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toc_hide: true
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---
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The room state *S′(E)* after an event *E* is defined in terms of the
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room state *S(E)* before *E*, and depends on whether *E* is a state
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event or a message event:
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- If *E* is a message event, then *S′(E)* = *S(E)*.
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- If *E* is a state event, then *S′(E)* is *S(E)*, except that its
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entry corresponding to the `event_type` and `state_key` of *E* is
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replaced by the `event_id` of *E*.
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The room state *S(E)* before *E* is the *resolution* of the set of
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states {*S′(E*<sub>1</sub>*)*, *S′(E*<sub>2</sub>*)*, …}
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after the `prev_event`s {*E*<sub>1</sub>, *E*<sub>2</sub>, …} of *E*.
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The resolution of a set of states is given in the algorithm below.
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#### Definitions
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The state resolution algorithm for version 2 rooms uses the following
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definitions, given the set of room states
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{*S*<sub>1</sub>, *S*<sub>2</sub>, …}:
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**Power events.**
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A *power event* is a state event with type `m.room.power_levels` or
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`m.room.join_rules`, or a state event with type `m.room.member` where
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the `membership` is `leave` or `ban` and the `sender` does not match the
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`state_key`. The idea behind this is that power events are events that
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might remove someone's ability to do something in the room.
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**Unconflicted state map and conflicted state set.**
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The keys of the state maps *S<sub>i</sub>* are 2-tuples of strings of the form
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*K* = `(event_type, state_key)`. The values *V* are state events.
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The key-value pairs (*K*, *V*) across all state maps *S<sub>i</sub>* can be
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divided into two collections.
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If a given key *K* is present in every *S<sub>i</sub>* with the same value *V*
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in each state map, then the pair (*K*, *V*) belongs to the *unconflicted state map*.
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Otherwise, *V* belongs to the *conflicted state set*.
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Note that the unconflicted state map only has one event for each key *K*,
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whereas the conflicted state set may contain multiple events with the same key.
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**Auth chain.**
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The *auth chain* of an event *E* is the set containing all of *E*'s auth events,
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all of *their* auth events, and so on recursively, stretching back to the
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start of the room. Put differently, these are the events reachable by walking
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the graph induced by an event's `auth_events` links.
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**Auth difference.**
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The *auth difference* is calculated by first calculating the full auth
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chain for each state *S*<sub>*i*</sub>, that is the union of the auth
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chains for each event in *S*<sub>*i*</sub>, and then taking every event
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that doesn't appear in every auth chain. If *C*<sub>*i*</sub> is the
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full auth chain of *S*<sub>*i*</sub>, then the auth difference is
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∪ *C*<sub>*i*</sub> − ∩ *C*<sub>*i*</sub>.
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**Full conflicted set.**
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The *full conflicted set* is the union of the conflicted state set and
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the auth difference.
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**Reverse topological power ordering.**
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The *reverse topological power ordering* of a set of events is the
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lexicographically smallest topological ordering based on the DAG formed
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by auth events. The reverse topological power ordering is ordered from
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earliest event to latest. For comparing two topological orderings to
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determine which is the lexicographically smallest, the following
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comparison relation on events is used: for events *x* and *y*,
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*x* < *y* if
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1. *x*'s sender has *greater* power level than *y*'s sender, when
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looking at their respective `auth_event`s; or
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2. the senders have the same power level, but *x*'s `origin_server_ts`
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is *less* than *y*'s `origin_server_ts`; or
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3. the senders have the same power level and the events have the same
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`origin_server_ts`, but *x*'s `event_id` is *less* than *y*'s
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`event_id`.
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The reverse topological power ordering can be found by sorting the
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events using Kahn's algorithm for topological sorting, and at each step
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selecting, among all the candidate vertices, the smallest vertex using
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the above comparison relation.
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**Mainline ordering.**
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Given an `m.room.power_levels` event *P*, the *mainline of* *P* is the
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list of events generated by starting with *P* and recursively taking the
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`m.room.power_levels` events from the `auth_events`, ordered such that
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*P* is last. Given another event *e*, the *closest mainline event to*
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*e* is the first event encountered in the mainline when iteratively
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descending through the `m.room.power_levels` events in the `auth_events`
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starting at *e*. If no mainline event is encountered when iteratively
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descending through the `m.room.power_levels` events, then the closest
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mainline event to *e* can be considered to be a dummy event that is
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before any other event in the mainline of *P* for the purposes of
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condition 1 below.
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The *mainline ordering based on* *P* of a set of events is the ordering,
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from smallest to largest, using the following comparison relation on
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events: for events *x* and *y*, *x* < *y* if
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1. the closest mainline event to *x* appears *before* the closest
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mainline event to *y*; or
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2. the closest mainline events are the same, but *x*'s
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`origin_server_ts` is *less* than *y*'s `origin_server_ts`; or
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3. the closest mainline events are the same and the events have the
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same `origin_server_ts`, but *x*'s `event_id` is *less* than *y*'s
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`event_id`.
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**Iterative auth checks.**
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The *iterative auth checks algorithm* takes as input an initial room
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state and a sorted list of state events, and constructs a new room state
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by iterating through the event list and applying the state event to the
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room state if the state event is allowed by the [authorization
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rules](/server-server-api#authorization-rules).
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If the state event is not allowed by the authorization rules, then the
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event is ignored. If a `(event_type, state_key)` key that is required
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for checking the authorization rules is not present in the state, then
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the appropriate state event from the event's `auth_events` is used if
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the auth event is not rejected.
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#### Algorithm
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The *resolution* of a set of states is obtained as follows:
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1. Select all *power events* that appear in the *full conflicted set*. Compute
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the union of their auth chains, including the power events themselves.
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Sort the union using the *reverse topological power ordering*.
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2. Apply the *iterative auth checks algorithm*, starting from the
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*unconflicted state map*, to the list of events from the previous
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step to get a partially resolved state.
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3. Take all remaining events that weren't picked in step 1 and order
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them by the mainline ordering based on the power level in the
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partially resolved state obtained in step 2.
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4. Apply the *iterative auth checks algorithm* on the partial resolved
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state and the list of events from the previous step.
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5. Update the result by replacing any event with the event with the
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same key from the *unconflicted state map*, if such an event exists,
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to get the final resolved state.
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#### Rejected events
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Events that have been rejected due to failing auth based on the state at
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the event (rather than based on their auth chain) are handled as usual
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by the algorithm, unless otherwise specified.
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Note that no events rejected due to failure to auth against their auth
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chain should appear in the process, as they should not appear in state
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(the algorithm only uses events that appear in either the state sets or
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in the auth chain of the events in the state sets).
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{{% boxes/rationale %}}
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This helps ensure that different servers' view of state is more likely
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to converge, since rejection state of an event may be different. This
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can happen if a third server gives an incorrect version of the state
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when a server joins a room via it (either due to being faulty or
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malicious). Convergence of state is a desirable property as it ensures
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that all users in the room have a (mostly) consistent view of the state
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of the room. If the view of the state on different servers diverges it
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can lead to bifurcation of the room due to e.g. servers disagreeing on
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who is in the room.
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Intuitively, using rejected events feels dangerous, however:
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1. Servers cannot arbitrarily make up state, since they still need to
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pass the auth checks based on the event's auth chain (e.g. they
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can't grant themselves power levels if they didn't have them
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before).
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2. For a previously rejected event to pass auth there must be a set of
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state that allows said event. A malicious server could therefore
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produce a fork where it claims the state is that particular set of
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state, duplicate the rejected event to point to that fork, and send
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the event. The duplicated event would then pass the auth checks.
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Ignoring rejected events would therefore not eliminate any potential
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attack vectors.
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{{% /boxes/rationale %}}
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Rejected auth events are deliberately excluded from use in the iterative
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auth checks, as auth events aren't re-authed (although non-auth events
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are) during the iterative auth checks.
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