Voting system particulars are opaque to regular users, but visible to developers, since you have open source. So malicious agents will be ready with their bots the moment SN userbase (/daily coin flow) reaches a certain level.

For instance, using a small botnet to create and fund 100 accounts with 1000 sats each (~30 usd cost). Could use this to for instance:

• Create superpower users. By having all the bots post (chatgpt generated stuff so it's not so obvious), then upvote each others posts (and a few externals, to fuzzy analyis), it seems that the "graph of trust" generated could be gamed such that arbitrary amount of "trust" can be given (or taken away, by flagging/downvoting) to any user.
• DDos your trust graph (which seems to have O^3 time complexity? So 1 sat/comment -> ~260 USD to make 1M ItemAct (etc) from separate users -> 1 TB adjacency table for trust..) It appears the trust-graph has a heavy recursive algorithm, I don't see any load tests for it but i might be wrong.
• I haven't looked super deep into the graph construction algorithm so you might have ways to prevent the above. But in case you haven't considered this: Could PageRank fit as an ranking algorithm instead of the graph? You want to give rank to users who zap high quality posts (early), and divide their rank by total number they zap, then rank by how many incoming vs outgoing zaps per user. IIRC it is O(n+m) complexity (n - nodes, m - links).
• Since Rewards calcs are done at a public, given time every 24hs, the same attack as above, or any other extracted from the source code can be done just before Reward calc to suddenly steal all 21% of posts and get all the rewards.
  Suggestion: Randomize the times these calculations are performed. Also extract out from open source the "heart" of vote calculation.
• Generally write load testers for big user influx cases, see what happens.