Firebase security rules - writing from Firebase functions - firebase

I'm trying to implement proper Firebase security rules and ran into one challenging issue. I've got public listings which should be viewable by all, can't be deleted or edited by anyone except by the author of the listing. When someone buys (via PayPal plugin) a given listing, I need to write to this listing changing it's status to SOLD. Essentially this is like a third party (not the listing author) has to write to a given listing.
Here are the rules I have so far:
"listings": {
".read": "auth.provider === 'facebook'",
"$listingID": {
".write": "auth.provider === 'facebook' && ((!data.exists() && newData.exists()) || root.child('listings/'+$listingID+'/UID').val() === auth.uid)"
}
}
I have a feeling that I need to write to Firebase from my backend (Firebase functions), but I'm not sure how the security rules will work out, as it would still be the buyer (3rd party) upon whose request we'd need to write the new status SOLD to the listing node which is only editable by the author.
Any advice/recommendations on how to go about this situation will be highly appreciated!
Many thanks!

Related

Delete node automatically using Firebase Rule

I am using the firebase for store some users data. So now i want to delete old data with check 'last_ubdated' time < 5 min. please help for create the firebase rule for this. below is my data structure.
I have created the rule, but its not working properly.(code is below)
{ "rules": {
".read": true,
".write": true,
"$drivers":{
".indexOn": ["driverId"],
".write": "newData.exists() || data.child('last_updated').val() > (now)",
} } }
Firebase security rules can't change any data after it's been added. They only take effect at the time data is read or written by the client. If you want to arrange to delete something on a schedule, you will need another solution.
See also: Cloud Functions for Firebase trigger on time?
As Doug said, security rules can't change the data. They merely affect what (read and write) operations are allowed.
An alternative would be to use a query to only request nodes that have not expired, and then use security rules to ensure only that query is allowed. For an example of that, see my answer here: How to make data unreadable once the time indicated on its time stamp has passed?

How to hide specific node in firebase realtime database

I have 2 questions related to firebase realtime database.
Q1) Is it possible to hide a certain node from public and only one person have access to that node ?
( I want to save a transaction key in database and only 1-2 persons can access that key from database. )
Q2) If my security rules for database are set to public, can anyone download/access complete data or they must know the structure in order to access data from database.
A1/ Yes it is possible to limit access to a certain node to a only subset of users. There are several approaches for that. If it is a small and more or less stable subset of users, you can check if their uid is contained in a specific node listing the admin users uids, as shown below:
{
"rules": {
"secretnode": {
//only an admin user can read
".read": "auth != null && root.child('adminusers/' + auth.uid).exists()"
},
"adminusers": {
".read": false,
".write": false
},
"othernodes": {
".read": true,
".write": true
}
}
}
And, for example, in the database you save the admin uids as follows:
DBRoot
- adminusers
- uid1
- name: "aaaaaa"
- otherDataItem: "xxxxxx"
- uid2
- name: "bbbbb"
- otherDataItem: "yyyy"
A2/ Yes, if your security rules for database root are set to public, "anyone (can) download/access complete data". Note that, as explained in the documentation:
Shallower security rules override rules at deeper paths. Child rules
can only grant additional privileges to what parent nodes have already
declared. They cannot revoke a read or write privilege.
In other words, this means that if your security rules for the database root are set to public anyone can download the full JSON tree representing your data, without the need to know its structure.

Firebase database rules – `data.exists()` always seems to be true, possible bug?

I am trying to secure my firebase database to allow the creation of new records, but not allow the deletion of existing records. Ultimately, I plan to utilise Firebase authentication in my app as well, and allow users to update existing records if they are the author, but I am trying to get the simple case working first.
However! No matter what I try in the database rules simulator, despite what the documentation seems to suggest, the value of data.exists() seems to always be true. From what I what I can understand from the documentation, the variable data represents a record in the database as it did before an operation took-place. That is to say, for creates, data would not exist, and for updates/deletes, data would refer to a real record that exists in the database. This does not seem to be the case, to the point where I am actually suspecting a bug in Firebase, as when setting the following rules on my database, all write operations are disallowed:
{
"rules": {
".read": true,
".write": "!data.exists()"
}
}
No matter what values I put into the simulator, be it Location or Data. I have even written a small EmberJS app to verify if the Simulator is telling the truth and it too, is denied permission for all write operations.
I really have no idea where to go from here as I am pretty much out of things to try. I tried deleting all records from my database, which lets the simulator think it can perform write operations, but my test app still gets PERMISSION_DENIED, so I don't know what's causing inconsistencies there.
Is my understanding of the predefined data variable correct? If so, why can't I write the rules I want? I have seen snippets literally trying to achieve my "create only, no-delete" rule that seem to line up with my understanding.
Last note: I am trying this in a totally new Firebase project with JUST the rules above, and only ~a few records of junk data laying around my database.
Because you have placed the !data.exists() at the root location of your database, data refers to the entire database. You will only be able to write to the database when it is completely empty.
You indicate that you run your tests with only a few records of junk data laying around my database. Those records will cause data.exists() to be true.
You can achieve your goal by placing the !data.exists() rule in your tree at the specific location where you want to require that no data already exists. This is typically done at a location with a wildcard key, as in the example you linked:
{
"rules": {
// default rules are false if not specified
"posts": {
".read": true, // everyone can read all posts
"$postId": {
// a new post can be created if it does not exist
// existing posts can only be edited by their original "author"
".write": "!data.exists() && newData.exists() || data.child('author').val() == auth.uid",
".validate": "newData.hasChildren(['title', 'author', 'timestamp'])",
}
}
}
}

Having consistency during multi path updates when the paths are not deterministic and are variable

I need help in a scenario when we do multipath updates to a fan-out data. When we calculate the number of paths and then update, in between that, if a new path is added somewhere, the data would be inconsistent in the newly added path.
For example below is the data of blog posts. The posts can be tagged by multiple terms like “tag1”, “tag2”. In order to find how many posts are tagged with a specific tag I can fanout the posts data to the tags path path as well:
/posts/postid1:{“Title”:”Title 1”, “body”: “About Firebase”, “tags”: {“tag1:true, “tag2”: true}}
/tags/tag1/postid1: {“Title”:”Title 1”, “body”: “About Firebase”}
/tags/tag2/postid1: {“Title”:”Title 1”, “body”: “About Firebase”}
Now consider concurrently,
1a) that User1 wants to modify title of postid1 and he builds following multi-path update:
/posts/postid1/Title : “Title 1 modified”
/tags/tag1/postid1/Title : “Title 1 modified”
/tags/tag2/postid1/Title : “Title 1 modified”
1b) At the same time User2 wants to add tag3 to the postid1 and build following multi-path update:
/posts/postid1/tags : {“tag1:true, “tag2”: true, “tag3”: true}
/tags/tag3/postid1: {“Title”:”Title 1”, “body”: “About Firebase”}
So apparently both updates can succeed one after other and we can have tags/tag3/postid1 data out of sync as it has old title.
I can think of security rules to handle this but then not sure if this is correct or will work.
Like we can have updatedAt and lastUpdatedAt fields and we have check if we are updating our own version of post that we read:
posts":{
"$postid":{
".write":true,
".read":true,
".validate": "
newData.hasChildren(['userId', 'updatedAt', 'lastUpdated', 'Title']) && (
!data.exists() ||
data.child('updatedAt').val() === newData.child('lastUpdated').val())"
}
}
Also for tags we do not want to check that again and we can check if /tags/$tag/$postid/updatedAt is same as /posts/$postid/updatedAt.
"tags":{
"$tag":{
"$postid":{
".write":true,
".read":true,
".validate": "
newData.hasChildren(['userId', 'updatedAt', 'lastUpdated', 'Title']) && (
newData.child('updatedAt').val() === root.child('posts').child('$postid').val().child('updatedAt').val())”
}
}
}
By this “/posts/$postid” has concurrency control in it and users can write their own reads
Also /posts/$postid” becomes source of truth and rest other fan-out paths check if updatedAt fields matches with it the primary source of truth path.
Will this bring in consistency or there are still problems? Or can bring performance down when done at scale?
Are multi path updates and rules atomic together by that I mean a rule or both rules are evaluated separately in isolation for multi path updates like 1a and 1b above?
Unfortunately, Firebase does not provide any guarantees, or mechanisms, to provide the level of determinism you're looking for. I have had the best luck front-ending such updates with an API stack (GCF and Lambda are both very easy, server-less methods of doing this). The updates can be made in that layer, and even serialized if absolutely necessary. But there isn't a safe way to do this in Firebase itself.
There are numerous "hack" options you could apply. You could, for example, have a simple lock mechanism using a dedicated collection for tracking write locks. Clients could post to a lock collection, then verify that their key was the only member of that collection, before performing a write. But I hope you'll agree with me that such cooperative systems have too many potential edge cases, potential security issues, and so on. In Firebase, it is best to design such that this component is not a requirement in the first place.

How to create time-expiring data with Firebase Rules?

This talk mentions time-expiring data using Firebase rules at 22:55
https://www.youtube.com/watch?v=PUBnlbjZFAI
How can one do this ?
I didn't find any information regarding this.
I recommend two solutions.
1) Use cloud functions to record a message path and the date it was posted. Then every hour sort that list by date, pick all the expired ones, and create a deep update object to null out every expired message. Nowadays you can use Cron Scheduler to handle the periodic flush.
2) Make a rule that says anyone can delete expired messages and make it so that clients automatically delete expired messages when they are in a chat room.
Written here: https://firebase.google.com/docs/database/security/securing-data
You can't have it auto delete your data but you can make them unreadable (which is the same thing from the user standpoint). Just send a timestamp child field with you data and check against it.
{
"rules": {
"messages": {
"$message": {
// only messages from the last ten minutes can be read
".read": "data.child('timestamp').val() > (now - 600000)",
// new messages must have a string content and a number timestamp
".validate": "newData.hasChildren(['content', 'timestamp']) && newData.child('content').isString() && newData.child('timestamp').isNumber()"
}
}
}
}
Same question here.
You can't do it using firebase rules. You should either have a NodeJS backend removing your old data or clients doing it for you. For example, before a client retrieves data, he could remove old data.

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