Inject Detect Progress Report

Written by Pete Corey on May 1, 2017.

It’s been almost two months since I announced I was working on a security focused SaaS application called Inject Detect.

For those that haven’t been following along, Inject Detect is a service designed to detect NoSQL Injection attacks against your Meteor applications. It does this by monitoring queries made against your application, looking for unexpected queries that may be the result of an injection attack.

I had lots of ideas about how I wanted to build out Inject Detect. To keep myself accountable and in an effort to iterate in public, I’ve decided to put together a progress report.

Let’s dive into how my plans have played out, where I’m at in the project, and most importantly let’s talk about when Inject Detect will be ready to use!

Front-end Progress

Since it was announced, I’ve been making steady headway on both the front-end and back-end components of Inject Detect.

The front-end of Inject Detect is being built as a React application, backed by Create React App tooling. On top of vanilla React, I’m using Apollo client to integrate with my Absinthe-powered GraphQL back-end.

So far, this combination has been a dream to work with.

The productivity gains I’ve experienced working with React and Apollo is off the charts. After climbing over a few learning curves, I’ve found myself effortlessly cranking out feature after feature.

I’m addicted to the GraphQL workflow.


The front-end of Inject Detect is still heavily under construction. I’ll be the first to say that I’m no designer. I’m using Semantic UI as the base for most of my designs and tweaking from there.

Overall, I’m very happy with the progress I’ve made so far on the front-end.

Check out a few screen shots to see where I’m at:






Since NoSQL Injection is a relatively unknown (but unbelievably common) vulnerability, I’m trying to incorporate healthy doses of education into its user interface.

I’m discovering that balancing education with brevity and clarity is a difficult thing to do.

Back-end Progress

Most of the first month of development was spent building out the back-end infrastructure and business logic to handle all of the various use cases of Inject Detect.

In my post about the high level design of Inject Detect, I talked about implementing the core domain of the application using Event Sourcing.

So far, I’m very happy with this choice.

Let’s look a little closer at some of the design decisions I’ve made, and dive into what it means to be an “Event Sourced” system.


Interactions with the system are done through “commands”. A command is just an instruction for the system to do something. Based on the current state of the system, the processing of a command will either return a list of events representing the changes to the system, or an error.

Keep in mind that events don’t actually modify the system in any way (write to a database, etc…). They just return a list of events, side-effect free.

Diving into the code, a command is just an Elixir struct. For example, here’s a command to toggle “alerting” on an application in Inject Detect:


defmodule InjectDetect.Command.ToggleAlerting do
  defstruct application_id: nil
end

The struct holds all of the information we need to carry out the command. In this case, we just need the application_id of the application in question.

Each command implements a Command protocol, which means it defines a handle function. Command.handle takes in the command struct being handled and a “context” map, which in our case holds the currently signed in user.

Our handle implementation for the ToggleAlerting command looks like this:


defimpl InjectDetect.Command, for: InjectDetect.Command.ToggleAlerting do

  alias InjectDetect.Event.TurnedOffAlerting
  alias InjectDetect.Event.TurnedOnAlerting
  alias InjectDetect.State.Application

  def toggle_alerting(application = %{user_id: user_id}, command, %{user_id: user_id}) do
    case application.alerting do
      true ->
        {:ok, [%TurnedOffAlerting{application_id: command.application_id}]}
      false ->
        {:ok, [%TurnedOnAlerting{application_id: command.application_id}]}
    end
  end

  def toggle_alerting(_, _, _) do
    {:error, %{code: :not_authorized,
               error: "Not authorized",
               message: "Not authorized"}}
  end

  def handle(command, context) do
    Application.find(command.application_id)
    |> toggle_alerting(command, context)
  end

end

If the current user has permission to toggle alerting on the specified application, we return either a TurnedOffAlerting event, or a TurnedOnAlerting event.

Otherwise, we throw an authorization error.


Events, like commands, are just Elixir structs. The TurnedOffAlerting event we mentioned earlier looks something like this:


defmodule InjectDetect.Event.TurnedOffAlerting do
  defstruct application_id: nil
end

Again, the only information we need to represent this event is the application_id of the application in question.

Events implement a Reducer protocol, which defines a apply function. The apply function takes in the system’s current state as its first argument, and the event being applied as the second argument. It’s purpose is to transform the current state according to the event being applied.

The Reducer implementation for TurnedOffAlerting looks like this:


defimpl InjectDetect.State.Reducer,
   for: InjectDetect.Event.TurnedOffAlerting do

  def apply(event, state) do
    put_in(state, [Lens.key(:users),
                   Lens.all,
                   Lens.key(:applications),
                   Lens.filter(&(&1.id == event.application_id)),
                   Lens.key(:alerting)], false)
  end

end

We basically just dig through our application’s state structure, finding the application we care about and we set its alerting key to false.


You may have noticed that we’re passing the entire system’s state into each Reducer.apply function call. Does this mean that the entire system’s state needs to exist in memory at all times?

Yes!

Inject Detect is storing application state entirely in memory as a Memory Image.

This means that Inject Detect isn’t using a database to hold information about the application’s users, applications, and queries. The only thing being stored in the database is a stream of events.

Instead, Inject Detect stores this stateful information in a long-lived GenServer process. Every time we grab the application’s current state (InjectDetect.State.get), it queries the database for any events that have happened since the last get, applies them using Reducer.apply, and then returns the resulting state.

This was definitely the most radical decision I made while building Inject Detect, but in my experience so far, it has proven to be incredibly powerful.


I definitely made some adventurous design decisions when implementing Inject Detect’s back-end. So far, I’m incredibly satisfied with my decisions to date.

I’m eager to see how they perform under continued development, load testing, and real-world usage.

I’m planning on writing more articles outlining and detailing these design choices in the future. If you’re particularly interested in any one aspect of this system, reach out and let me know!

What’s Next?

While I didn’t mention it in this post, the Meteor plugin component of Inject Detect is essentially finished. The back-end portion of the projects is a few loose ends and a few missing features away from being completed. The front-end of the application represents the bulk of the remaining work, but it’s moving along at a steady pace.

I expect to be ready for beta testing for a small number of real-world users in the next one or two months.

If you haven’t yet, be sure to subscribe to the Inject Detect newsletter to get official news on the release as soon as it’s ready!

Passwordless Authentication with Phoenix Tokens

Written by Pete Corey on Apr 24, 2017.

Subtitled: I got 99 problems, but a password ain’t one.

I’m in the process of building a security-focused SaaS application (shameless plug: Inject Detect), and I’ve decided to use a passwordless authentication scheme. Since I’ve decided to stop using passwords, I feel like a great burden has been lifted from my shoulders.

In this post, let’s dig into how awesome passwordless authentication is, and just how easy it is to set up in your Elixir/Phoenix application.

Passwordless in a Passwordful World

Before we dig into the nuts and bolts of building out a passwordless system, we should probably talk about what exactly “passwordless” means.

How can we authentication users without passwords?

The general idea behind a passwordless authentication scheme is that instead of a user regurgitating a password to prove their identity, they’re emailed a “magic link” that, when clicked, will activate their session.


In many ways, a passwordless authentication scheme is very similar to traditional password-based authentication. The only difference is that we require the user makes a trip to their inbox.

So why bother? Shouldn’t we focus on creating less work for our users? Aren’t passwords fine?

It turns out that passwords aren’t fine. There are numerous problems with passwords as we know them. Not only do people often choose poor passwords and have deplorable password habits (full disclosure: I’m one of these people), but they fundamentally don’t do the job they’re designed to do.

How so?

Authentication ultimately boils down to proving you are who you say you are. This is often done by presenting the system with a fact that can only be known by you. If you can produce this fact, the system assumes that you are who you say you are.

Unfortunately, your passwords aren’t secrets only known by you. Every time you use (or reuse) a password in a system, you’re giving that system knowledge of your password. You’re trusting the ethics and technical competency of that system with the defining factor of your online identity.


How is passwordless better?

I believe that passwordless authentication is a better alternative over password-based authentication for the simple reason that turns authentication into a process of active consent, rather than the passive transfer of a piece of information.

Your active consent cannot be given to another system, or stolen by an attacker. As long as you control the channel through which consent is granted (email, SMS, etc…), you control your identity.

Take the power back!

Going Passwordless with Phoenix Tokens

Now that I’ve spent all that time waxing poetic about the beauties of passwordless authentication, let’s talk about how can actually implement it in a Elixir/Phoenix based application.

I debated going into great detail in this section discussing how to implement passwordless authentication in a few different stack permutations (Vanilla Phoenix, React, Apollo, Absinthe, etc…), but instead, let’s talk about the common theme in all of these implementations: Phoenix Tokens.

Phoenix Tokens do two things that turn out to be invaluable for building out a passwordless authentication scheme:

  • They generate cryptographically strong bearer tokens.
  • They let you make assertions about the age of a token.

There are three major workflows of a passwordless system. Let’s run through each of them and see how easy they are to implement using Phoenix Tokens.

Signing Up

In a passwordless system, all we need to create an account for a new user is their email address.

If we don’t care to verify the email address they provided, we can immediately sign them in by using Phoenix.Token.sign to generate the user an auth_token:


Phoenix.Token.sign(Endpoint, user.id, :crypto.strong_rand_bytes(32))

This auth_token will be saved and passed down to the client and stored in localStorage. Any subsequent requests to the server will send along this token to identify the currently logged in user.

When the server receives a request with an attached auth_token, it can look up the associated user.

If we want to limit the maximum age of a user’s session, we can verify the token using Phoenix.Token.verify and pass in a :max_age in seconds:


Phoenix.Token.verify(Endpoint, user.id, auth_token, max_age: 1209600)

In this example, we’re limiting sessions to two weeks (or 1,209,600 seconds). If a user tries to use an expired token, or a token not associated with any users, we return an error.

Signing Out

Once our new user has signed up, signing out is as simple as deleting their associated auth_token.

Once the auth_token is removed, and cleared from their browser’s localStorage, all subsequent requests they make will be unauthenticated until they sign back in.

Signing In

Now we’re getting to the interesting part.

Once our user has signed out, how do they sign back into our passwordless application?

On the “sign in” page, the user will enter their email address and click a “Send me a magic link” button. Next, our server will use Phoenix.Token.sign to generate a new requested_token, which will be saved and emailed to the provided email address.


Phoenix.Token.sign(Endpoint, user.id, :crypto.strong_rand_bytes(32))

The email will contain a link to a “verify requested token” route in our application which takes the requested_token as a parameter.

That route looks up the user with the provided requested_token, verifies that the requested_token isn’t expired, generates a new auth_token for that user, and finally removes the verified requested_token from the user:


Phoenix.Token.verify(Endpoint, user.id, requested_token, max_age: 600)

Phoenix.Token.sign(Endpoint, user.id, :crypto.strong_rand_bytes(32))

In this example, our “magic link” emails only last for ten minutes.

Once a user clicks the link, their new auth_token will be sent down to the client and they’ll be automatically signed in!

Final Thoughts

Passwordless authentication is definitely new territory for me, and I suspect, a lot of other software developers.

I strongly believe that it’s important to explore other options for user authentication. The status quo simply isn’t working. Whether you look at it from a user experience perspective, or from a perspective of security, traditional passwords in practice are ineffective and wrought with problems.

Passwordless authentication may not be the ideal solution, but I believe that it’s a step in the right direction.

If you want to see passwordless authentication in action, sign up for the Inject Detect newsletter to receive the latest news on its upcoming release!

Who Needs Lodash When You Have Elixir?

Written by Pete Corey on Apr 17, 2017.

Before adventuring into the land of Elixir, I used Javascript day in and day out for both front-end and back-end development. Javascript’s (lack of) standard libraries forced me to rely heavily on third-party tools and libraries such as Underscore and Lodash.

I became very proficient at working with these tools, and after initially starting with Elixir, I felt very clumsy with the new language. I wasn’t able to accomplish the things I could easily and quickly do with Javascript and Lodash.

Over the past few months, I’ve become much more comfortable with the language, and I’ve realized that Elixir’s standard library outclasses Lodash in nearly every way.

Let’s dig into the two and see how we would translate the Lodash-isms we know and love into Elixir code.

The Usual Suspects

For many functions in Lodash, there’s an obvious mapping to an equivalent function in Elixir’s standard library.

For example, the usual suspects like _.map, _.reduce, _.find, and _.filter all have equivalent functions in Elixir’s Enum module:


_.map([1, 2, 3], n => n + 1)  // Enum.map([1, 2, 3], &(&1 + 1))

_.reduce([1, 2, 3], (s, n) => s + n)  // Enum.reduce([1, 2, 3], &(&2 + &1))

_.includes([1, 2, 3], 2)  // Enum.member?([1, 2, 3], 2)

_.filter([1, 2, 3], n => n < 3)  // Enum.filter([1, 2, 3], &(&1 < 3))

Other commonly used Lodash functions such as _.uniq (Enum.uniq), _.find (Enum.find), _.keyBy (Enum.group_by), etc. also have their counterparts in the Elixir standard library.

Getting Nested Values

I’ve also come to heavily rely on Lodash’s _.get and _.set functions to grab and update values in deeply nested data structures.

Using _.get lets me grab a nested value (or undefined) even if the intermediary objects and arrays don’t exist. For example, instead of writing:


if (foo && foo.bar && foo.bar.baz) {
  return foo.bar.baz.bot;
}

I can simply write:


return _.get(foo, "bar.baz.bot");

When I first started working with Elixir, I really missed being able to do this. Working with complex, nested data structures felt so clunky! That was before I found out about the awesome power of Elixir’s Access behavior and the family of functions built around it.

In Elixir, we can use the get_in function to grab values (or nil) out of nested structures, even if the intermediary values don’t exist:


get_in(foo, [:bar, :baz, :bot])

We can even pass in dynamic lookup fields, which would have required string manipulation in the Javascript example:


get_in(foo, [:bar, some_id, :baz])

Additionally, we can use Accessor functions to take our Elixir-foo to the next level. For example, we could grab the second user’s name (if it exists, otherwise we get nil):


get_in(..., [:users, Access.at(1), :name])

Or we could grab all of the users’ names:


get_in(..., [:users, Access.all(), :name])

If we wanted any of these values or intermediary values to have a default value, we could use Access.key:


get_in(..., [:users, Access.all(), Access.key(:name, "Anonymous")])

Let’s see Lodash’s _.get do that!

Setting Nested Values

All of these ideas apply to updating values as well. We can use put_in to directly set a value in a nested data structure, or update_in to update it with a function we provide.

For example, we can set values deep in a data structure, even if the intermediary values don’t exist, with put_in and Access.key:


put_in(%{}, [Access.key(:foo, %{}), :bar], "baz")

Similarly, we can update values with update_in or get_and_update_in.

If the Accessors provided by Elixir’s Access module aren’t enough for your use case, you can even write your own custom accessor functions!

Out of the Box Chaining

Elixir’s proverbial cherry on top is undoubtedly its built-in pipe operator.

To pipe Lodash function calls together, you need to explicitly construct a function chain with _.chain, passing in your initial value, and then call _.value at the end of your chain to retrieve the resulting value.

For example, let’s say we want to count the number of orders a set of users has made:


_.chain(users)
 .map("orders")
 .map(orders => orders.length)
 .sum()
 .value();

Because of Elixir’s stateless, functional nature, the barrier of entry for starting a chain is nonexistent:


users
|> Enum.map(&(&1.orders))
|> Enum.map(&length/1)
|> Enum.sum

Final Thoughts

I’ve yet to find a problem easily solvable with Lodash that isn’t easily solvable with an out-of-the-box tool provided by Elixir. In my experience, Elixir has proven to be incredibly more flexible and more powerful than Lodash.

While I originally felt uncomfortable and clumsy working with data in Elixir, my ever growing understanding of the tools the language provides is helping me regain my confidence.

If you haven’t already checked out Elixir, do it!

If you’re new to Elixir and feeling like a fish out of water, my only advice is to stick with it and read through the guides and documentation. You’ll be swimming again in no time.