Hands-On with PostgreSQL Authorization – Part 2 – Row-Level Security

https://www.tangramvision.com/blog/hands-on-with-postgresql-authorization-part-2-row-level-security

by grschafer • 4 years ago

95 32 4 years ago

brownkonas• 4 years ago

Good article on what's possible and how to do it, but is row level security scalable in any way for a production application? Not so much on the performance impact of any one query but maintaining the definition of what a role can or can't do (if a db user = an application role). It also seems like it would complicate managing db connections as well, separate pools for each db user? If you have 10 roles, you have to open up at least 10 connections to avoid connection opening latency.

Leveraging most RDBMS security features seem to be geared for an ever shrinking set of use cases where a mostly static set of users are given direct access to a SQL prompt, or a simple record to GUI application interface.

jzelinskie2• 4 years ago

Disclaimer: I am a founder of Authzed (W21)[0].

It always depends on the domain. If the data model for the app is simple enough, RLS can take you pretty far. Enterprise apps that require you to support the various vague interpretations of "RBAC" or domains that have more complex data models will eventually need some kind of more sophisticated authorization solution. There are a variety solutions at that point (e.g. SpiceDB[1], oso[2], OPA[3]) and you'll be making your decision based on not only the implementation of the technology, but concerns that have cropped in your business requirements:

- "How will additional microservices check permissions?"

- "How can we test and enforce that our authorization system is correct?"

- "Can I support user-defined permissions?"

[0] https://authzed.com

[1] https://github.com/authzed/spicedb

[2] https://www.osohq.com

[3] https://www.openpolicyagent.org

ewuhic2• 4 years ago

And how exactly does one approach those 3 outlined questions?

ctxc• 4 years ago

You can get pretty far with RLS. First discovered this when I started working with Supabase.

RedShift14• 4 years ago

You don't need 10 different connections, you can switch roles in a transaction. You connect using a role that can impersonate other roles and then run your queries like this:

begin;

set local role myrole; -- the important part

SELECT * FROM page;

commit;

WinterMount223• 4 years ago

Can you refer to roles? Something like “set local role (SELECT name FROM roles WHERE id = 7)”

grschafer• 4 years ago

Good questions! Regarding maintaining the definition of what a role can or can't do -- I think this comes down to how you organize your SQL. If you keep authz declarations in one place, it's going to be more maintainable than if they're spread across many database migrations. One way you can keep those authz declarations in one place is by doing development/maintenance on that one place then using a database-diffing tool[1] to generate migrations based on whatever changes you made.

Regarding database connections -- one way to avoid needing a connection per user is to use something like PostgREST[2] to handle incoming requests, identify the user making the request, and use an existing db pool connection to switch roles and execute whatever queries are requested. EDIT: RedShift1 beat me to this explanation by a little bit! :)

RLS certainly isn't the answer for every domain or problem size, but I've been surprised by how powerful it is compared with how relatively unknown it is.

[1] https://supabase.com/blog/2021/03/31/supabase-cli#migrations

[2] https://postgrest.org/en/stable/auth.html

osrec• 4 years ago

Is this a viable/scalable method for setting up a multi tenant DB?

RedShift14• 4 years ago

Yes

kaladin_1• 4 years ago

Great article!

Although, I would say that this merely shows what is possible with the database level security. It might be useful for an internal db with less complicated permission system.

Authorisation Libraries on application level are more scalable and more maintainable than this database level security. Also, just by reading the application code you can tell the expected behaviour...

sekun3• 4 years ago

I don’t understand what metrics you use for “more scalable” and “more maintainable”. If your application’s needs is sufficiently fulfilled by RLS, you don’t have to reinvent the wheel in the application level. Less code there to maintain is good.

Plus, I don’t see how “just by reading application code you can tell the expected behavior” doesn’t apply to RLS. Policies are written in a consistent format. USING for visibility, WITH CHECK for altering. I only have to keep an eye for these, and I’ll already get a good summary on what it does, no?

ggregoire2• 4 years ago

I discovered row-level security when I started using PostgREST [1] [2].

It was eye opening for me. In every traditional codebase I worked on, this is usually handled is such a slow and messy way, adding another layer of filtering on top of already slow and complex queries. This is always one of the first things that needs to be cached in Redis. Instead, row-level security solves the problem in a very elegant, simple and performant way in my opinion.

Obviously it works better when all your logic is already at the DB level (e.g. PostgREST). I wouldn't imagine using DB roles and row-level security in a traditional backend where all the logic is at the application level (e.g. Django, Rails…). Edit: seems like there are workarounds to use RLS with Django [3].

[1] https://postgrest.org

[2] https://postgrest.org/en/stable/auth.html#roles-for-each-web...

[3] https://pganalyze.com/blog/postgres-row-level-security-djang...

RedShift14• 4 years ago

Yeah it's ridiculous how many features of a modern database server we are leaving on the table in favour of spending more time re-inventing these things for every new app or middle layer. Even MSSQL has row level security, I doubt it's being used very much.

pow_pp_-1_v2• 4 years ago

I don't see why RLS would mandate all your logic living in the DB level. Basically what the database does when you enable RLS is add the RLS policy clause to every query you run against a table that has the policy applied. So if you have a policy saying "A = 'blah'" on table "dummy", a query like "SELECT * FROM dummy WHERE a_col = 123" becomes "SELECT * FROM dummy WHERE a_col = 123 and A = 'blah'".

ggregoire2• 4 years ago

Indeed. I was thinking about the RLS use case where the policy is based on the current user and its role. It wasn't obvious to me at first but you could just add a middleware to your app that dynamically set the role in the DB for the user making the request (as in the third article I posted in my edit). Basically what PostgREST does.

paulryanrogers2• 4 years ago

Some features just don't scale or cannot easily integrate into app layers which need them. For example Pg connections are expensive, so you need a Pooler, now you don't want a DB user per end user. FK constraints too can prove hard to scale as one ends up with extra writes and contention, or do sharing.

timando• 4 years ago

now you don't want a DB user per end user.

`RESET ROLE; SET ROLE app_username;` could be done for each query / transaction / when fetching the connection from the pool.

Winsaucerer2• 4 years ago

Looking at that django link, rather than creating a new role for every user ID, you can set a value in each transaction that can contain whatever you like, including a user ID [1] [2]. What I don't like about that django solution is that it's very django dependent. If you ever had another system that can create users, the django signal wouldn't fire and the new role wouldn't be created. Apart from that, you'll have a lot of unnecessary roles in postgres itself.

[1] https://news.ycombinator.com/item?id=30706295

[2] https://news.ycombinator.com/item?id=30703881

pow_pp_-1_v2• 4 years ago

We use RLS on a multi-tenant application in production. It's used as a secondary level of protection that ensures that one tenant cannot see another tenant's data. The system hasn't been out in production for very long but, so far so good.

montmorency88• 4 years ago

I first realized the usefulness/minimalism of row level security when playing with the [ihp-backend](https://ihpbackend.digitallyinduced.com/) package. It's a really lean way of moving straight from your data definitions in a schema to your application logic written in react.

I thought it was interesting because it was a change from the usual authentication cycle of storing some session information and handling all the authentication through sessions and restricted queries.

BrandiATMuhkuh• 4 years ago

Each time I'm reading about RLS in PostgreSQL they leave out how to actually get the `user` into the query.

You need to use

``` SET my.user = 'user1'; SELECT * FROM todos; ```

And in you RLS you can then use

``` CREATE POLICY owner ON todos USING (user = current_setting('my.user')); ```

cryptonector• 4 years ago

PostgreSQL RLS used to have problems with UPDATEs. Does it still?

sekun3• 4 years ago

Could you elaborate? I can update things just fine with a combination of USING, and WITH CHECK. USING can imply WITH CHECK too IIRC.

alex-olivier• 4 years ago

Disclaimer: I work for Cerbos[0].

Whilst this is a very good approach when all your data is stored in a single datastore, as applications grow it is common to start breaking out into more optimised data stores eg you may have few relational databases, a fast lookup source and a search index. This presents a problem of enforcing authorization down into each system.

An alternate way to tackle this is to have the authorization system produce the conditions which need to be applied dynamically at request time (with all the relevant context) which can then be pushed down to each fetching layer as needed [2][3]. This gives far more flexibility in the sorts of authorization rules which can be applied to the data and doesn't tie it to a single bit of technology.

As a real world example we have an integration with Prisma[3] which maps a query plan into a Prisma query format dynamically based on the context of the user and the currently live policies[4].

[0] https://cerbos.dev

[1] https://cerbos.dev/blog/filtering-data-using-authorization-l...

[2] https://docs.cerbos.dev/cerbos/latest/api/index.html#resourc...

[3] https://prisma.io/

[4] https://youtu.be/lqiGj02WVqo?t=3601

gavinray• 4 years ago

This is a really neat and innovative idea. Just burned about an hour going through your website and watching the YouTube demo.

One piece of feedback I have -- I wasn't entirely sure what I was looking at from the homepage, there's a lot going on messaging and content-wise and I had to watch the video to get it.

Maybe something more to the point like "Takes policies, converts them to adapter-specific filter conditions that you tack on to your queries" might be helpful

nhoughto• 4 years ago

ah cool, i've implemented a similar thing but baked into the app dao+authz layer (so easier to do).

I would never guess people would use row level security for this for the reasons you've outlined, rarely (?) is one database the only resource you need to authorise access to, so you will need an authz for all non-db things anyway. Always assumed row-level authz was more for data warehouse type applications where a User has a client directly connected to a database, not intermediated thru multiple levels of abstraction.

Cerbos approach logically seems to make more sense to me than the general Zanzibar inspired methods like Authzed and others. I could never wrap my head around how they could authorise access (Pre and Post filtering?) to data without pushing down conditions to join with into the store. Actually having a 3rd party system like Cerbos be able to push down conditions and have good ergonomics is another thing, that is a tough problem.

ewuhic2• 4 years ago

Does it provide a standalone UI with possibility to expose it to the end-users?

Hands-On with PostgreSQL Authorization – Part 2 – Row-Level Security

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