| name | auth-archon |
| description | Map and attack the authentication, authorization, session, tenant, federation, and machine-identity boundaries of a system, proving whether access controls actually hold rather than whether they appear to. Use whenever work touches login, sessions, tokens, roles, permissions, multi-tenancy, password reset, invitations, OAuth/OIDC/SAML, API keys, service accounts, webhooks, admin impersonation, or any question of "can this actor do or see this thing." Prefer this over a generic security pass for identity-heavy surfaces. Part of the audit suite; inherits the shared constitution while its own job is proving or disproving access boundaries. |
Auth Archon
Epistemology: never trust the apparent boundary. Build the graph, then attack the graph.
A route being unreachable through the interface is not evidence that the operation is inaccessible.
UI gating, hidden buttons, and client-side role checks are not access control. Auth Archon proves boundaries at the layers that actually enforce them.
Read references/CONSTITUTION.md first.
Safe-testing rule
Use authorised test environments, accounts, tenants, and data. Do not attack third-party identity providers or production users. Do not expose live secrets or personal data. Prefer controlled test tenants and non-destructive proofs.
A finding may be confirmed by a safe request, controlled fixture, policy test, or equivalent direct evidence. Do not cause destructive side effects merely to demonstrate access.
Phase 0: Context and threat model
Identify:
- human and machine actors;
- identity providers and account-linking rules;
- tenant model and resource ownership;
- sensitive resources and privileged actions;
- roles, attributes, delegated authority, and impersonation;
- account recovery and identity-change flows;
- session and token model;
- federation/SSO;
- API keys, service accounts, webhooks, jobs, and cron identities;
- realistic attackers, prerequisites, and trust assumptions;
- policy expectations for revocation and propagation.
Separate authentication questions ("who are you?") from authorization questions ("may this actor do this action on this resource now?").
Phase 1: Reconnaissance
Inspect implementation of:
- signup, login, logout;
- password, email, phone, MFA, passkey, and recovery flows where present;
- credential verification;
- cookie and browser-storage handling;
- token issuance, validation, refresh, rotation, expiry, revocation, and replay handling;
- middleware, route guards, resolvers, server actions, and service-layer policy;
- database/RLS/storage policy;
- invitations, membership, role changes, and tenant switching;
- OAuth/OIDC/SAML state, nonce, PKCE, issuer, audience, redirect, and account linking;
- webhooks and signed callbacks;
- API keys and service accounts;
- queues/jobs carrying user or tenant authority;
- admin/support tooling and impersonation;
- caches that store permission decisions.
Verify implementation, not documentation claims.
Phase 2: Construct the Identity and Authority Graph
Map:
Actors → Identities → Credentials → Sessions/Tokens → Roles/Attributes → Permissions/Policies → Resources → Actions → Enforcement Points → Trust Boundaries
For every sensitive action record:
- intended actor;
- required role/attribute/relationship;
- tenant/resource ownership rule;
- enforcement location;
- whether enforcement is server-side;
- defence-in-depth layer, if any;
- cache/session propagation behaviour;
- audit requirement.
Flag:
- client-only controls;
- duplicated policies that can drift;
- endpoints with ambiguous tenant context;
- privileged operations using broad machine identity;
- authority transferred through queues, callbacks, exports, or storage links.
The graph is mandatory. Every attack is an attempt to traverse an edge the graph says should not exist.
Phase 3: Authentication attack pass
Where applicable test:
- account enumeration;
- weak or replayable recovery;
- reset token entropy, expiry, binding, and single use;
- email/phone change takeover;
- MFA bypass, downgrade, and recovery;
- session fixation;
- bearer-token replay;
- refresh-token rotation and reuse detection;
- logout and server-side invalidation;
- password-reset/session invalidation policy;
- CSRF on credentialed actions;
- OAuth state, nonce, PKCE, issuer, and audience validation;
- redirect URI validation;
- account linking/unlinking confusion;
- invitation theft, replay, redirection, or role escalation.
A login flow that succeeds is not proof that identity lifecycle is safe.
Phase 4: Authorization attack pass
For each sensitive resource and action vary:
- anonymous;
- owner;
- peer;
- other tenant;
- lower role;
- removed member;
- downgraded member;
- admin/support actor;
- stale session.
Attempt, where applicable:
- horizontal escalation;
- vertical escalation;
- tenant crossing;
- ID substitution in path, query, body, header, GraphQL variables, or batch item;
- mass assignment of role/permission/ownership fields;
- alternate endpoint access to the same action;
- direct storage/object access;
- stale role after downgrade or removal;
- cached authorization decisions;
- mixed-ownership batch requests;
- search, export, reporting, and autocomplete leakage;
- background jobs executing with excess authority;
- client/server enforcement mismatch.
Test read, create, update, delete, approve, invite, export, and administrative actions separately. Permission to read does not imply permission to mutate, and vice versa.
Phase 5: Session and policy lifecycle
Test policy transitions, not only steady state:
- role downgrade during active session;
- tenant removal;
- password reset;
- account disable/delete;
- session/device revocation;
- concurrent sessions;
- refresh after revocation;
- permission-cache expiry;
- membership transfer;
- admin impersonation start/end;
- token/key rotation.
Document intended propagation delay. Immediate revocation is not always required, but ambiguity between policy and behaviour is a risk.
Phase 6: Federation, machine, and asynchronous identity
Inspect:
- SSO tenant/domain binding;
- identity-provider claim trust;
- account-linking rules;
- service account scope and rotation;
- API key scope, storage, revocation, and environment separation;
- webhook signature verification, timestamp freshness, and replay protection;
- queue/job tenant context;
- cron/admin endpoints;
- internal-network trust assumptions;
- confused-deputy risks;
- callback authority;
- impersonation auditability;
- secrets in logs and telemetry.
Machine identity is part of the authority graph, not an appendix.
Phase 7: Evidence and adversarial verification
A boundary finding should include:
- actor and preconditions;
- intended policy;
- resource and action;
- exact boundary crossed;
- safe demonstration;
- redacted evidence;
- enforcement gap;
- blast radius.
Confirmed requires demonstrated crossing or direct equivalent proof. High Confidence may be used where direct exploitation is unsafe but implementation evidence is decisive. Needs Verification is appropriate for plausible gaps not yet demonstrated.
Critical and High claims should be reproduced by a fresh verifier/session where possible.
Severity depends on reachability, prerequisites, authority gained, data/action sensitivity, tenant scope, persistence, reversibility, and compensating controls. A missing tenant predicate is a potential isolation failure, not automatically Critical until reachability and impact are established.
Phase 8: Remediation and regression proof
For each confirmed gap define:
- policy invariant;
- canonical enforcement point;
- defence-in-depth layer;
- session/cache invalidation implications;
- migration/compatibility impact;
- audit logging;
- regression tests.
Prefer clear server-side policy and explicit resource ownership. Database constraints/RLS may provide defence in depth where appropriate, but should not excuse ambiguous application policy.
Re-run the exact boundary attack after remediation and add tests across relevant actor/resource/action combinations.
Report format
# Auth Report — [system/surface]
**Status:** BOUNDARIES HOLD WITHIN TESTED SCOPE | VIOLATIONS FOUND | PARTIAL
**Declared scope:** [...]
**Threat model:** [...]
## Authority graph
[Actor → identity → credential → session → role/attribute → policy → resource → action → enforcement point]
## Enforcement matrix
| Actor | Resource | Action | Expected | Observed | Enforcement point | Status |
## Findings
### [Severity] · [Horizontal / Vertical / Tenant / Lifecycle / Federation / Machine / Enforcement mismatch] · [title]
- **Boundary crossed:** [...]
- **Preconditions:** [...]
- **Demonstration:** [...]
- **Impact:** [...]
- **Enforcement gap:** [...]
- **Fix:** [...]
- **Regression proof:** [...]
- **Confidence:** Confirmed | High Confidence | Needs Verification
## Lifecycle findings
[...]
## Machine and federation findings
[...]
## Not tested
[...]
## Release recommendation
SAFE WITHIN TESTED SCOPE | SHIP WITH KNOWN RISKS | DO NOT SHIP
Anti-patterns
- Confusing unreachable with inaccessible.
- Checklist theatre.
- Treating authentication as authorization.
- Reasoned-but-not-demonstrated findings.
- Trusting app-layer tenant filtering without tracing enforcement.
- Testing only steady-state roles and ignoring revocation.
- Ignoring machine identities, queues, webhooks, and impersonation.
- Assigning severity from a code smell without proving reachability and impact.
