If you're using Cloud Firestore or Cloud Storage for Firebase, you're also using Security Rules. (If you're using the default rules instead of tailoring them to your app, this is where to start!) We're excited to announce that in the last few months we've released some substantial improvements to the tools for writing and debugging Rules, improvements to the Rules language itself, and increases to the size limits for Rules!. These are a few of the great new features. Check out the Security Rules Release Notes for a comprehensive list of everything we've released.
We've released several improvements to make the rules language more expressive and succinct. One particularly verbose pattern was comparing the new values of a document to existing values. The new Set type available in Rules is purpose-built for these comparisons, and also has methods for functionality you'd expect for a Set, like getting the intersection, union, or difference between Sets. For examples:
Set type
Allow a user to create a document if the document has required and optional fields, but not others:
allow create: if (request.resource.data.keys().toSet() .hasOnly(["required","and","optional","keys"])
Sets come with == and in operators and hasAll, hasAny, hasOnly, difference, intersection, union, and size methods.
==
in
hasAll
hasAny
hasOnly
difference
intersection
union
size
Sets are most useful in conjunction with the Map class, and because the request and resource objects are both structured as maps, you're probably already familiar with it. Map recently got a few new methods, diff and get, that will hopefully open the door to more concise rules for everyone. Here's how they work:
Map
request
resource
diff
get
Map.diff() is called on one map, and takes the second map as an argument: map1.diff(map2). It returns a MapDiff object, and all of the MapDiff methods, like addedKeys, changedKeys, or affectedKeys return a Set object.
map1.diff(map2)
addedKeys
changedKeys
affectedKeys
Set
Map.diff() can solve some verbose patterns like checking which fields changed before and after a request. For example, this rule allows an update if the "maxLevel" field was the only field changed:
allow update: if request.resource.data.diff(resource.data).changedKeys().hasOnly(["maxLevel"]);
In the next example, posts have a field indicating the user role required to modify the post. We'll use Map.get() to get the "roleToEdit" field. If the document doesn't have the field, it will default to the "admin" role. Then we'll compare that to the role that's on the user's custom claims:
"roleToEdit"
"admin"
allow update, delete: if resource.data.get("roleToEdit", "admin") == request.auth.token.role;
Keep in mind that because Sets are not ordered but Lists are. You can convert a List to a Set, but you can't convert a Set to a List.
Local variables have been one of the most requested features in Rules, and they're now available within functions. You can declare a variable using the keyword let, and you can have up to 10 local variables per function.
let
Say you're commonly checking that a user meets the same three conditions before granting access: that they're an owner of the product or an admin user, that they successfully answered a challenge question, and that they meet the karma threshold.
rules_version = '2'; service cloud.firestore { match /databases/{database}/documents { match /products/{product} { allow read: if true; allow write: if (exists(/databases/$(database)/documents/admins/$(request.auth.uid)) || exists(/databases/$(database)/documents/product/owner/$(request.auth.uid))) && get(/databases/$(database)/documents/users/$(request.auth.uid)) .data.passChallenge == true && get(/databases/$(database)/documents/users/$(request.auth.uid)) .data.karma > 5; } match /categories/{category} { allow read: if true; allow write: if (exists(/databases/$(database)/documents/admins/$(request.auth.uid)) || exists(/databases/$(database)/documents/product/owner/$(request.auth.uid))) && get(/databases/$(database)/documents/users/$(request.auth.uid)) .data.passChallenge == true && get(/databases/$(database)/documents/users/$(request.auth.uid)) .data.karma > 5; } match /brands/{brand} { allow read, write: if (exists(/databases/$(database)/documents/admins/$(request.auth.uid)) || exists(/databases/$(database)/documents/product/owner/$(request.auth.uid))) && get(/databases/$(database)/documents/users/$(request.auth.uid)) .data.passChallenge == true && get(/databases/$(database)/documents/users/$(request.auth.uid)) .data.karma > 5; } } }
Those conditions, along with the paths I'm using for lookups can all now become variables in a function, which creates more readable rules:
rules_version = '2'; service cloud.firestore { match /databases/{database}/documents { function privilegedAccess(uid, product) { let adminDatabasePath = /databases/$(database)/documents/admins/$(uid); let userDatabasePath = /databases/$(database)/documents/users/$(uid); let ownerDatabasePath = /databases/$(database)/documents/$(product)/owner/$(uid); let isOwnerOrAdmin = exists(adminDatabasePath) || exists(ownerDatabasePath); let meetsChallenge = get(userDatabasePath).data.get("passChallenge", false) == true; let meetsKarmaThreshold = get(userDatabasePath).get("karma", 1) > 5; return isOwnerOrAdmin && meetsChallenge && meetsKarmaThreshold; } match /products/{product} { allow read: if true; allow write: if privilegedAccess(); } match /categories/{category} { allow read: if true; allow write: if privilegedAccess(); } match /brands/{brand} { allow read, write: if privilegedAccess(); } } }
You can see at a glance that the same conditions grant access to write to documents in the three different collections.
The updated version also uses map.get() to fetch the karma and passChallenge fields from the user data, which helps keep the new function concise. In this example, if there is no karma field for a user, then the get returns false. Keep in mind that Map.get() fetches a specific field, and is separate from the DocumentReference.get() that fetches a document.
map.get()
karma
passChallenge
Map.get()
DocumentReference.get()
This is the first time we've introduced an if/else control flow, and we hope it will make rules smoother and more powerful.
if/else
Here's an example of using a ternary operator to specify complex conditions for a write. A user can update a document in two cases: first, if they're an admin user, they need to either set the field overrideReason or approvedBy. Second, if they're not an admin user, then the update must include all the required fields:
overrideReason
approvedBy
allow update: if isAdminUser(request.auth.uid) ? request.resource.data.keys().toSet().hasAny(["overrideReason", "approvedBy"]) : request.resource.data.keys().toSet().hasAll(["all", "the", "required", "fields"])
It was possible to express this before the ternary, but this is a much more concise expression.
And finally, here's a feature for those of you with longer rules. Until now, rules files had to be smaller than 64 KB. (To be more specific, the compiled AST of the rules file had to be smaller than 64 KB, and you wouldn't know you were within the limit until you tried to deploy the rules.) This limit was holding some developers back, and once you reached the limit, you had to start making tradeoffs in your rules. We definitely wanted to fix this.
Since this is one of the limits that helps rules return a decision in nanoseconds, we wanted to find a way to increase the limit without sacrificing performance. We optimized how we compile and store the Rules file, and we were able to quadruple the limit to 256 KB!
The limits on rules are in place to keep rules fast enough to return a decision in nanoseconds, but we work hard to keep them workable. Let us know if you start to outgrow any of them
All of these features are informed by the feedback we hear from you about what's great, what's hard, and what's confusing about Firestore Security Rules, so keep letting us know what you think!
Hello, Cloud Firestore developers! We wanted to let you know about some useful new querying features we've added to Cloud Firestore this week. Starting with… in queries!
With the in query, you can query a specific field for multiple values (up to 10) in a single query. You do this by passing a list containing all the values you want to search for, and Cloud Firestore will match any document whose field equals one of those values.
in queries are a good way to run simple OR queries in Cloud Firestore. For instance, if the database for your E-commerce app had a customer_orders collection, and you wanted to find which orders had a "Ready to ship", "Out for delivery" or "Completed" status, this is now something you can do with a single query, like so:
customer_orders
We've launched another feature similar to the in query, the array-contains-any query. This feature allows you to perform array-contains queries against multiple values at the same time.
array-contains-any
array-contains
For example, if your app had a products collection, and those documents contained an array of categories that every item belongs in, you could now look for items that were in the "Appliances" or "Electronics" category, by passing these values into a single array-contains-any query.
Note that the baby monitor document will only be returned once in your query, even though it matches with multiple categories.
These queries are also supported in the Firebase console, which gives you the ability to try them out on your dataset before you start modifying your client code.
This also seems like a good time to remind you that you can apply filters directly in the Firebase console. Neat, huh?
Security rule behavior for these queries is pretty straightforward. Cloud Firestore will look at each potential value passed in for your in or array-contains-any operation and make sure your query would be allowed for that value. If any value is not allowed, the entire query fails.
For example, if your project was set up with these security rules…
match /projects/{project} { allow read: if resource.data.status != "secret"; ... }
This request would work…
db.collection("projects").where("status", "in", ["public", "unlisted"]);
...but this entire request would fail, because it's possible that our query will return documents that are forbidden in our security rules.
db.collection("projects").where("status", "in", ["public", "unlisted", "secret"]);
Not sure why we couldn't just send you back the allowed documents? Make sure to review the 'Rules are not filters' section of this video.
While we're excited to have you unlock the potential of in queries and array-contains-any queries, you should know about a few important limitations:
I think there's a lot of exciting things you can do now with in queries, and we're looking forward to hearing what new functionality you've added to your apps. So make sure you've upgraded your client libraries to the latest versions to take advantage of the new features, check out the documentation, and happy databasing!
Firebase is a great platform for developing rich mobile and web applications by leveraging the power and scale of the Google Cloud Platform. Firebase provides a wide range of composable backend services and SDKs that help developers overcome numerous challenges in app development including user authentication, data storage, notification delivery, and more.
In addition to the services and the SDKs, Firebase also offers security rules -- a powerful mechanism that helps enforce the security and logical correctness of your apps. The backend services use security rules to authorize and validate the requests made by client apps, and make sure they adhere to the policies that app developers have put in place. Today, you can use security rules to govern how your users interact with the Firebase Realtime Database, Cloud Storage, and Cloud Firestore. Rules in these Firebase products help you achieve two critical goals:
If you're using any Firebase product mentioned above, rules are essential. But you may have questions about how they fit into your application architecture. In order to shed some light on this subject, we'd like to share a few tips related to security rules and the Admin SDK.
As you explore security rules in depth, you will eventually discover that requests from the Firebase Admin SDK are not gated by rules. The Admin SDK is initialized with a service account, which gives the SDK full access to your data. In Firebase Realtime Database, you can scope the Admin SDK's privileges to a user ID, and enforce rules as usual. But other products, most notably Google Cloud Firestore, don't support this feature yet. You should be mindful about that when implementing server-side data access operations.
Because of the elevated privileges of service accounts and the Admin SDK, you should also make sure that they only get deployed in environments that you trust with administrative control of your project. Typical environments include servers controlled by the developers, and managed cloud environments like Google Cloud Functions and App Engine. On the other hand, end-user devices and web browsers where the application code is open for modification are inherently untrusted, and the Admin SDK should never be deployed in them.
Many applications have data that is critical to the operation of the app, but should never be modified by the users. Consider a forum app that promotes user engagement by awarding its participants points (think StackOverflow). Each forum post needs to be scored in near real-time so the users can track their progress, but the users themselves should never be able to change anyone's points, not even their own.
The simplest way to protect such application-managed data is to specify a rule that prevents all writes to the data from the users.
service cloud.firestore { match /databases/{database}/documents { function isAuthorized() { // Some function that grants users read access. } match /scores/{uid}/{document} { allow write: if false; // Nothing gets past me (except Admin of course). allow read: if isAuthorized(); // Grant read access as necessary. } } }
Then you can use the Admin SDK to implement backend services that keep the data up-to-date. For instance, you can implement a serverless function using Cloud Functions for Firebase that automatically executes whenever a user posts something in the forum. This function can determine how many points to award the user, and update the respective entries in the read-only scores collection.
scores
import * as admin from 'firebase-admin'; admin.initializeApp(); export const updateScores = functions.firestore.document('posts/{userId}/{postId}') .onCreate((snapshot, context) => { const score = calculateScore(snapshot); const userId = context.params.userId; const doc = admin.firestore().collection('scores').document(userId); return admin.firestore().runTransaction((txn) => { return txn.get(doc).then((snap) => { const current = snap.data().total || 0; txn.set(doc, {total: current + score}, {merge: true}); }); }); });
Since Cloud Functions is a trusted environment, the backend code can continue to update your data, while keeping users from doing something they are not allowed to.
Many applications need to deal with users in different roles. What individual users can do in the app usually depends on their roles. Let's take a MOOC (Massively Open Online Courses) app as an example, where there are teachers, students and TAs. Teachers and TAs should be able to view and update course content, but students should only be able to view the material.
In a Firebase app, user roles can be managed by setting custom claims on user accounts. This is a privileged operation that can only be performed in a backend environment, typically using the Admin SDK. Custom claims are additional information that we associate with user accounts in Firebase Auth, and this information becomes available in the ID tokens that Firebase issues to users upon sign in. You can inspect these claims via security rules to facilitate role-based access control.
Going back to our example MOOC app, we can use the following backed code to grant a user teacher role.
import * as admin from 'firebase-admin'; admin.initializeApp(); async function grantTeacherRole(userId: string) { await admin.auth().setCustomUserClaims(userId, {role: 'teacher'}); }
Now you can define a rule that only allows teachers and TAs write-access to the courses collection.
courses
service cloud.firestore { match /databases/{database}/documents { function isTeacher() { return request.auth.token.role == "teacher"; } function isTA() { return request.auth.token.role == "ta"; } match /courses/{doc} { allow write: if isTeacher() || isTA(); // Only teachers and TAs can write. allow read: if true; // But anybody can read. } } }
Note that Firebase client SDKs cache ID tokens up to an hour. Therefore changes to a user's custom claims may take up to an hour to take effect.
Sometimes you want the ability to withhold some data from users until an administrator or a backend service determines it's time to release the data. For example, consider an automated process that grades tests in a MOOC app. You would want this process to finish grading all the tests before any scores are shared with the students. In this case the grading process should be able to update any Firestore document, and it can be deployed in a trusted backend environment. Therefore you can use the Admin SDK to implement it.
To make sure the intermediate states of data are not visible to users, you can create each document with a visibility attribute set to "private". Then in security rules, restrict access to only those documents whose visibility attribute is set to "public". Here's what this rule would look like:
visibility
"private"
"public"
service cloud.firestore { match /databases/{database}/documents { function isPublic() { return resource.data.visibility == "public"; } match /grades/{document} { allow read: if isPublic(); // Cannot read unless marked as "public". allow write: if false; // Nobody except Admin can update the documents. } } }
With the above rules configuration in place, all documents created with the visibility attribute set to "private" are inaccessible to the end-users. When the backend process is ready to release a document to the users, it can use the Admin SDK to change the visibility attribute of the target document to "public".
import * as admin from 'firebase-admin'; admin.initializeApp(); async function gradeTests() { // Create a new document and continue to write to it. const doc = await createNewDoc(); await updateGrades(doc); // Later, make the document visible when ready. await releaseGrades(doc); } async function createNewDoc() { const doc = admin.firestore().collection('grades').document(); // Make the new doc hidden by default await doc.set({visibility: 'private'}); return doc; } async function releaseGrades(doc) { await doc.update({visibility: 'public'}); }
As soon as the visibility attribute is set to "public" on a document, it will start appearing in matching Firestore queries executed by users.
It can be tempting to write rules that apply across collections -- for example, writing a rule that grants teachers in the MOOC app access to all documents in the database. In such situations, remember that rules will grant access to a document if any match statement in the rules configuration grants access. When multiple rules apply to the same document, it is easy to forget that any rule that allows access, overrides all the other rules that deny access.
service cloud.firestore { match /databases/{database}/documents { match /reports/{document} { // This rule is intended to selectively grant users read-only access to the // documents in the 'reports' collection. But the rule below inadvertently // grants teachers read-write access to these documents. allow read: if isConditionMet(); allow write: if false; } match /{document=**} { // This rule matches all documents in the database, including the 'reports' // collection. In case of teachers, this will override the previous rule. allow read, write: if isTeacher(); } } }
To avoid accidentally granting users access to protected data in your app, you should try to write rules in a manner so that each document only matches a single rules statement. One way to make that easier is to avoid wildcards that match collections ({document=**}), and only use wildcards that match documents ({document}). If you're tempted to define overarching rules, consider if the Admin SDK would be a better fit, because as we learned in the Tip #1, requests from the Admin SDK bypasses security rules.
{document=**}
{document}
As your apps grow and evolve over time, you may implement various administrative tools to manage your app's data. For example, you may want to implement a tool that backs up certain Firestore collections or RTDB paths. Or you are trying to meet specific privacy requirements, and you want to implement a service that deletes user data when the data becomes obsolete or when the users demand it. Such tools typically require unrestricted access to large portions of your database.
At first this may look like a good reason to have a relaxed set of security rules. But you should strive to write the most detailed and restrictive rules that describe the access patterns of your app. Administrative tools should be implemented using the Admin SDK, and deployed in a privileged environment that you control. This way your admin tools can retain full access to all the data, while closely regulating what end-users can do in the app.
In some situations you may want to temporarily deny a user access to data. Perhaps the monitoring infrastructure of your forum app has just detected a user posting spam, and you want to prevent that user from posting any more content until you can conduct a thorough investigation of the incident. You can use security rules to implement a simple access control list (ACL) on top of Firestore, and use the Admin SDK to dynamically manage it. You would start by declaring a rule like the following:
service cloud.firestore { match /databases/{database}/documents { function isBlackListed() { return exists(/databases/$(database)/documents/blacklist/$(request.auth.uid)) } // Collections are closed for reads and writes by default. This match block // is included for clarity. match /blacklist/{entry} { allow read: if false; allow write: if false; } match /posts/{postId} { allow write: if !isBlackListed() } } }
This mentions a Firestore collection named blacklist that no user can read or write. It also uses the exists built-in function to check if a document with a given key exists in the Firestore database. If you haven't seen this pattern before, built-in functions like exists and get enable us to access Firestore documents from security rules. In this case, if we find a user ID in the blacklist collection, we prevent the corresponding user from writing to the posts collection. Now we can use the Admin SDK to add users to the blacklist collection, and revoke their write-access:
blacklist
exists
posts
await revokeWriteAccess('bAdAgEnT'); async function revokeWriteAccess(userId) { const user = admin.firestore().collection('blacklist').document(userId) await user.set({ reason: 'possible bad agent', blacklisted_at: admin.firestore.FieldValue.serverTimestamp(), }); }
Since you have already locked down all access to the blacklist collection, you can rest assured that only the Admin SDK (i.e. our backend code) can make modifications to it. Changes to the ACL take effect immediately. To grant a user access to the data again, simply remove the corresponding document with the user ID from the blacklist collection.
Note that we are also writing the current timestamp to the same document when adding a user to the blacklist. If you want, you can write a rule that references this property to automatically grant blacklisted users access after a cool off period.
service cloud.firestore { function isTwoDaysElapsed() { return request.time > timestamp.value(get(/databases/$(database)/documents/ blacklist/$(request.auth.uid)).data.blacklisted_at.seconds*1000) + duration.value(2, 'd'); } match /databases/{database}/documents { match /posts/{postId} { // allow if blacklisted more than 2 days ago allow write: if isTwoDaysElapsed(); } } }
Firebase takes a declarative approach to ensuring the security and logical correctness of your apps. By keeping the rules separate from application code, you can easily update your security policies, while keeping the application code simple. As many developers know by experience, code changes are harder to make, and even harder to test and deploy. But with Firebase, you can rapidly iterate on your rules without having to touch the application code at all. Moreover, you can patch any detected security vulnerabilities instantly, without having to go through a long and arduous app rollout.
You can also use rules in conjunction with the Firebase Admin SDK to implement sophisticated use cases that involve server-side code. Admin SDK is not subjected to rules checks, but this extra degree of freedom enables some useful patterns that can be applied to multiple real world applications. You can implement any server-side components using the Admin SDK and deploy them in trusted environments like Google Cloud Functions, while subjecting the client-side apps to stricter constraints.
Read more about Firebase security rules and the Admin SDK in our documentation. If you have used these tools to solve any interesting problems, we'd love to hear about your experience. Happy coding with Firebase!
We all know that securing your database from malicious or misguided clients is critical. And with Security Rules for Cloud Firestore, you can create a very powerful access control system with simple matching syntax and logic.
Until now, however, testing your rules was difficult. You couldn't test your rules before deploying them, and running arbitrary tests against these rules (to ensure they worked the way you expected) wasn't easy, either.
Today, we're pleased to announce our first big step in making it easier to secure your Cloud Firestore database with the release of the Rules Simulator.
With the new Rules Simulator in the Firebase console, you can test your rules as you write them — and before you deploy!
The simulator lets you test document reads, writes, and deletes against any part of your Cloud Firestore database. It will also let you simulate being signed in with a particular userID, so you can better test user-based access control. And for more sophisticated auth-based security, the simulator will help you build authentication tokens for various providers, giving you a preview of what that token will look like and allowing you to directly map the shape of the token to the rules you are writing.
The simulator tests against the rules as they are currently drafted in your editor, not as they are in deployment, allowing you to rapidly test different rules with different types of requests. This means that next time you click the publish button, you can have more confidence that your rules are protecting your data and doing exactly what you expect them to do!
You can get started today with the simulator by navigating over to the Rules section of the Firestore panel in the console.
We've also significantly increased the number of get(), exists() and getAfter() calls you can make in each security rule. For a single document request, you can now make 10 document access calls (up from 3). For multi-resource requests, such as batched writes, you'll be able to make a total of 20 document access calls for all documents in that request.
get()
exists()
getAfter()
Check out our documentation for more information and examples.
Firestore Security Rules may look like JavaScript, but they're actually a purpose-built language with its own unique syntax and behavior. While we've always provided guides to help you write security rules, many developers mentioned to us that it is too hard to discover all of the functions, types, and edge-cases that you need to learn in order to write complex rules.
That's why we published comprehensive reference documentation on the security rules language and the built-in types and functions that it provides. We hope this will enable you to be more confident when writing advanced rules conditions.
The Firebase console gives you the power to make changes to your Cloud Firestore Security Rules directly from your browser! Unfortunately, that also means your team has the ability to break your security rules directly from your browser, maybe without remembering exactly what they changed. Well fear no more; Firebase has your back!
Recently, we added Version History to Cloud Firestore Security Rules. For any Cloud Firestore project, you can now browse all previously published versions of Rules, view the differences between the previous and current versions, and edit the current version -- either to a complete rollback to an earlier version or to a mix of rules.
Now, when your team introduces a bad security rule, it's a snap to find out what the previous working version was and get back to it.
To start using version history for Security Rules, simply navigate to the Rules tab of Cloud Firestore, and start browsing your version history in the left-hand column. From any older version, you can click "Compare to Latest" to view the diff and edit the latest version.
Every deploy that includes Rules is considered a new version; you'll see unchanged versions if you've deployed unchanged rules several times from the command line. To avoid that, you can call deploy --only from the Firebase CLI to deploy only the things you've changed. For example, I often make edits to my project's Cloud Functions without changing anything else, so I end up running firebase deploy --only functions from the command-line tool to make sure only the changes to my Cloud Functions get submitted.
deploy --only
firebase deploy --only functions
Reach out to us via Twitter @Firebase or via our other support channels to let us know what you think! We're looking forward to adding this to other Firebase features, and would like to get your feedback before we do.
