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Invalidating JSON Web Tokens

For a new node.js project I'm working on, I'm thinking about switching over from a cookie based session approach (by this, I mean, storing an id to a key-value store containing user sessions in a user's browser) to a token-based session approach (no key-value store) using JSON Web Tokens (jwt).

The project is a game that utilizes socket.io - having a token-based session would be useful in such a scenario where there will be multiple communication channels in a single session (web and socket.io)

How would one provide token/session invalidation from the server using the jwt Approach?

I also wanted to understand what common (or uncommon) pitfalls/attacks I should look out for with this sort of paradigm. For example, if this paradigm is vulnerable to the same/different kinds of attacks as the session store/cookie-based approach.

So, say I have the following (adapted from this and this):

Session Store Login:

app.get('/login', function(request, response) {
    var user = {username: request.body.username, password: request.body.password };
    // Validate somehow
    validate(user, function(isValid, profile) {
        // Create session token
        var token= createSessionToken();

        // Add to a key-value database
        KeyValueStore.add({token: {userid: profile.id, expiresInMinutes: 60}});

        // The client should save this session token in a cookie
        response.json({sessionToken: token});
    });
}

Token-Based Login:

var jwt = require('jsonwebtoken');
app.get('/login', function(request, response) {
    var user = {username: request.body.username, password: request.body.password };
    // Validate somehow
    validate(user, function(isValid, profile) {
        var token = jwt.sign(profile, 'My Super Secret', {expiresInMinutes: 60});
        response.json({token: token});
    });
}

--

A logout (or invalidate) for the Session Store approach would require an update to the KeyValueStore database with the specified token.

It seems like such a mechanism would not exist in the token-based approach since the token itself would contain the info that would normally exist in the key-value store.

If you are using the 'express-jwt' package, you can take a look at the isRevoked option, or attempt to replicate the same functionality. github.com/auth0/express-jwt#revoked-tokens
Consider using a short expiration time on the access token and using a refresh token, with a long-lived expiration, to allow for checking of the user's access status in a database (blacklisting). auth0.com/blog/…
another option would be attaching IP address in payload while generating jwt token and checking stored IP vs incoming request for the same Ip address. ex : req.connection.remoteAddress in nodeJs. There are ISP providers that do not issue static IP per customer, I think this won't be a problem unless a client reconnects to the internet.
I'm inclined to say that it's exactly this problem that makes JWT not very useful. It's a cool solution, and an elegant way to safely break the never-trust-the-client rule, but ultimately solving its problems, chiefly invalidation, always inevitably reintroduces state
There is a simple, quick and elegant way to do what you expect the JWT invalidation should do - logging a user out. See my answer down below.

M
Matt Way

I too have been researching this question, and while none of the ideas below are complete solutions, they might help others rule out ideas, or provide further ones.

1) Simply remove the token from the client

Obviously this does nothing for server side security, but it does stop an attacker by removing the token from existence (ie. they would have to have stolen the token prior to logout).

2) Create a token blocklist

You could store the invalid tokens until their initial expiry date, and compare them against incoming requests. This seems to negate the reason for going fully token based in the first place though, as you would need to touch the database for every request. The storage size would likely be lower though, as you would only need to store tokens that were between logout & expiry time (this is a gut feeling, and is definitely dependent on context).

3) Just keep token expiry times short and rotate them often

If you keep the token expiry times at short enough intervals, and have the running client keep track and request updates when necessary, number 1 would effectively work as a complete logout system. The problem with this method, is that it makes it impossible to keep the user logged in between closes of the client code (depending on how long you make the expiry interval).

Contingency Plans

If there ever was an emergency, or a user token was compromised, one thing you could do is allow the user to change an underlying user lookup ID with their login credentials. This would render all associated tokens invalid, as the associated user would no longer be able to be found.

I also wanted to note that it is a good idea to include the last login date with the token, so that you are able to enforce a relogin after some distant period of time.

In terms of similarities/differences with regards to attacks using tokens, this post addresses the question: https://github.com/dentarg/blog/blob/master/_posts/2014-01-07-angularjs-authentication-with-cookies-vs-token.markdown


The article is well written, and is an elaborated version of 2) above. While it works fine, personally I don't see much difference to traditional session stores. I guess the storage requirement would be lower, but you still require a database. The biggest appeal of JWT for me was to not use a database at all for sessions.
A common approach for invalidating tokens when a user changes their password is to sign the token with a hash of their password. Thus if the password changes, any previous tokens automatically fail to verify. You can extend this to logout by including a last-logout-time in the user's record and using a combination of the last-logout-time and password hash to sign the token. This requires a DB lookup each time you need to verify the token signature, but presumably you're looking up the user anyway.
A blacklist can be made efficient by keeping it in memory, so that the DB need only be hit to record invalidations and remove expired invalidations and only read at server launch. Under a load-balancing architecture, the in-memory blacklist can poll the DB at short intervals, like 10s, limiting the exposure of invalidated tokens. These approaches allow the server to continue authenticating requests without per-request DB accesses.
@TravisTerry Your approach if useful in monolithic apps, but in order to implement it in a microservices app you need all services to either store the user's password and last login or to make requests to fetch them and both are bad ideas.
Another way is to use a random secret for each user, and keep the secret with the user in the database. When a user logout or change password, just change the secret in the database.
A
Andy

The ideas posted above are good, but a very simple and easy way to invalidate all the existing JWTs is simply to change the secret.

If your server creates the JWT, signs it with a secret (JWS) then sends it to the client, simply changing the secret will invalidating all existing tokens and require all users to gain a new token to authenticate as their old token suddenly becomes invalid according to the server.

It doesn't require any modifications to the actual token contents (or lookup ID).

Clearly this only works for an emergency case when you wanted all existing tokens to expire, for per token expiry one of the solutions above is required (such as short token expiry time or invalidating a stored key inside the token).


I think this approach isn't ideal. While it works and is certainly simple, imagine a case where you're using a public key - you wouldn't want to go and recreate that key any time you want to invalidate a single token.
@KijanaWoodard, a public/private key pair can be used to validate the signature as effectively the secret in the RS256 algorithm. In the example shown here he mentions changing the secret to invalidate a JWT. This can be done by either a) introducing a fake pubkey that doesn't match the signature or b) generating a new pubkey. In that situation, it is less than ideal.
@Signus - gotcha. not using the public key as the secret, but others may be relying on the public key to verify the signature.
This is very bad solution. Main reason to use JWT is it's stateless and scales. Using a dynamic secret introduces a state. If the service is clustered across multiple nodes, you would have to synchronize the secret each time new token is issued. You would have to store secrets in a database or other external service, which would be just re-inventing cookie based authentication
@TuomasToivonen, but you must sign a JWT with a secret and be able to verify the JWT with that same secret. So you must store the secret on the protected resources. If the secret is compromised you must change it and distribute that change to each of your nodes. Hosting providers with clustering/scaling usually allow you to store secrets in their service to make distributing these secrets easy and reliable.
r
robsch

This is primarily a long comment supporting and building on the answer by @mattway

Given:

Some of the other proposed solutions on this page advocate hitting the datastore on every request. If you hit the main datastore to validate every authentication request, then I see less reason to use JWT instead of other established token authentication mechanisms. You've essentially made JWT stateful, instead of stateless if you go to the datastore each time.

(If your site receives a high volume of unauthorized requests, then JWT would deny them without hitting the datastore, which is helpful. There are probably other use cases like that.)

Given:

Truly stateless JWT authentication cannot be achieved for a typical, real world web app because stateless JWT does not have a way to provide immediate and secure support for the following important use cases:

User's account is deleted/blocked/suspended.

User's password is changed.

User's roles or permissions are changed.

User is logged out by admin.

Any other application critical data in the JWT token is changed by the site admin.

You cannot wait for token expiration in these cases. The token invalidation must occur immediately. Also, you cannot trust the client not to keep and use a copy of the old token, whether with malicious intent or not.

Therefore:

I think the answer from @matt-way, #2 TokenBlackList, would be most efficient way to add the required state to JWT based authentication.

You have a blacklist that holds these tokens until their expiration date is hit. The list of tokens will be quite small compared to the total number of users, since it only has to keep blacklisted tokens until their expiration. I'd implement by putting invalidated tokens in redis, memcached or another in-memory datastore that supports setting an expiration time on a key.

You still have to make a call to your in-memory db for every authentication request that passes initial JWT auth, but you don't have to store keys for your entire set of users in there. (Which may or may not be a big deal for a given site.)


I don't agree with your answer. Hitting a database does not make anything stateful; storing state on your backend does. JWT was not created so that you don't have to hit the database on each request.Every major application that uses JWT is backed by a database. JWT solves a completely different problem. en.wikipedia.org/wiki/Stateless_protocol
@Julian can you elaborate on this a little? Which problem does JWT really solve then?
@zero01alpha Authentication: This is the most common scenario for using JWT. Once the user is logged in, each subsequent request will include the JWT, allowing the user to access routes, services, and resources that are permitted with that token. Information Exchange: JSON Web Tokens are a good way of securely transmitting information between parties. Because JWTs can be signed you can be sure the senders are who they say they are. See jwt.io/introduction
@Julian I don't agree with your disagreement :) JWT solves the problem (for services) to have the need to access a centralized entity providing authorization information for any given client. So instead of service A and service B have to access some resource to find out if client X has or has not permissions to do something, service A and B receive a token from X that proves his/hers permissions (most commonly issued by a 3rd party). Anyway, JWT is a tool that helps avoiding a shared state between services in a system, especially when they are controlled by more than one service provider.
Also from jwt.io/introduction If the JWT contains the necessary data, the need to query the database for certain operations may be reduced, though this may not always be the case.
D
DaftMonk

I would keep a record of the jwt version number on the user model. New jwt tokens would set their version to this.

When you validate the jwt, simply check that it has a version number equal to the users current jwt version.

Any time you want to invalidate old jwts, just bump the users jwt version number.


This is an interesting idea, the only thing is where to store the version, as part of the purpose of tokens is it being stateless and not needing to use the database. A hard coded version would make it hard to bump, and a version number in a database would negate some of the benefits of using tokens.
Presumably you're already storing a user id in your token, and then querying the database to check that the user exists / is authorized to access the api endpoint. So you aren't doing any extra db queries by comparing the jwt token version number with the one on the user.
I shouldn't say presumably, because theres a lot of situations where you might use tokens with validations that don't touch the database at all. But I think in this case its hard to avoid.
What if user logs in from multiple devices? Should one token be used across them all or should login invalidate all previous ones?
I agree with @SergioCorrea This would make JWT almost as stateful as any other token authentication mechanism.
A
Ashtonian

Haven't tried this yet, and it is uses a lot of information based on some of the other answers. The complexity here is to avoid a server side data store call per request for user information. Most of the other solutions require a db lookup per request to a user session store. That is fine in certain scenarios but this was created in an attempt to avoid such calls and make whatever required server side state to be very small. You will end up recreating a server side session, however small to provide all the force invalidation features. But if you want to do it here is the gist:

Goals:

Mitigate use of a data store (state-less).

Ability to force log out all users.

Ability to force log out any individual at any time.

Ability to require password re-entry after a certain amount of time.

Ability to work with multiple clients.

Ability to force a re-log in when a user clicks logout from a particular client. (To prevent someone "un-deleting" a client token after user walks away - see comments for additional information)

The Solution:

Use short lived (<5m) access tokens paired with a longer lived (few hours) client stored refresh-token.

Every request checks either the auth or refresh token expiration date for validity.

When the access token expires, the client uses the refresh token to refresh the access token.

During the refresh token check, the server checks a small blacklist of user ids - if found reject the refresh request.

When a client doesn't have a valid(not expired) refresh or auth token the user must log back in, as all other requests will be rejected.

On login request, check user data store for ban.

On logout - add that user to the session blacklist so they have to log back in. You would have to store additional information to not log them out of all devices in a multi device environment but it could be done by adding a device field to the user blacklist.

To force re-entry after x amount of time - maintain last login date in the auth token, and check it per request.

To force log out all users - reset token hash key.

This requires you to maintain a blacklist(state) on the server, assuming the user table contains banned user information. The invalid sessions blacklist - is a list of user ids. This blacklist is only checked during a refresh token request. Entries are required to live on it as long as the refresh token TTL. Once the refresh token expires the user would be required to log back in.

Cons:

Still required to do a data store lookup on the refresh token request.

Invalid tokens may continue to operate for access token's TTL.

Pros:

Provides desired functionality.

Refresh token action is hidden from the user under normal operation.

Only required to do a data store lookup on refresh requests instead of every request. ie 1 every 15 min instead of 1 per second.

Minimizes server side state to a very small blacklist.

With this solution an in memory data store like reddis isn't needed, at least not for user information as you are as the server is only making a db call every 15 or so minutes. If using reddis, storing a valid/invalid session list in there would be a very fast and simpler solution. No need for a refresh token. Each auth token would have a session id and device id, they could be stored in a reddis table on creation and invalidated when appropriate. Then they would be checked on every request and rejected when invalid.


What about the scenario where one person gets up from a computer to let another person use the same computer? The 1st person will logout and expect the logout to instantly block the 2nd person. If the 2nd person is an average user, the client could easily block the user by deleting the token. But if the 2nd user has hacking skills, the user has time to recover the still-valid token to authenticate as the 1st user. It seems that there is no way avoid the need to immediately invalidate tokens, without delay.
Or you can remove your JWT from sesion/local storage or cookie.
Thanks @Ashtonian. After doing extensive research, I abandoned JWTs. Unless you go to extraordinary lengths to secure the secret key, or unless you delegate to a secure OAuth implementation, JWTs are much more vulnerable than regular sessions. See my full report: by.jtl.xyz/2016/06/the-unspoken-vulnerability-of-jwts.html
Using a refresh token is the key to allowing blacklisting. Great explanation: auth0.com/blog/…
This seems to me the best answer as it combines a short-lived access token with a long-lived refresh token that can be blacklisted. On logout, client should delete the access token so a 2nd user can't get access (even though the access token will remain valid for a few more minutes after logout). @Joe Lapp says a hacker (2nd user) get the access token even after it's been deleted. How?
B
Brack Mo

An approach I've been considering is to always have an iat (issued at) value in the JWT. Then when a user logs out, store that timestamp on the user record. When validating the JWT just compare the iat to the last logged out timestamp. If the iat is older, then it's not valid. Yes, you have to go to the DB, but I'll always be pulling the user record anyway if the JWT is otherwise valid.

The major downside I see to this is that it'd log them out of all their sessions if they're in multiple browsers, or have a mobile client too.

This could also be a nice mechanism for invalidating all JWTs in a system. Part of the check could be against a global timestamp of the last valid iat time.


Good thought! To solve the "one device" problem is to make this a contingency feature rather than a logout. Store the a date on the user record that invalidates all tokens issued before it. Something like token_valid_after, or something. Awesome!
Like all the other proposed solutions, this one requires a database lookup which is the reason this question exists because avoiding that lookup is the most important thing here! (Performance, scalability). Under normal circumstances you don't need a DB lookup to have the user data, you already got it from the client.
This can be easily combined with the refresh token approach suggested in a different answer to reduce the number of accesses to the data store.
M
Matas Kairaitis

I'm a bit late here, but I think I have a decent solution.

I have a "last_password_change" column in my database that stores the date and time when the password was last changed. I also store the date/time of issue in the JWT. When validating a token, I check if the password has been changed after the token was issued and if it was the token is rejected even though it hasn't expired yet.


How do you reject the token? Can you show a brief example code?
if (jwt.issue_date < user.last_pw_change) { /* not valid, redirect to login */}
Requires a db lookup!
A
Aman Kumar Gupta

----------------Bit late for this answer but may be it will help to someone----------------

From the Client Side, the easiest way is to remove the token from the storage of browser.

But, What if you want to destroy the token on the Node server -

The problem with JWT package is that it doesn't provide any method or way to destroy the token. You may use different methods with respect to JWT which are mentioned above. But here i go with the jwt-redis.

So in order to destroy the token on the serverside you may use jwt-redis package instead of JWT

This library (jwt-redis) completely repeats the entire functionality of the library jsonwebtoken, with one important addition. Jwt-redis allows you to store the tokenIdentifier in redis to verify validity. The absence of a tokenIdentifier in redis makes the token not valid. To destroy the token in jwt-redis, there is a destroy method

it works in this way :

Install jwt-redis from npm To Create:

var redis = require('redis'); var JWTR = require('jwt-redis').default; var redisClient = redis.createClient(); var jwtr = new JWTR(redisClient); const secret = 'secret'; const tokenIdentifier = 'test'; const payload = { jti: tokenIdentifier }; // you can put other data in payload as well jwtr.sign(payload, secret) .then((token)=>{ // your code }) .catch((error)=>{ // error handling });

To verify:

jwtr.verify(token, secret);

To Destroy:

// if jti passed during signing of token then tokenIdentifier else token jwtr.destroy(tokenIdentifier or token)

Note :

1). You can provide expiresIn during signin of token in the same as it is provided in JWT.

2). If jti is not passed during signing of token then jti is generated randomly by the library.

May be this will help you or somebody else. Thanks.


This approach seems to be the best proposed. But, if I have multiple servers then I'd have to sync the token labels whenever there's a change, right?
Thanks @Eren, Yes if you have multiple servers and there is any change in token's configuration then offcourse you need to sync it again. And there is also way to destroy the token via label by calling jwtr.destroy(jti) ("jti is json token identifier") you can pass it in payload while signing the token and if not passed then library will randomly generate the jti of token. Please refer here for more details "npmjs.com/package/jwt-redis"
@Eren Updated proposed answer as well. Thanks!
N
NickVarcha

You can have a "last_key_used" field on your DB on your user's document/record.

When the user logs in with user and pass, generate a new random string, store it in the last_key_used field, and add it to the payload when signing the token.

When the user logs in using the token, check the last_key_used in the DB to match the one in the token.

Then, when user does a logout for instance, or if you want to invalidate the token, simply change that "last_key_used" field to another random value and any subsequent checks will fail, hence forcing the user to log in with user and pass again.


This is the solution I've been considering, but it has these drawbacks: (1) you're either doing a DB-lookup on each request to check the random (nullifying the reason for using tokens instead of sessions) or you're only checking intermittently after a refresh token has expired (preventing users from logging out immediately or sessions from being terminated immediately); and (2) logging out logs the user out from all browsers and all devices (which is not conventionally expected behavior).
You don't need to change the key when the user logs out, only when they change their password or -if you provide it- when they choose to log out from all devices
E
Eduardo

Keep an in-memory list like this

user_id   revoke_tokens_issued_before
-------------------------------------
123       2018-07-02T15:55:33
567       2018-07-01T12:34:21

If your tokens expire in one week then clean or ignore the records older than that. Also keep only the most recent record of each user. The size of the list will depend on how long you keep your tokens and how often users revoke their tokens. Use db only when the table changes. Load the table in memory when your application starts.


Most production sites run on more than one server so this solution will not work. Adding Redis or similar interpocess cache significantly complicates the system and often brings more problems than solutions.
@user2555515 all servers can be synchronized with the database. It is your choice hitting the database everytime or not. You could tell what problems it brings.
M
Mark Essel

Unique per user string, and global string hashed together

Here's an example:

HEADER:ALGORITHM & TOKEN TYPE

{
  "alg": "HS256",
  "typ": "JWT"
}
PAYLOAD:DATA

{
  "sub": "1234567890",
  "some": "data",
  "iat": 1516239022
}
VERIFY SIGNATURE

HMACSHA256(
  base64UrlEncode(header) + "." +
  base64UrlEncode(payload), 
  HMACSHA256('perUserString'+'globalString')
)

where HMACSHA256 is your local crypto sha256
  nodejs 
    import sha256 from 'crypto-js/sha256';
    sha256(message);

for example usage see https://jwt.io (not sure they handle dynamic 256 bit secrets)


Some more detail would suffice
@giantas, i think what Mark mean is the signature part. So instead using only single key to sign the JWT, combine it a key that unique for each client. Therefore, if you want invalidate a user's all session, just change the key for that user and if you to invalidate all session in your system, just change that global single key.
good one, but apparently, would still require a DB lookup
d
davidkomer

Why not just use the jti claim (nonce) and store that in a list as a user record field (db dependant, but at very least a comma-separated list is fine)? No need for separate lookup, as others have pointed out presumably you want to get the user record anyway, and this way you can have multiple valid tokens for different client instances ("logout everywhere" can reset the list to empty)


Yes, this. Maybe make a one-to-many relation between the user table and a new (session) table, so you can store meta data along with the jti claims.
S
Shamseer

Late to the party, MY two cents are given below after some research. During logout, make sure following things are happening...

Clear the client storage/session

Update the user table last login date-time and logout date-time whenever login or logout happens respectively. So login date time always should be greater than logout (Or keep logout date null if the current status is login and not yet logged out)

This is way far simple than keeping additional table of blacklist and purging regularly. Multiple device support requires additional table to keep loggedIn, logout dates with some additional details like OS-or client details.


J
James111

I did it the following way:

Generate a unique hash, and then store it in redis and your JWT. This can be called a session We'll also store the number of requests the particular JWT has made - Each time a jwt is sent to the server, we increment the requests integer. (this is optional)

So when a user logs in, a unique hash is created, stored in redis and injected into your JWT.

When a user tries to visit a protected endpoint, you'll grab the unique session hash from your JWT, query redis and see if it's a match!

We can extend from this and make our JWT even more secure, here's how:

Every X requests a particular JWT has made, we generate a new unique session, store it in our JWT, and then blacklist the previous one.

This means that the JWT is constantly changing and stops stale JWT's being hacked, stolen, or something else.


You can hash the token itself and store that value in redis, rather than inject a new hash into the token.
Also check out aud and jti claims in JWT, you are on the right path.
E
Ebru Yener

Give 1 day expiry time for the tokens Maintain a daily blacklist. Put the invalidated / logout tokens into the blacklist

For token validation, check for the token expiry time first and then the blacklist if token not expired.

For long session needs, there should be a mechanism for extending token expiry time.


put tokens into blacklist and there goes your statelessness
If you maintain the backlist in the database, you still stay stateless
put blacklist into the database and there go your performance and scalability.
V
Valentin

Kafka message queue and local black lists

I thought about using a messaging system like kafka. Let me explain:

You could have one micro service (let call it userMgmtMs service) for example which is responsible for the login and logout and to produce the JWT token. This token then gets passed to the client.

Now the client can use this token to call different micro services (lets call it pricesMs), within pricesMs there will be NO database check to the users table from which the initial token creation was triggered. This database has only to exist in userMgmtMs. Also the JWT token should include the permissions / roles so that the pricesMs do not need to lookup anything from the DB to allow spring security to work.

Instead of going to the DB in the pricesMs the JwtRequestFilter could provide a UserDetails object created by the data provided in the JWT token (without the password obviously).

So, how to logout or invalidate a token? Since we do not wanna call the database of userMgmtMs with every request for priecesMs (which would introduce quite a lot of unwanted dependencies) a solution could be to use this token blacklist.

Instead of keeping this blacklist central and haveing a dependency on one table from all microservices, I propose to use a kafka message queue.

The userMgmtMs is still responsible for the logout and once this is done it puts it into its own blacklist (a table NOT shared among microservices). In addition it sends a kafka event with the content of this token to a internal kafka service where all other microservices are subscribed to.

Once the other microservices receive the kafka event they will put it as well in their internal blacklist.

Even if some microservices are down at the time of logout they will eventually go up again and will receive the message at a later state.

Since kafka is developed so that clients have their own reference which messages they did read it is ensured that no client, down or up will miss any of this invalid tokens.

The only issue again what I can think of is that the kafka messaging service will again introduce a single point of failure. But it is kind of reversed because if we have one global table where all invalid JWT tokens are saved and this db or micro service is down nothing works. With the kafka approach + client side deletion of JWT tokens for a normal user logout a downtime of kafka would in most cases not even be noticeable. Since the black lists are distributed among all microservies as an internal copy.

In the off case that you need to invalidate a user which was hacked and kafka is down this is where the problems start. In this case changing the secret as a last resort could help. Or just make sure kafka is up before doing so.

Disclaimer: I did not implement this solution yet but somehow I feel that most of the proposed solution negate the idea of the JWT tokens with having a central database lookup. So I was thinking about another solution.

Please let me know what you think, does it make sense or is there an obvious reason why it cant?


I agree with your approach. When we talk about possibility, MQ are way more stable than we thought.
I finished the happy path for this idea and it seems to work fine. Micro services can be totally independent and only check against their local copy of the black list. If they are down they will receive all messages when they go up again so no risk of loosing a message. Assuming there are no glitches in the MQ. Now I am looking into the issue how to do CSRF protection, not sure how this will play out.
I just added the grantedAuthorities and the user id to the JWT with this information I am able to use the WebSecurityConfigurerAdapter like I would have the real user database in my micro services (antMatchers etc.). If the user roles and permissions change this needs then also trigger an invalidate message to the MQ to inform the other microservices that the current JWT token with the included rights are also invalid.
A
Arik

If you want to be able to revoke user tokens, you can keep track of all issued tokens on your DB and check if they're valid (exist) on a session-like table. The downside is that you'll hit the DB on every request.

I haven't tried it, but i suggest the following method to allow token revocation while keeping DB hits to a minimum -

To lower the database checks rate, divide all issued JWT tokens into X groups according to some deterministic association (e.g., 10 groups by first digit of the user id).

Each JWT token will hold the group id and a timestamp created upon token creation. e.g., { "group_id": 1, "timestamp": 1551861473716 }

The server will hold all group ids in memory and each group will have a timestamp that indicates when was the last log-out event of a user belonging to that group. e.g., { "group1": 1551861473714, "group2": 1551861487293, ... }

Requests with a JWT token that have an older group timestamp, will be checked for validity (DB hit) and if valid, a new JWT token with a fresh timestamp will be issued for client's future use. If the token's group timestamp is newer, we trust the JWT (No DB hit).

So -

We only validate a JWT token using the DB if the token has an old group timestamp, while future requests won't get validated until someone in the user's group will log-out. We use groups to limit the number of timestamp changes (say there's a user logging in and out like there's no tomorrow - will only affect limited number of users instead of everyone) We limit the number of groups to limit the amount of timestamps held in memory Invalidating a token is a breeze - just remove it from the session table and generate a new timestamp for the user's group.


Same list can be kept in memory (application for c#) and it would eliminate the need for hitting the db for each request. The list can be loaded from db on application start
u
user2555515

If "logout from all devices" option is acceptable (in most cases it is):

Add the token version field to the user record.

Add the value in this field to the claims stored in the JWT.

Increment the version every time the user logs out.

When validating the token compare its version claim to the version stored in the user record and reject if it is not the same.

A db trip to get the user record in most cases is required anyway so this does not add much overhead to the validation process. Unlike maintaining a blacklist, where DB load is significant due to the necessity to use a join or a separate call, clean old records and so on.


O
Olumide

USING REFRESHING OF JWT...

An approach that I take as being practical is to store a refresh token (which can be a GUID) and a counterpart refresh token ID (that does not change no matter how many refreshes are done) on the database and add them as claims for the user when the user's JWT is being generated. An alternative to a database can be used, e.g. memory cache. But I'm using database in this answer.

Then, create a JWT refresh Web API endpoint that the client can call before the expiry of the JWT. When the refresh is called, get the refresh token from the claims in the JWT.

On any call to the JWT refresh endpoint, validate the current refresh token and the refresh token ID as a pair on the database. Generate a new refresh token, and use it to replace the old refresh token on the database, using the refresh token ID. Remember they are claims that can be extracted from the JWT

Extract the user's claims from the current JWT. Begin the process of generating a new JWT. Replace the value of the old refresh token claim with the newly generated refresh token that has also been newly saved on the database. With all that, generate the new JWT and send it to the client.

So, after a refresh token has been used, whether by the intended user or an attacker, any other attempt to use a/the refresh token, that is not paired, on the database, with its refresh token ID, would not lead to the generation of a new JWT, hence preventing any client having that refresh token ID from being able to use the backend anymore, leading to a full logout of such clients (including the legitimate client).

That explains the basic information.

The next thing to add to that is to have a window for when a JWT can be refreshed, such that anything outside that window would be a suspicious activity. For example, the window can be 10min before the expiration of a JWT. The date-time a JWT was generated can be saved as a claim in that JWT itself. And when such suspicious activity occurs, i.e. when someone else tries to reuse that refresh token ID outside or within the window after it has already been used within the window, should mark the refresh token ID as invalid. Hence, even the valid owner of the refresh token ID would have to log in afresh.

A refresh token that can't be found to be paired, on the database, with a presented refresh token ID implies that the refresh token ID should be invalidated. Because an idle user may try to use a refresh token that an attacker, for example, has already used.

A JWT that was stolen and used by an attacker, before the intended user does, would be marked as invalid too when the user attempts to use the refresh token too, as explained earlier.

The only situation not covered is if a client never attempts to refresh its JWT even after an attacker may have already stolen it. But this is unlikely to happen to a client that's not in custody (or something similar) of an attacker, meaning that the client cannot be predicted by the attacker as regards when the client would stop using the backend.

If the client initiates a usual logout. The logout should be made to delete the refresh token ID and associated records from the database, hence, preventing any client from generating a refresh JWT.


c
codeman48

The following approach could give best of both worlds solution:

Let "immediate" mean "~1 minute".

Cases:

User attempts a successful login: A. Add an "issue time" field to the token, and keep the expiry time as needed. B. Store the hash of user's password's hash or create a new field say tokenhash in the user's table. Store the tokenhash in the generated token. User accesses a url: A. If the "issue time" is in the "immediate" range, process the token normally. Don't change the "issue time". Depending upon the duration of "immediate" this is the duration one is vulnerable in. But a short duration like a minute or two shouldn't be too risky. (This is a balance between performance and security). Three is no need to hit the db here. B. If the token is not in the "immediate" range, check the tokenhash against the db. If its okay, update the "issue time" field. If not okay then don't process the request (Security is finally enforced). User changes the tokenhash to secure the account. In the "immediate" future the account is secured.

We save the database lookups in the "immediate" range. This is most beneficial if there are a bursts of requests from the client in the "immediate" time duration.


This is useful for just how to use jwts without db lookups, but how does one enforce a logout? A removal of the tokenhash from the db?
@funseiki Yes. On a user logout the token can be removed from the client and the tokenhash changed to a special value. In the "immediate" future all other possible copies become invalid too and hence forcing a re-login. Drawback: it logs out the user from all devices (haven't thought how to overcome this yet).
O
Olumide

WITHOUT USING REFRESHING OF JWT...

2 scenarios of an attack come to mind. One is about compromised login credentials. And the other is an actual theft of JWT.

For compromised login credentials, when a new login happens, normally send the user an email notification. So, if the customer doesn't consent to being the one who logged in, they should be advised to do a reset of credentials, which should save to database/cache the date-time the password was last set (and set this too when user sets password during initial registration). Whenever a user action is being authorized, the date-time a user changed their password should be fetched from database/cache and compared to the date-time a given JWT was generated, and forbid the action for JWTs that were generated before the said date-time of credentials reset, hence essentially rendering such JWTs useless. That means save the date-time of generation of a JWT as a claim in the JWT itself. In ASP.NET Core, a policy/requirement can be used to do do this comparison, and on failure, the client is forbidden. This consequently logs out the user on the backend, globally, whenever a reset of credentials is done.

For actual theft of JWT... A theft of JWT is not easy to detect but a JWT that expires easily solves this. But what can be done to stop the attacker before the JWT expires? It is with an actual global logout. It is similar to what was described above for credentials reset. For this, normally save on database/cache the date-time a user initiated a global logout, and on authorizing a user action, get it and compare it to the date-time of generation of a given JWT too, and forbid the action for JWTs that were generated before the said date-time of global logout, hence essentially rendering such JWTs useless. This can be done using a policy/requirement in ASP.NET Core, as previously described.

Now, how do you detect the theft of JWT? My answer to this for now is to occasionally alert user to globally log out and log in again, as this would definitely log the attacker out.


E
Erisan Olasheni

A good approach to invalidating a token would still need database trips. For a purpose that includes when some parts of the user record change, for example changing roles, changing passwords, email, and more. One can add a modified or updated_at field in the user record, which records the time of this change, and then you include this in the claims. So when a JWT is authenticated, you compare the time in the claims with the one recorded in the DB, if that of the claim was before, then token is invalid. This approach is also similar to storing the iat in the DB.

Note: If you're using the modified or updated_at option, then you will also have to update it when the user logs in and out.


N
Normal

Simply create add the following object to your user schema:

const userSchema = new mongoose.Schema({
{
... your schema code,
destroyAnyJWTbefore: Date
}

and whenever you receive a POST request on /login change the date of this document to Date.now()

finally, in your authentication checking code, i.e, in your middleware where you check for isAuthanticated or protected or whatever the name you're using, simply add a validation that checks the myjwt.iat is greater than userDoc.destroyAnyJWTbefore.

This solution is the best when it comes to security if you wanted to destroy the JWT on the server-side.

This solution is no longer client-side dependent, it breaks the main goal of using JWTs which is to stop storing tokens on the server-side.

it depends on your project context, but most likely you will want to destroy the JWT from the server.

If you wanted to only destroy the token from the client-side, simply remove the cookie from the browser (if your client is a browser), the same can be done on smartphones or any other client.

In case chose to destroy the token from the server-side, I suggest that you use Radis to quickly perform this operation, by implementing the black-list style mentioned by other users.

The main question now is: are JWTs useless? God knows.


btw, a better name for destroyAnyJWTbefore is "lastLogout"
To answer my question are JWTs useless? I would say no because the security risk of a stolen token before a user updates his password is pretty much low. and as the old saying "Keep it simple and stupid", don't overthink the stuff. so there's actually no need to destroy the token on the server-side. period (.)
T
Tharsanan

I am going to answer If we need to provide logout from all devices feature when we are using JWT. This approach will use database look-ups for each requests. Because we need a persistence security state even if there is a server crash. In the user table we will have two columns

LastValidTime (default: creation time) Logged-In (default: true)

Whenever there is a log out request from the user we will update the LastValidTime to current time and Logged-In to false. If there is a log in request we wont change LastValidTime but Logged-In will be set to true.

When we create the JWT we will have the JWT creation time in the payload. When we authorize for a service we will check 3 conditions

Is JWT valid Is JWT payload creation time is greater than User LastValidTime Is user Logged-In

Lets see a practical scenario.

User X has two devices A, B. He logged in to our server at 7 pm using device A and device B. (lets say JWT expire time is 12 hrs). A and B both have JWT with createdTime : 7pm

At 9 pm he lost his device B. He immediately log out from the device A. That means Now our database X user entry has LastValidTime as "ThatDate:9:00:xx:xxx" and Logged-In as "false".

At 9:30 the Mr.Thief tries to log in using device B. We will check the database even the Logged-In is false so we wont allow.

At 10 pm Mr.X log in from his device A. Now device A has JWT with created time : 10pm. Now database Logged-In is set to "true"

At 10:30 pm Mr.Thief tries to log in. Even though the Logged-In is true. The LastValidTime is 9 pm in the database but B's JWT has created time as 7pm. So he wont be allowed to access the service. So using device B without having the password he cannot use already created JWT after one device log out.


C
Community

IAM solution like Keycloak (which I'have worked on) provide Token Revocation endpoint like

Token Revocation Endpoint /realms/{realm-name}/protocol/openid-connect/revoke

Of if you simply want to logout an useragent(or user), you could call an endpoint as well(this would simply invalidate the Tokens). Again, in the case of Keycloak, the Relying Party just needs to call the endpoint

/realms/{realm-name}/protocol/openid-connect/logout

Link in case if you want to learn more


G
George I.

An alternative would be to have a middleware script just for critical API endpoints. This middleware script would check in the database if the token is invalidated by an admin. This solution may be useful for cases where is not necessary to completely block the access of a user right away.


M
MyDaftQuestions

In this example, I am assuming the end user also has an account. If this isn't he case, then the rest of the approach is unlikely to work.

When you create the JWT, persist it in the database, associated with the account that is logging in. This does mean that just from the JWT you could pull out additional information about the user, so depending on the environment, this may or may not be OK.

On every request after, not only do you perform the standard validation that (I hope) comes with what ever framework you use (that validates the JWT is valid), it also includes soemthing like the user ID or another token (that needs to match that in the database).

When you log out, delete the cookie (if using) and invalidate the JWT (string) from the database. If the cookie can't be deleted from the client side, then at least the log out process will ensure the token is destroyed.

I found this approach, coupled with another unique identifier (so there are 2 persist items in the database and are available to the front end) with the session to be very resilient


H
Hai Phaikawl

Here's how to do it without having to call the database on every request:

Keep a hashmap of valid tokens in a memory cache (e.g a LRU with limited size)

When checking a token: if the token is in cache, return the result immediately, no database query is needed (majority case). Otherwise perform a full check (query the database, check for user status & invalidated tokens...). Then update the cache.

When invalidating a token: add it to a blacklist in database, then update the cache, send signal to all servers if needed.

Keep in mind that the cache should have limited size, like a LRU, otherwise you might run out of memory.


Y
Yilmaz

Even if you delete the token from storage, it is still valid, but only for short period to reduce the probability of it being used maliciously.

You could create a deny-listing and once you delete the token from the storage you can add the token to this list. If you have a microservice service, all other services which consume this token have to add extra logic to check this listing. This will centralized your authentication, because each server has to check an centralized data structure.


J
Jose V

This seems really difficult to solve without a DB lookup upon every token verification. The alternative I can think of is keeping a blacklist of invalidated tokens server-side; which should be updated on a database whenever a change happens to persist the changes across restarts, by making the server check the database upon restart to load the current blacklist.

But if you keep it in the server memory (a global variable of sorts) then it's not gonna be scalable across multiple servers if you are using more than one, so in that case you can keep it on a shared Redis cache, which should be set-up to persist the data somewhere (database? filesystem?) in case it has to be restarted, and every time a new server is spun up it has to subscribe to the Redis cache.

Alternative to a black-list, using the same solution, you can do it with a hash saved in redis per session as this other answer points out (not sure that would be more efficient with many users logging in though).

Does it sound awfully complicated? it does to me!

Disclaimer: I have not used Redis.