Privacy scoring modelling > Web3privacy now analytical platform
General
Scoring |
Techie |
Immutability |
+ |
Decentralised throughout, including hosting |
+ |
Permissionless & accessible to all |
+ |
Open-source |
+ |
Docs
Scoring |
Techie |
read the documentation |
+ |
Good and comprehensive documentation |
+ |
Third-party analysis
Scoring |
Techie |
Where's the code? Has it been audited? |
+ |
Validation by trusted and respected independent scientists and researchers |
+ |
Team
Scoring |
Techie |
ideological team |
+ |
Reputation of the team |
+ |
is it purely marketing oriented, or it seems created by researchers/developers, are the developers anons? |
+ |
Privacy policy
Scoring |
Techie |
Privacy Policy content |
+ |
Non-vague and non-intrusive privacy policy |
+ |
Infrastructure
Scoring |
Techie |
How much to run a node |
+ |
Where are the nodes |
+ |
Number of nodes/servers/ -> the larger the footprint the best privacy |
+ |
Storage
Scoring |
Techie |
e2e encrypted LOCAL storage |
+ |
What user information is stored? (username, IP address, last connection, wallets associate, etc) |
+ |
Where is it stored? (centralized server, certain jurisdictions, on-chain, in browser/local cache) |
+ |
Data aggregation
Scoring |
Techie |
no email or tel nr for signup |
+ |
does not implement KYC or AML |
+ |
Traction
Scoring |
Techie |
Amount of transactions |
+ |
number of people using it |
+ |
is it famous |
+ |
Governance
Scoring |
Techie |
DAO structure (if applied) |
+ |
Privacy execution
Scoring |
Techie |
p2p / no central server |
+ |
Trustless - No ID required (this is where ZKs are useful) |
+ |
Product-centric
Scoring |
Techie |
Onboarding steps |
+ |
Testing
Scoring |
Techie |
try to trace a transaction |
+ |
Other tooling to verify e.g. block explorers |
+ |
MVP for non-tecies expanded to techies
Sandbox: DeFi category that has been analyzed
How to use sandbox?
- Read takeaways.
- Give us feedback via general comments in the Community on Signal or make a Pull request here.
- You can always explore 38 DeFi project' assessment here
Scoring model 1.2: validity track
Validity track covers GitHub, Product-readiness, Team, Docs, Audit.
Note: quick assessment helps to decrease privacy dark patterns from obscure language to test-net claiming it has a "state of art privacy".
We use % as a simplified way to prototype scoring model (from % to 100%). Later versions will include a mixmodel of %, yes/no assumptions & much complex observations.