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Token Refresh and Keychain Resolution

This document updates Keychain Token Refresh to match the current DSL runtime model.

Standard intent:

  • Playbooks do not embed tokens; they reference auth/credentials by name (often via workload).
  • Workers resolve auth per tool task execution (inside the tool runner).
  • Token refresh is part of the credential materialization + caching subsystem (see credential_caching_v2.md).
  • The event log stores metadata only (never decrypted token bytes).

“Keychain” may exist as an implementation registry (catalog of credential definitions), but the standard behavior is: tool auth resolution → refresh if needed → cache encrypted → execute tool.

1) Overview​

Many credentials produce short-lived tokens (OAuth access tokens, ID tokens, STS tokens). NoETL prevents token-expiration failures by refreshing tokens before a tool task uses them.

At tool execution time, the worker:

  1. Resolves the requested credential reference (auth: / credential:)
  2. Checks if the resolved token is expired or expiring soon (TTL threshold)
  3. Refreshes (or re-mints) the token if needed
  4. Updates secure caches (execution-scoped and/or global derived-token cache)
  5. Uses the fresh token to execute the tool task

This is executed automatically before each tool task that requires auth.

2) What playbooks reference​

Standard playbooks reference credentials by name, typically:

  • auth: pg_k8s
  • auth: "{{ workload.openai_auth }}"
  • tool-specific fields such as credential: ... are allowed but should normalize to a credential reference

Playbooks should not reference {{ keychain.*.token }} as the primary mechanism. If legacy playbooks do so, the runtime may support it for compatibility by treating it as a credential reference resolution step, but it is not the preferred standard style.

3) Refresh threshold policy​

Workers refresh tokens when remaining TTL is below a configurable threshold.

Recommended environment variable (unchanged concept):

  • NOETL_AUTH_REFRESH_THRESHOLD_SECONDS (default: 300 seconds)

The threshold should be chosen based on:

  • expected tool/task duration
  • token mint/refresh latency
  • network conditions and retry budget

4) Where refresh happens (worker tool runner)​

Refresh occurs during auth resolution, not as a separate step/DSL feature.

Conceptual flow:

Worker begins task execution
  ↓
Resolve auth reference (credential name + usage policy)
  ↓
Fetch cached token material (hot cache → Postgres cache → provider)
  ↓
Check TTL vs threshold
  - TTL > threshold  → use token
  - TTL ≤ threshold  → refresh/re-mint token
  ↓
Update caches (encrypted) + return token in-memory
  ↓
Execute tool

5) Caching model (Standard)​

Token refresh integrates with the standard caching scopes:

5.1 Execution-scoped cache​

  • caches credential material for the current execution
  • key includes (execution_id, credential_name, credential_fingerprint)

5.2 Global derived-token cache​

  • caches derived tokens across executions when safe
  • key MUST include token derivation inputs (audience, scopes, client_id, tenant, etc.)

See credential_caching_v2.md for full keying and security rules.

6) Error handling and retry​

Token refresh failures are represented as structured tool outcomes, allowing task policy rules to decide:

  • retry for transient failures (timeouts, 429, 5xx from token provider)
  • fail fast for permanent auth failures (invalid_grant, invalid_client, 401)

Important:

  • retries for refresh happen via task policy (then.do: retry) and/or tool-internal retry knobs (implementation-defined)
  • the runtime should avoid repeated refresh storms (use jitter/backoff and global cache keys)

7) Security constraints (MUST)​

  • Decrypted tokens MUST exist only in worker memory for the duration of tool execution.
  • Decrypted tokens MUST NOT be:
    • written to the event log
    • returned in outcome.result
    • written to ctx or iter
    • included in projections
  • Logs MUST redact token values.
  • Cache entries MUST be encrypted at rest and include metadata (fingerprint, expiry, key id).

8) Optional: “Keychain” registry compatibility​

If your implementation uses a keychain section or a keychain service:

  • treat it as a registry/catalog that maps credential_name → provider configuration
  • the worker still resolves auth via the same materialization pipeline
  • token refresh still occurs during tool execution

This preserves the conceptual “keychain” while keeping standard semantics consistent.

Emit non-sensitive operational metrics/logs:

  • token cache hit/miss (by credential name)
  • refresh count and refresh latency
  • refresh failure rate (by provider)
  • token age/TTL distribution at time of use (bucketed)

Example safe messages:

  • AUTH: refresh performed for credential X (ttl=120s < threshold=300s)
  • AUTH: refresh failed for credential X (provider timeout); retrying…

10) Best practices​

  1. Prefer auth: references over templated token injection.
  2. Include all derivation inputs in global token cache keys (audience, scopes, tenant, client).
  3. Refresh “ahead of expiry” with a threshold; do not wait for hard expiry.
  4. Use idempotent tool calls or safe retries where possible.
  5. Do not leak tokens into logs, events, or outputs—ever.

See also​

  • credential_caching_v2.md
  • retry_mechanism.md
  • result_storage_v2.md