matrix-spec/content/rooms/fragments/v2-state-res.md

toc_hide
true

The room state S′(E) after an event E is defined in terms of the room state S(E) before E, and depends on whether E is a state event or a message event:

• If E is a message event, then S′(E) = S(E).
• If E is a state event, then S′(E) is S(E), except that its entry corresponding to the event_type and state_key of E is replaced by the event_id of E.

The room state S(E) before E is the resolution of the set of states {S′(E₁), S′(E₂), …} after the prev_events {E₁, E₂, …} of E. The resolution of a set of states is given in the algorithm below.

Definitions

The state resolution algorithm for version 2 rooms uses the following definitions, given the set of room states {S₁, S₂, …}:

Power events. A power event is a state event with type m.room.power_levels or m.room.join_rules, or a state event with type m.room.member where the membership is leave or ban and the sender does not match the state_key. The idea behind this is that power events are events that might remove someone's ability to do something in the room.

Unconflicted state map and conflicted state set. The keys of the state maps S_i are 2-tuples of strings of the form K = (event_type, state_key). The values V are state events. The key-value pairs (K, V) across all state maps S_i can be divided into two collections. If a given key K is present in every S_i with the same value V in each state map, then the pair (K, V) belongs to the unconflicted state map. Otherwise, V belongs to the conflicted state set.

Note that the unconflicted state map only has one event for each key K, whereas the conflicted state set may contain multiple events with the same key.

Auth chain. The auth chain of an event E is the set containing all of E's auth events, all of their auth events, and so on recursively, stretching back to the start of the room. Put differently, these are the events reachable by walking the graph induced by an event's auth_events links.

Auth difference. The auth difference is calculated by first calculating the full auth chain for each state S_i, that is the union of the auth chains for each event in S_i, and then taking every event that doesn't appear in every auth chain. If C_i is the full auth chain of S_i, then the auth difference is  ∪ C_i −  ∩ C_i.

Full conflicted set. The full conflicted set is the union of the conflicted state set and the auth difference.

Reverse topological power ordering. The reverse topological power ordering of a set of events is the lexicographically smallest topological ordering based on the DAG formed by auth events. The reverse topological power ordering is ordered from earliest event to latest. For comparing two topological orderings to determine which is the lexicographically smallest, the following comparison relation on events is used: for events x and y, x < y if

1. x's sender has greater power level than y's sender, when looking at their respective auth_events; or
2. the senders have the same power level, but x's origin_server_ts is less than y's origin_server_ts; or
3. the senders have the same power level and the events have the same origin_server_ts, but x's event_id is less than y's event_id.

The reverse topological power ordering can be found by sorting the events using Kahn's algorithm for topological sorting, and at each step selecting, among all the candidate vertices, the smallest vertex using the above comparison relation.

Mainline ordering. Let P = P₀ be an m.room.power_levels event. Starting with i = 0, repeatedly fetch P_i+1, the m.room.power_levels event in the auth_events of P_i. Increment i and repeat until P_i has no m.room.power_levels event in its auth_events. The mainline of P₀ is the list of events [P₀ , P₁, ... , P_n], fetched in this way.

Let e = e₀ be another event (possibly another m.room.power_levels event). We can compute a similar list of events [e₁, ..., e_m], where e_j+1 is the m.room.power_levels event in the auth_events of e_j and where e_m has no m.room.power_levels event in its auth_events. (Note that the event we started with, e₀, is not included in this list. Also note that it may be empty, because e may not cite an m.room.power_levels event in its auth_events at all.)

Now compare these two lists as follows.

• Find the smallest index j ≥ 1 for which e_j belongs to the mainline of P.
• If such a j exists, then e_j = P_i for some unique index i ≥ 0. Otherwise set i = ∞, where ∞ is a sentinel value greater than any integer.
• In both cases, the mainline position of e is i.

Given mainline positions calculated from P, the mainline ordering based on P of a set of events is the ordering, from smallest to largest, using the following comparison relation on events: for events x and y, x < y if

1. the mainline position of x is greater than the mainline position of y (i.e. the auth chain of x is based on an earlier event in the mainline than y); or
2. the mainline positions of the events are the same, but x's origin_server_ts is less than y's origin_server_ts; or
3. the mainline positions of the events are the same and the events have the same origin_server_ts, but x's event_id is less than y's event_id.

Iterative auth checks. The iterative auth checks algorithm takes as input an initial room state and a sorted list of state events, and constructs a new room state by iterating through the event list and applying the state event to the room state if the state event is allowed by the authorization rules. If the state event is not allowed by the authorization rules, then the event is ignored. If a (event_type, state_key) key that is required for checking the authorization rules is not present in the state, then the appropriate state event from the event's auth_events is used if the auth event is not rejected.

Algorithm

The resolution of a set of states is obtained as follows:

1. Select the set X of all power events that appear in the full conflicted set. For each such power event P, enlarge X by adding the events in the auth chain of P which also belong to the full conflicted set. Sort X into a list using the reverse topological power ordering.
2. Apply the iterative auth checks algorithm, starting from the unconflicted state map, to the list of events from the previous step to get a partially resolved state.
3. Take all remaining events that weren't picked in step 1 and order them by the mainline ordering based on the power level in the partially resolved state obtained in step 2.
4. Apply the iterative auth checks algorithm on the partial resolved state and the list of events from the previous step.
5. Update the result by replacing any event with the event with the same key from the unconflicted state map, if such an event exists, to get the final resolved state.

Rejected events

Events that have been rejected due to failing auth based on the state at the event (rather than based on their auth chain) are handled as usual by the algorithm, unless otherwise specified.

Note that no events rejected due to failure to auth against their auth chain should appear in the process, as they should not appear in state (the algorithm only uses events that appear in either the state sets or in the auth chain of the events in the state sets).

{{% boxes/rationale %}} This helps ensure that different servers' view of state is more likely to converge, since rejection state of an event may be different. This can happen if a third server gives an incorrect version of the state when a server joins a room via it (either due to being faulty or malicious). Convergence of state is a desirable property as it ensures that all users in the room have a (mostly) consistent view of the state of the room. If the view of the state on different servers diverges it can lead to bifurcation of the room due to e.g. servers disagreeing on who is in the room.

Intuitively, using rejected events feels dangerous, however:

1. Servers cannot arbitrarily make up state, since they still need to pass the auth checks based on the event's auth chain (e.g. they can't grant themselves power levels if they didn't have them before).
2. For a previously rejected event to pass auth there must be a set of state that allows said event. A malicious server could therefore produce a fork where it claims the state is that particular set of state, duplicate the rejected event to point to that fork, and send the event. The duplicated event would then pass the auth checks. Ignoring rejected events would therefore not eliminate any potential attack vectors. {{% /boxes/rationale %}}

Rejected auth events are deliberately excluded from use in the iterative auth checks, as auth events aren't re-authed (although non-auth events are) during the iterative auth checks.