Getting Started with Curiefense
This Quick Start guide shows how to quickly deploy Curiefense, set up some basic security policies, and test them.
Prerequisite: Ubuntu 20.04 LTS
In this guide, we will deploy Curiefense using Docker Compose, then test and configure.
If you want to use Helm instead of Docker Compose, or if you want more control over the deployment options, then do this:
Go to the Deployment in Depth: First Tasks page and follow its instructions.
Go to the appropriate Deployment in Depth page (Docker Compose or Helm) and follow its instructions.
Return here to the Verify the Deployment section below, and continue.
Let's begin
To ensure we have all tools in place, we will run:
Grab the latest code from GitHub to get started:
ProTip: Try Curiefense out on Katacoda, no install necessary.
Verify the Deployment
This tutorial assumes that host names curie.demo and api.curie.demo are mapped to the host machine. You may replace it with the IP of your host, or set your /etc/hosts file accordingly. For example, if docker-compose was executed locally, then
127.0.0.1 curie.demo api.curie.demo
At this point you should have the following http interfaces:
Interface
URL
Management UI
http://curie.demo:30080/
Swagger API
http://curie.demo:30000/api/v1/
Echo web server
http://curie.demo:30081/
Grafana
http://curie.demo:30300/
Make sure everything is working by testing the echo server:
Deployed Containers Overview
This section describes the newly-described components of Curiefense. Feel free to skip it if desired, and go straight to the instructions for policy and rules configuration.
What Have We Just Deployed?
This diagram will help us understand the containers we just deployed, their connections, and the data flow:
Container Name
Purpose and Functionality
curieproxy
Envoy built with our modules
curiesync
ensures configurations are always in sync with latest policies and rules changes
curielogger
pushes Envoy access log to postgresql and metrics to prometheus
confserver
API server to manage configuration
curielogserver
REST API interface for reading and analyzing logs from PostgreSQL
uiserver
UI Management Console
echo
Dummy web server for testing
logdb *
stores access log
grafana *
dashboards
prometheus *
stores time series metrics
redis *
Synchronizes session and rules across deployments and Envoy containers
(*) You may replace these containers with your own if desired.
Terminology and Concepts
Before diving in and making changes, let's discuss a few concepts of Curiefense's configuration.
Git is the storage management used to keep track of changes. This means:
Data can be stored anywhere a git repository can (local, remote, hosted, etc).
Every change you made can be reverted.
You can automate deployments based on tagging.
Using a single configuration server, you can maintain configurations of multiple deployments (e.g. production, devops, qa, rc, etc.) by keeping each in a separate branch, and you can merge them the git way at any point in time, via the API and/or UI.
Configurations are organized in Documents and Entries. More on this here.
Policy and Rules Configuration
Curiefense runs every incoming request (and in some cases, responses as well) through a series of mechanisms. We will now walk through some of them to understand how traffic is handled and processed.
During the procedures described below, you will set up some simple rules and then run some requests through Curiefense. By the end of this process, you will understand how to create security rules and policies, you will observe them being applied, and you will see how Curiefense reports on incoming requests and its reactions to them.
Open the UI
Open the UI management console by going to http://curie.demo:30080/. In the left sidebar, select Document Editor if it is not already selected.
At the top left of the page, in the second pulldown control, select Profiling Lists.
Create a Session Profiling list
Session profiling attaches tags to requests and sessions based on various criteria, from matching headers, cookies, arguments or URLs to traffic sources such as geolocations, IP addresses, CIDRs, and AS numbers. Subsequently, the tags are then used to make decisions about how the requests are handled.
Start by creating a new Profiling List:
Next, in the Tags text box, enter the value trusted .
Then, at the top of the (currently empty) list to the right, add a new entry by selecting the + button. Enter foo for its name, bar for value, and trust me for annotation. Now click on the "add" link.
Your screen should look similar to this:
We have created a simple profiling rule. Every request that contains a header named foo which matches the regex (PCRE) bar will receive a tag of trusted.
(The Annotation of trust me is a label for internal admin use, and does not affect traffic processing.)
Now save the new configuration:
And then publish it:
After publishing, your changes need time to propagate. Waiting 10-15 seconds should be enough.
Now it is time to test our configuration. Let's run the following curl commands:
Navigating to Access Log in the left sidebar should show a screen similar to this:
Click on the /with/header entry, and notice the trusted tag on the right column:
Notice also that along the trusted tag you defined, Curiefense attached a number of tags that were generated automatically. More information about this.
Profiling Lists are a powerful feature of Curiefense (and are explained in depth here). We just demonstrated the ability to create a single-entry self-managed list that characterizes incoming requests based on a header. Curiefense allows you to attach tags based on complex combinations of headers, arguments, cookies, geolocation, methods, paths, and more. External data sources are also supported; sessions can be profiled based on data and rules defined by a third party, such as blocklists and whitelists.
Now that we know how to attach tags to incoming requests, let's tell Curiefense how to react to them.
Create an ACL (Access Control List)
We're going to block all requests with the trusted tag.
In the left menu, navigate to Document Editor. By default, ACL Profiles should already be selected.
Enter trusted into the DENY column, then save your changes.
Your screen should look similar to this:
Publish the new configuration again (and wait 15 seconds for the changes to propagate).
Test the ACL
Run this command:
In the Access Log, you should see the request listed. Expanding it will show this:
Note that the request was identified as a risk, because it contains the specified tag and therefore matches the DENY ACL.
However, Curiefense passed the request through the system, as seen in the green HTTP status code (200: successful). If it had been blocked, the code would instead be red with an error code.
This behavior is expected. By default, Curiefense's security profiles are in report/monitor mode; requests will be flagged but not blocked. This mode allows for testing and fine-tuning of new configurations without affecting traffic.
Let's assume that we've tested our new policies and want to make the ACL active.
Activate the ACL
Navigate to Document Editor and then choose to edit URL Maps in the upper dropdown list.
URL Maps assign security policies to paths within the protected application. You can assign policies at any scale, from globally down to individual URLs. (They are explained in depth here.)
We're going to edit Curiefense's default security profile: the one that applies to every URL which does not otherwise have any policies assigned to it.
Expand the default profile (the one assigned to path /) by selecting it. Then activate the profile by checking the Active Mode checkbox.
Save your changes and publish the configuration again.
After the change propagates, Curiefense should block the request:
Add Rate Limiting
You have seen how to create security policies that filter hostile requests, and how to assign these policies to paths within your application.
Now we'll see how to filter requests that are not obviously hostile at first, but which display hostile intent with increased volume. For example, a user who fails a login attempt might have mistyped their password—but a user who fails ten login attempts in a short time is probably trying to guess the password for an account they do not own.
Add a Rate Limit
Return to URL Maps and select the default profile again. At the bottom of its map, there is the Rate Limit Rules section. Currently, it is empty.
Attach an existing rule by select the first "here" link. A pulldown list of available Rate Limit Rules will be displayed.
Open the list, and select its only entry (the one that comes by default with the system). This rule limits requests from a given IP address to a maximum of 5 requests per 60 seconds.
Select the "add" link to add this rule to the default URL Map.
Save your changes, and then publish.
After propagation, we can test it:
Wait briefly, and you should see how the response changes from 403 (ACL) to 503 (Rate limit) on the 6th request.
Add Multiple Rate Limits
Now that we're somewhat familiar with the system, let's set up multi-layered rate limiting to protect against a variety of attacks.
Rate limits in Curiefense are reusable "stand-alone" rules that can be attached to different paths in URL Maps.
Previously, we used the default Rate Limit that comes with Curiefense, and applied it to the entire domain. Now we will create three specific Rate Limits for the login process of an API, and attach them to the relevant endpoints.
Creating a URL Map for the API
Create a new URL Map by duplicating the default one:
Set its name (the unlabeled field at the top) to API. Set Matching Names to api.curie.demo.
Adding Profiles
Note that the new URL Map contains a default profile. As you might expect, this will apply to every path within the scope set by the Matching Names entry. (In this tutorial, the Matching Names is a specific subdomain. In production use, this might be a regex describing a range of domains, subdomains, or URLs.)
To add a profile to a URL Map, open an existing profile (in this case, the default) and select the Fork profile button.
Edit the Name and Match condition of the profile and then repeat this process twice more, so that there are four profiles in total. The Names and Match Conditions are shown below:
At this point, we have four profiles: the default / which we left in place, /api/v1/ and /api/v2 to match API calls of different versions, and an entry for /login that catches both versions.
Setting Rate Limits
Note that the default has one Rate Limit attached to it (shown as a "1" in the RL column), because it already had this when it was duplicated. The other three profiles do not yet have any limits.
For /api/v1/ and /api/v2/ , set the standard rate limit rule as you did before:
For /api/v[1-2]/login, we will create three new rate limit rules.
Create New Rate Limits
Open the Rate Limits section of the UI by selecting Rate Limits at the top of the window (in the pulldown list that currently says URL Maps).
The default Rate Limit should be displayed. Add a new Rate Limit by duplicating it, using the Duplicate Document button in the top right part of the interface.
Rule #1: Limiting IPs
Edit the new Rate Limit so that it limits login attempts from the same IP address, allowing a maximum of three within 10 minutes:
Rule #2: Limiting locations
Create a second Rate Limit by duplicating an existing one. Edit it so that it limits a given User-Id header to a single country within a four hour timespan:
Rule #3: Limit number of User IDs
Create a third Rate Limit by duplicating an existing one. Edit it so that it limits each IP to submitting a maximum of eight unique User IDs:
Using the new Rate Limit rules
Return to the URL Maps section of the interface. Let's attach the new rules to the /api/v[1-2]/login matching path.
Expand the appropriate profile, select the link at the bottom ("To attach an existing rule..."), and select the first of the three new rules you created. Repeat for the second and third rules. When you're finished, you should see something similar to this:
Testing the new Rate Limits
Next, let's try to brute-force the login endpoint, using the same user id and IP, but with a new password each time:
To test the other rule, we will have curl send a unique User ID each time:
As traffic gets blocked (returning a 503 error by default) we can look at the Access Log. When expanding a 503 line, you can see the Risk Details, which include the rate limit rule that was violated (in this case, Dictionary Harvesting).
You can also see the system has generated a tag named after the rule name. Lastly, notice that every request is logged with all details.
Advanced Rate Limiting
The demonstration above is only the beginning of what can be done with Rate Limiting. You can configure Curiefense to limit complex combinations of conditions and events, customize its reactions (including blocking, redirecting, monitoring, responding with custom codes, adding headers to requests for backend evaluation), and more.
Here's a common example. Rate Limits like the ones demonstrated above will block a requestor who exceeds a defined limit within the given timespan. However, once the limit resets, the requestor would be able to try again, and could repeat this cycle as often as desired. To prevent this, you can configure Curiefense to ban a requestor (and block all of their requests) when multiple rate limits are violated.
A full explanation of Curiefense's Rate Limits and their capabilities is available here.
Grafana Dashboards
The docker-compose deployment process will create Grafana visualizations for Curiefense's traffic data.
Curiefense comes with two dashboards out of the box: Traffic Overview and Top Activities. They are available at http://curie.demo:30300/.
Traffic Overview Dashboard
Top Activities
Onwards
You now have a working Curiefense installation to experiment with. Its capabilities go far beyond those demonstrated in this tutorial; browsing through the rest of this Manual (especially the Document Editor section) will give you some ideas to test, so you can see what the platform can do.
Note that this tutorial was a Quick Start guide, and therefore, it used many default options for the deployment. You might want to change some of them; for example, you might want Curiefense to use TLS for its UI server and for communicating with the backend.
Modifying the deployment is straightforward. For Docker Compose, just go through the procedures described here and then re-run docker-compose up. For Helm, go through the procedures here.
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