Activity Audit

Prerequisites

• To track kubectl exec and other Kubernetes commands, Install Kubernetes audit logging.

• If you are running on a GKE cluster, review GKE Limitations.

Access Activity Audit

To access Activity Audit:

1. Log in to Sysdig Secure.

2. Select Threats > Forensics | Activity Audit.

Understand Activity Audit

Use Activity Audit to view different data sources in-depth for monitoring, troubleshooting, diagnostics, or to meet regulatory controls.

Investigate Events

A system investigation might be triggered by an event generated by Sysdig, or by an alert from another tool or person.

• Find contextualized, relevant data - Activity Audit enables you to easily access to the underlying data to help trace the event, evaluate its impact, and resolve the issue.

  From Policy Events in Sysdig Secure, go directly to the relevant Activity Audit to investigate details.

• Trace commands and connections back to users Activity Audit can correlate interactive requests from a Kubernetes user with the commands and network connections performed inside the container, enabling an operator to trace this activity back to a user identity.

Use Activity Audit for Regulatory Audits

Activity Audit can also provide data about the infrastructure to help prove to auditors that proper data visibility and security measures are in place.

Activity Audit is a critical requirement for many compliance standards:

• SOC2

• PCI

• HIPAA

• NIST 800-53

Navigate the Audit Interface

Activity Audit displays a continuously updated list of activities. Use the UI features to find and filter the information you need.

Select Threats > Forensics|Activity Audit to view the Audit Interface.

Filter Activities

Filtering is the heart of Activity Audit’s power. You can use filters to search, sort, parse, and surface meaningful data and connections.

Ways to filter Activity Data:

• Scope: Reduce the scope of your investigation by focusing on a more specific area of your infrastructure. By default, your scope will be set to Everywhere, unless a team scope is defined for your currently selected team.

• Data Source: Choose a data source from the right side of the graph. Currently available data sources are: network activity, commands, kubectl exec, or file. You can also select more than one source.

• Attribute (=/!=): Choose = or -!= next to an attribute, either from the list or from the detail view, to include/exclude that attribute from the filter

• Attribute (manual): If you know the attribute, you can type it into the filter box manually, with the following syntax:

  Include an attribute

  attribute_name="attribute_value" e.g. comm="grep"

  Exclude an attribute

  attribute_name!="attribute_value" e.g. comm!="grep"

• Trace Trace entries to see all relevant activity in a session from a specific user. See the Trace Button paragraph for details.

• Frequency graph: Select a section of the graph to zoom in on a time frame and see detailed activity. For details, see Frequency Graph paragraph.

• Combine: You can combine these methods as needed.

  For example, the following filter surfaces activity on a particular pod, while excluding activity from one IP address that is known to be normal.

  resource="pods" name="woocommerce-6877958" sourceaddresses!="172.20.41.2

Frequency Graph

The graph shows the activity frequency for each data source, letting you easily zero-in on anomalies.

The image above shows a spike in network activity (purple line) between 12:00 - 3:00 pm.

Drag the mouse over the peak to auto-zoom on the time frame and see more detail.

Data Sources

Use the legend at the right side of the graph to filter information from one particular data set. The currently available data sources are:

• User commands (interactive commands tracked by Activity Audit when a user has logged in and is interacting with the shell via SSH or console login)

• Kube exec commands (extracted from the Kubernetes/OpenShift audit log)

• Network connections and file activities related to user and Kube/Docker exec commands

Time Navigation Buttons

Use the time window navigation bar to show only activities run within that window.

Activity Row and Details

Select an activity row to see its details on the right panel, including all the collected attributes. You can use attributes to quickly add filters including = or excluding != such a value.

See Review Activity Details for the attributes of each data source.

You can also perform quick filtering by selecting attribute and filter type directly from the activity row.

Trace Button for kube exec and Shell Activities

Beside each activity originating a trace there is a Trace button

• kube exec
• kube attach
• ssh
• dropbear
• shells (*sh)

The Trace button lets you correlate activities from the originator to each single performed operation. See Follow a kubectl exec Trace use case to see it in action.

This button does not appear if you are running on a GKE cluster.

kubectl run

The Kubernetes event in the activity audit list labeled kube run is received from the AC in the following cases:

• A kubectl run is performed
• A kubectl attach is performed

Review Activity Details

Command Details

Network Connection Details

Kubectl Exec Details

File Activity Details

Use Cases

Look for Suspicious Commands

During an investigation you usually need to find suspicious activities among the most normal and recurring ones.

In this example, a ps command is executed very frequently, being noisy and making investigations harder.

To focus on other, more suspicious commands, you can use filters to reduce noise and make the investigation easier.

You can use quick filters to exclude the ps command, so that other more interesting commands emerge instantly.

Filtering for Incident Response

A Policy Event reports a dangerous peak in network connections coming from a specific pod. This example describes one way to search for the root cause.

What user and what activity triggered this issue?

1. Use the Respond button next to the policy event to jump directly to the relevant data.

2. Here you can determine at a glance:

   • The pod/namespace on which the heightened activity is occurring.

   • The process related to the activity (in this case, ab, or the Apache Benchmark tool).

   • Related activities in the graph (cmd and kube exec lines).

   • Repetitive entries that can be screened out.

3. Refine the view through filtering:

   1. Switch from network data source to cmd and kube exe.

   2. Filter out noisy, repetitive entries (such as comm!="bash")

   3. Investigate details of a kube exec item for user information.

   

4. After filtering, you have a focused incident report detailing:

   • The Kubernetes user “johndoe”

   • The external IP he used to connect

   • The set of commands he used to install and launch the Apache Benchmark stress-testing tool.

Follow a kubectl exec Trace

In a production environment, kubectl exec commands are typically suspicious. Also, because such commands are interactive sessions, it can be difficult to pinpoint which individual has issued the commands and what other activities the individual performed. You can use Sysdig’s Trace functionality to correlate kubectl exec commands with a specific user and the network and command activities performed in that user’s session.

In this example, suspicious activity has been detected and you want to determine whether someone has downloaded and executed a Trojan horse.

1. Use the Groups to display your Kubernetes hierarchy by namespace and deployment. Focus on the pod displaying unexpected high levels of activity (based on the number in parentheses).

2. Check the corresponding activity graph and zero in on a time frame and see kube exec activity among the hundreds of commands and network events.

   

3. Select the kube exec item and click the Trace button on left.

   This session trace displays a formatted report of any container activity (network, commands) that the user performed inside the container.