FDC3 Identity & Threat Modelling -14 Mar 2024

Yannick-Malins commented 3 months ago

Group overview

FDC3 revolves around several types of independent entities:

Applications
Desktop Agents
App Directories
Users

Each of these has an identity, and needs to know and trust the identities of several of the others in order to work seamlessly.However, at present there are few or no methods for them to validate those identities within the FDC3 Standard, meaning trust must be assumed. This comes with problems and risks : data loss, identity theft, oauth hell, or an inability to adopt interop via FDC3 - all of which are a threat to the FDC3 ecosystem’s continued growth. This complexity is multiplied by the different types of FDC3 setups now possible - desktop app interop, in-container interop, web interop, and interop between Desktop Agents (Bridging).

Over the past few years, various discussions, demos and roundtables have addressed this topic, but the outcome each time has been “what do our users need?”.

Therefore our first objective in this stream is to dig into what these risks and problems are, before we discuss and work on potential solutions

Relevant issue tags

https://github.com/finos/FDC3/labels/identity-security

Meeting Date

Thursday 14 Mar 2024 - 3pm GMT

Zoom info

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Agenda (60mn)

[ ] Convene & roll call, review meeting notices (5mins)
[ ] Discuss usecases from participants (50mins)
[ ] AOB & Adjourn (5mins)

Minutes

The entire discussion revolved around building and refining a set of "core use-cases" that can be used to analyse the different potential solutions (signing, symmetric or asymmetric encrypting etc).

Use Case A: “Look up public information” Persona: Buy-side investor From: In-house platform To: Market data app Flow: From within their in-house platform, the user requests the latest news items concerning a public company, using a context broadcast or a direct intent Risks: There is no proprietary information sent, however the fact that the investor is looking at this information is in itself confidential
Use Case B: “Look up internal information” Persona: Buy-side investor From Market data app To: In-house platform Flow: Whilst browsing public information, an investor wants to check the current firm position on a security Risks: Again, no proprietary information is sent over FDC3 (only a request to display whatever internal information may or may not exist). But again, the fact that the investor wants to look at this information is in itself confidential
Use Case C: “Request pre-trade information” Persona: Buy-side trader From: In-house platform To: Multiple Single-dealer platforms Flow: Buy-side trader requests margin requirements on an instrument from multiple sell-side platforms. Information is sent back through intent replies Risks: From the buy-side perspective, they expect the same level of confidentiality as cases A/B - none of their data is shared, but the fact that they want to see this data is in of itself confidential. From the sell-side perspective they cannot risk this information leaking to anyone except the buy who requested it.
Use Case D: CRUD with sensitive information Persona: Analyst From: In-house platform To: CRM Flow: Log a client call Risks: Similar to use-case B, but with two differences: sensitive information is transmitted over FDC3, and this is a “write” operation, not read