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Enhancing Runtime-Security with Falco: My Hands-On Experience
9 min read
Containerization and microservices have revolutionized the way applications are developed and deployed. But, with these technological advancements come new challenges in securing the containerized environment. Security in a containerized environment requires a different approach than traditional security mechanisms. It involves the continuous monitoring of container activities, identifying security threats, and ensuring compliance.
In this blog, I share my hands-on experience with Falco, an open-source tool designed specifically for securing containerized environments. It can be easily categorized as the de facto threat detection engine for Kubernetes and for cloud infrastructure. Because of its advanced features and capabilities, Falco has become a popular choice among DevOps and security professionals alike.
I will discuss how Falco enhances security in containerized environments and how it can help in addressing security challenges. I will also share my experience with the tool and provide insights into its features and capabilities.
As we are aware, Linux systems come with isolated environments — userspace and kernel space. Falco operates at both the user space and kernel space. The system calls are intercepted by the kernel module by the executable code deployed inside the OS kernel or using eBPF probes, which allows running scripts safely and performing actions inside the OS. The syscalls are then analyzed using the libraries. Alerts are generated when there is a match in a rule defined in the rule engine and alerted to outputs that are configured as Syslog, files, Standard Output, and others.
Falco can be installed on any local machine, cloud, or Kubernetes cluster. It mainly uses different drivers for collecting system calls' activity on the host. In this post, I will be installing Falco's latest release
v3.41as a Package on my Ubuntu 22.04 system, so that it can detect any malicious activity occurring in the runtime. The detailed installation instruction for installing Faclo can be found in the official docs. I have gone ahead and installed the Falco package using the pre-installed dialog package and chose the
falco-modern-bpf driver for this demo.
Once the installation is complete, we can verify that the Falco package is installed correctly and running by using the
systemctl status falco-modern-bpf.service command:
santosh@~:$ systemctl status falco-modern-bpf.service ● falco-modern-bpf.service - Falco: Container Native Runtime Security with modern ebpf Loaded: loaded (/lib/systemd/system/falco-modern-bpf.service; enabled; vendor preset: enabled) Active: active (running) since Mon 2023-02-27 16:49:51 IST; 32s ago Docs: https://falco.org/docs/ Main PID: 39540 (falco) Tasks: 9 (limit: 14115) Memory: 85.7M CPU: 1.787s CGroup: /system.slice/falco-modern-bpf.service └─39540 /usr/bin/falco --pidfile=/var/run/falco.pid --modern-bpf Feb 27 16:49:51 santoshdts falco: Loading rules from file /etc/falco/falco_rules.yaml Feb 27 16:49:51 santoshdts falco: Loading rules from file /etc/falco/falco_rules.local.yaml Feb 27 16:49:51 santoshdts falco: The chosen syscall buffer dimension is: 8388608 bytes (8 MBs) Feb 27 16:49:51 santoshdts falco: Starting health webserver with threadiness 4, listening on port 8765 Feb 27 16:49:51 santoshdts falco: Enabled event sources: syscall Feb 27 16:49:51 santoshdts falco: Opening capture with modern BPF probe. Feb 27 16:49:51 santoshdts falco: One ring buffer every '2' CPUs. Feb 27 16:50:02 santoshdts falco: 18:23:12.408382864: Error File below /etc opened for writing (user=root user_loginuid=-1 command=falcoc> Feb 27 16:50:15 santoshdts falco: 18:23:25.539821933: Error File below / or /root opened for writing (user=root user_loginuid=1000 comman> Feb 27 16:50:18 santoshdts falco: 18:23:28.101536918: Error File below /etc opened for writing (user=root user_loginuid=-1 command=falcoc>
As you can see from the above output the Falco service is up, and running, and is already collecting logs.
0.34, Falco supports other driver types apart from kernel modules. To see the list of drivers view the
systemd unit-files. However, it is recommended not to run multiple units in parallel :
santosh@~:$ systemctl list-unit-files | grep falco falco-bpf.service disabled enabled falco-custom.service disabled enabled falco-kmod-inject.service static - falco-kmod.service disabled enabled falco-modern-bpf.service enabled enabled falcoctl-artifact-follow.service disabled enabled
Also, you can see from the above system status, Falco by default loads rules from the default directory
/etc/falco/falco_rules.yaml. The default Falco configuration file is also placed in the same directory as
/etc/falco/falco.yaml. This config file contains all the details about the rule files, the log output methods, etc. At the very top of the Falco config file, the order in which the rules will be evaluated is defined:
The order in which the above rules files are defined is important. The defining order decides which rule file Falco will use to evaluate events generated by syscalls as default, which is the first one defined in the list
It is advisable and recommended practice, not to overwrite the main rules file, i.e
etc/falco/falco_rules.yaml file, and make any modifications or additions to the rules in the file located in the same directory by the name
/etc/falco/falco_rules.local.yaml. You can see from the above image, this local rule is defined second in order of preference. We will see this in action later.
Falco ruleset basically is a
yaml file consisting of five main components as a list.
rule: a rule in any ruleset defines the name of the rule being defined.
desc: A short description of the rule.
condition: a condition is the important part in a rule. A condition is a boolean expression, which is evaluated when an event is triggered and detected by Falco. The condition stanza contains various syscall event types, file descriptive combined with some boolean operators. You can also check all the supported fields on the command prompt by using
Output: Output is the field that formats the logs in a readable format. The output is formatted in
<Timestamp> <Severity> <Message>. The message can be broken down into two parts. The first is a human-readable message. The second includes some placeholders (ex:
%user,name), that will be populated when outputted. The placeholders, start with a
%symbol followed by one of the event's supported fields, as in the
Priority: This field indicates the severity of the rule being voilated. This is included in the output logs. Priority field can include values like EMERGENCY, ALERT, CRITICAL, ERROR, WARNING, NOTICE, INFORMATIONAL, DEBUG.
The above structure forms a rule in Falco. But, the rules can include some more fields like,
tags, etc, to form advanced rules. You can read more on this in official docs.
Working with Falco Hands-on
So now, we have some understanding of the Falco rules and Falco configured, up and running. Let's put it to work.
To witness Faclo in action, let's try to open a sensitive file on a Linux system
/etc/sudoers file which needs sudo access. Simultaneously, I will open another terminal to view systemd logs with the
journalctl -fu falco-modern-bpf command:
Falco outputs the logs whenever a condition in a rule matches an event being triggered. You can see, the Falco tool detected that a sensitive file
/etc/shadow was opened for reading with a priority of Warning. The output also provides some context to the event, like the
user who tried to open the file, it was
root in our case, the name of the file, etc.
Now, let us test it with Kubernetes pods:
First, in order to enable communication between our security tool Falco and Kubernetes Pods to fetch information from the containers. We need to install falco as a Daemonset on our Kubernetes cluster. This enables, falco to query the CRI — contained I'm my case for polling the events.
santosh@blogs:main$ kubectl get pods -n falco NAME READY STATUS RESTARTS AGE falco-gxxb6 2/2 Running 7 (34m ago) 3d15h falco-rpz45 2/2 Running 7 (34m ago) 3d15h
Once, the Falco pods are up and running on both nodes (I've installed it on my two-node Kind cluster. Hence, two pods). We can move ahead and see Falco watching the processes triggered by Containers as well.
To see this in action, I've deployed a pod named
privileged1, which is just a busybox container running with some serious security flaws in the configurations:
apiVersion: v1 kind: Pod metadata: creationTimestamp: null labels: run: privileged1 name: privileged1 spec: containers: - args: - sleep - 1d image: nginx name: privilaged securityContext: privileged: true runAsUser: 1000 allowPrivilegeEscalation: true <snip>
In order to view the logs, we need to exec into the Kind node, where Falco is installed, and view the logs through
journalctlthe command line tool that lets you interact with the journal logs.
Now, let's deploy this pod and see if Falco catches the security misconfiguration in the workload.
As expected, Falco detected that a privileged pod was created and a volumeMount was executed inside the container. The severity of the output is set to Warning in this case. Suppose, we now try to spawn a shell inside the container. As spawning a shell inside a container is considered a security risk, Falco would again sense this and alert us about this.
Modifying a rule
Another point to notice from the above image is that the output in the logs is more concise, giving only the relevant information about the user and container. This is achieved by altering the default rules to provide the output. As we discussed earlier in the Rules section, the rules are evaluated based on their listing in the main Falco config file. The default rules
faclo_rules.yaml file is one which comes pre-installed with all the rules formulated by the wonderful Falco community and might change during upgrades. Keeping this in mind, all the modification to the rules is made in a local rules file listed below the
falco_rules.yaml file, namely
falco_rules.local.yaml. Hence, while evaluating the rules, Falco looks first goes through the main rules file and then to the local file to evaluate the rules.
In order to make any changes to the existing rules, we need to add our custom rules in the
santosh@blogs:main$ cat /etc/falco/falco_rules.local.yaml # Custom rules! - rule: Terminal shell in container desc: Detects a shell being spawned in a Container condition: container.id != host and proc.name in (linux_shells) output: > A shell was spawned in a container with an attached terminal (user=%user.name user_name=%user.loginname shell=%proc.name parent=%proc.pname cmdline=%proc.cmdline container_name=%container.name image=%container.image) priority: WARNING - list: linux_shells items: [sh, bash, zsh]
There are various events that falco tracks for evaluating the process and generating readable output. We can learn more about all the event types and supported fields in the rules Condition field from Falco's official docs.
falco_rules.local.yamlfile is altered, we need to restart the Falco service either by
systemctl restart falco-modern-bpf.serviceor by hot reloading, this method does not restart the systemd service and restart the falco instance by identifying the pid of falco and sending a
sighupsignal by using this command:
kill 1 $(cat pidof falco).
In our case, we were monitoring the logs from the
journalctl utility as text files. But, Falco provides various ways to export the logs to different alert channels. We can export logs in
json, to a specific file, a Program output for a Slack Incoming Webhook, even an HTTP/HTTPS endpoint to some URL, or via a gRPC API client to an external program.
In this post, we've just scratched the surface of the runtime security paradigm by working with Falco. Falco also supports Kubernetes Audit logs by ingesting the Kubernetes event as event source, among others. Falco's support for monitoring the Kubernetes Audit logs in real-time provides an additional layer of security for Kubernetes environments and helps organizations detect and respond to security threats quickly and effectively.
In the next post, we will be integrating Falco with Kubernetes, enabling robust runtime security for our Kubernetes cluster.
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