaves the pipeline retryable; retries create a new revision and preserve the previous attempt for audit. Verdicts, sandbox submission, disclosure delivery, and publication remain independent human approvals.

ChatGPT app MCP server

The app exposes nine read-only tools:

  • workspace summary
  • list and get findings
  • list assets and recent asset changes
  • list and get research cases
  • build a non-persisting evidence matrix
  • check publication readiness

The MCP server never runs Codex. ChatGPT provides the reasoning and calls the tools. The server verifies the SecOpsAI OAuth access token, checks issuer, audience, expiry, signature, and per-tool scope, then calls the Core intelligence API with a server-side read credential.

Local protocol test

cd /Users/chrixchange/secopsai/apps/secopsai-chatgpt
npm ci --ignore-scripts
npm test
npm audit --audit-level=moderate

Production OAuth requirements

Use an established OAuth 2.1 provider such as Auth0, Okta, Cognito, or Stytch. Configure authorization-code flow with PKCE S256, a token audience equal to SECOPSAI_MCP_RESOURCE, short-lived signed access tokens, the four SecOpsAI read scopes, and a JWKS endpoint. Do not build a custom password or token issuer inside the MCP server.

Required scopes:

  • secopsai.workspace.read
  • secopsai.findings.read
  • secopsai.assets.read
  • secopsai.research.read

The primary render.yaml deliberately does not provision this service. This keeps ordinary Core and research-worker Blueprint syncs independent from optional OAuth configuration and avoids an unused paid service. When the ChatGPT app is ready for a pilot, create one Render web service manually with:

  • Repository: Techris93/secopsai
  • Root directory: apps/secopsai-chatgpt
  • Runtime: Node
  • Build command: npm ci --ignore-scripts
  • Start command: npm start
  • Health path: /readyz
  • Instance: Starter or higher for a reliable pilot; free is acceptable only for temporary development

Required service values:

Variable Purpose
SECOPSAI_MCP_AUTHORIZATION_SERVER OAuth issuer base URL advertised to ChatGPT
SECOPSAI_MCP_ISSUER Exact expected JWT iss value
SECOPSAI_MCP_JWKS_URL Provider signing-key endpoint
SECOPSAI_CORE_READ_TOKEN Same server-side read credential configured on Core

Also set:

Variable Value
SECOPSAI_MCP_ENVIRONMENT production
SECOPSAI_MCP_RESOURCE Exact public service origin, without /mcp
SECOPSAI_MCP_AUDIENCE Same exact public service origin
SECOPSAI_MCP_ALLOWED_HOSTS Public service hostname only
SECOPSAI_MCP_ALLOWED_ORIGINS https://chatgpt.com
SECOPSAI_MCP_DOCUMENTATION_URL https://docs.secopsai.dev/intelligence-integrations/
SECOPSAI_CORE_API_URL https://secopsai-core-api.onrender.com

Set the production MCP resource and audience to the exact public Render origin. Change both together if a custom domain is introduced.

After the opt-in deployment, verify:

curl -sS https://secopsai-chatgpt-app.onrender.com/readyz
curl -sS https://secopsai-chatgpt-app.onrender.com/.well-known/oauth-protected-resource

Then enable ChatGPT developer mode, create a developer app using https://secopsai-chatgpt-app.onrender.com/mcp, complete the OAuth link, and test secopsai_workspace_summary before enabling any wider pilot group.

The current hosted Core is a single-tenant pilot deployment. Limit OAuth access to the same invited SecOpsAI organization. Do not use this deployment for multiple unrelated customers until Core enforces organization membership on every query.

Security boundary

  • Every MCP tool is read-only and declares its exact OAuth scope.
  • Core read, ingest, and intelligence credentials are different.
  • The local bridge runs only allowlisted actions and structured output.
  • Raw telemetry and artifact contents are removed before context construction.
  • Package metadata and finding text are treated as untrusted data, not model instructions.
  • Model output is advisory. It cannot resolve a finding, approve disclosure, submit a sandbox artifact, or publish research.