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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Minimizing Microservice Vulnerabilities | 20% | - Container isolation and security contexts - Pod security standards |
| Topic 2: System Hardening | 15% | - Kernel and node security configuration - Host security controls |
| Topic 3: Cluster Setup | 15% | - Secure installation configuration - Hardening cluster components |
| Topic 4: Cluster Hardening | 15% | - API server security - Authentication and authorization |
| Topic 5: Monitoring, Logging and Runtime Security | 15% | - Runtime threat detection - Audit logging and monitoring |
| Topic 6: Supply Chain Security | 20% | - Secure CI/CD practices - Image scanning and verification |
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28. Frage
You are monitoring a Kubernetes cluster running a critical web application. You observe a sudden spike in resource consumption, specifically CPU utilization, on a specific pod within the cluster. The pod's CPL] usage is significantly higher than its usual baseline. How can you use behavioral analytics to investigate the cause of this spike and potentially identify malicious activity? Provide a step-by-step approach with concrete examples and tools.
Antwort:
Begründung:
Solution (Step by Step):
1. Identify the affected pod: Use 'kubectl get podS or the Kubernetes dashboard to identity the pod exhibiting abnormal CPU usage.
2. Gatner relevant data:
- Kubernetes Events: Examine the pod's events using 'kubectl describe pod ' or 'kubectl get events -field-selector Look for unusual events like container restarts, tailed probes, or resource limits being exceeded.
- Pod logs: Use 'kubectl logs to retrieve the pod's logs. Analyze the logs for suspicious activity like error messages, unusual requests, or unexpected commands.
- Resource metrics: Employ monitoring tools like Prometheus, Grafana, or Datadog to visualize the pod's CPU usage over time. Identity potential anomalies like sudden spikes or sustained high usage that deviate from the baseline.
- Network traffic: Analyze network traffic associated with the pod using tools like tcpdump, Wireshark, or network monitoring dashboards. Look for unusual connections, excessive bandwidth consumption, or suspicious communication patterns.
3. Analyze the collected data:
- Baseline Comparison: Compare the current resource usage with the pod's historical performance baseline. Identify significant deviations that could indicate a problem.
- Behavioral Analysis: Look for unusual or unexpected actions within the pod's logs and events. For example, observe if the pod is executing scripts, running unexpected commands, or making excessive network calls.
4. Identify potential causes:
- Code Bug: Check for recent code changes or deployments that could have introduced resource-intensive code.
- Resource Contention: Analyze other pods sharing the same node to identify any potential resource contention.
- Malicious Activity: Consider the possibility of malicious activity if the observed behavior is consistent with known attack patterns. Examples include:
- Cryptojacking: The pod could be running cryptocurrency mining software.
- Denial-of-Service (DoS): The pod might be launching attacks against other resources.
- Data Exfiltration: The pod could be trying to steal sensitive data from the cluster
5. Investigate further:
- Security Scanning: Conduct a security scan of the affected container image to identify potential vulnerabilities. I-Jse tools like Clair, Trivy, or Anchore
- Network Forensics: If suspicious network traffic is identified, conduct network forensics analysis to track the source and destination of the traffic.
- Threat Intelligence: Use threat intelligence feeds to correlate observed behavior with known attack patterns and identify potential threat actors.
6. Remediation:
- Isolate the pod: If malicious activity is suspected, isolate the pod to prevent further harm.
- Patch vulnerabilities: Apply security patches to the affected container image and the Kubernetes nodes-
- Implement security controls: Strengthen security controls to prevent future attacks. Examples include:
- Network Segmentation: Isolate sensitive applications and data.
- Access Control: Use role-based access control (RBAC) to restrict access to sensitive resources.
- Intrusion Detection: Implement intrusion detection systems (IDS) to monitor for suspicious activity
Example (using Prometheus & Grafana):
- Configure Prometheus to scrape metrics from the Kubernetes cluster
- Use Grafana to create a dashboard with panels displaying pod resource usage over time.
- Analyze the dashboard to identify sudden spikes or sustained high CPU utilization.
- Drill down into the affected pod and examine logs and events to identify potential causes.
29. Frage
You have a microservice application running in a Kubernetes cluster with a sidecar container responsible for logging. The sidecar container has access to the main application containers sensitive data, including credentials. You need to implement a security policy to prevent the sidecar container from accessing the main application container's data.
Antwort:
Begründung:
Solution (Step by Step) :
1. Create a Securitycontext for the main application container:
2. Apply the updated Deployment: bash kubectl apply -f my-app-deployment.yaml - The readOnlyRootFilesystem: true' setting in the main application container's security context prevents the sidecar container from writing to the main container's filesystem. - This ensures that the sidecar container cannot modify or access the main application's sensitive data. Important Notes: - This policy restricts the sidecar container from accessing the main containers data through the filesystem. - If the sidecar needs access to specific data, you can mount a shared volume that is read-only for the sidecar container and read-write for the main container. - It's crucial to review the security context of both main and sidecar containers to ensure that all necessary access restrictions are implemented.
30. Frage
You must complete this task on the following cluster/nodes:
Cluster: trace
Master node: master
Worker node: worker1
You can switch the cluster/configuration context using the following command:
[desk@cli] $ kubectl config use-context trace
Given: You may use Sysdig or Falco documentation.
Task:
Use detection tools to detect anomalies like processes spawning and executing something weird frequently in the single container belonging to Pod tomcat.
Two tools are available to use:
1. falco
2. sysdig
Tools are pre-installed on the worker1 node only.
Analyse the container's behaviour for at least 40 seconds, using filters that detect newly spawning and executing processes.
Store an incident file at /home/cert_masters/report, in the following format:
[timestamp],[uid],[processName]
Note: Make sure to store incident file on the cluster's worker node, don't move it to master node.
Antwort:
Begründung:
$vim /etc/falco/falco_rules.local.yaml
- rule: Container Drift Detected (open+create)
desc: New executable created in a container due to open+create
condition: >
evt.type in (open,openat,creat) and
evt.is_open_exec=true and
container and
not runc_writing_exec_fifo and
not runc_writing_var_lib_docker and
not user_known_container_drift_activities and
evt.rawres>=0
output: >
%evt.time,%user.uid,%proc.name # Add this/Refer falco documentation
priority: ERROR
$kill -1 <PID of falco>
Explanation
[desk@cli] $ ssh node01
[node01@cli] $ vim /etc/falco/falco_rules.yaml
search for Container Drift Detected & paste in falco_rules.local.yaml
[node01@cli] $ vim /etc/falco/falco_rules.local.yaml
- rule: Container Drift Detected (open+create)
desc: New executable created in a container due to open+create
condition: >
evt.type in (open,openat,creat) and
evt.is_open_exec=true and
container and
not runc_writing_exec_fifo and
not runc_writing_var_lib_docker and
not user_known_container_drift_activities and
evt.rawres>=0
output: >
%evt.time,%user.uid,%proc.name # Add this/Refer falco documentation
priority: ERROR
[node01@cli] $ vim /etc/falco/falco.yaml
31. Frage
Create a PSP that will prevent the creation of privileged pods in the namespace.
Create a new PodSecurityPolicy named prevent-privileged-policy which prevents the creation of privileged pods.
Create a new ServiceAccount named psp-sa in the namespace default.
Create a new ClusterRole named prevent-role, which uses the newly created Pod Security Policy prevent-privileged-policy.
Create a new ClusterRoleBinding named prevent-role-binding, which binds the created ClusterRole prevent-role to the created SA psp-sa.
Also, Check the Configuration is working or not by trying to Create a Privileged pod, it should get failed.
Antwort:
Begründung:
Create a PSP that will prevent the creation of privileged pods in the namespace.
$ cat clusterrole-use-privileged.yaml
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: use-privileged-psp
rules:
- apiGroups: ['policy']
resources: ['podsecuritypolicies']
verbs: ['use']
resourceNames:
- default-psp
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: privileged-role-bind
namespace: psp-test
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: use-privileged-psp
subjects:
- kind: ServiceAccount
name: privileged-sa
$ kubectl -n psp-test apply -f clusterrole-use-privileged.yaml
After a few moments, the privileged Pod should be created.
Create a new PodSecurityPolicy named prevent-privileged-policy which prevents the creation of privileged pods.
apiVersion: policy/v1beta1
kind: PodSecurityPolicy
metadata:
name: example
spec:
privileged: false # Don't allow privileged pods!
# The rest fills in some required fields.
seLinux:
rule: RunAsAny
supplementalGroups:
rule: RunAsAny
runAsUser:
rule: RunAsAny
fsGroup:
rule: RunAsAny
volumes:
- '*'
And create it with kubectl:
kubectl-admin create -f example-psp.yaml
Now, as the unprivileged user, try to create a simple pod:
kubectl-user create -f- <<EOF
apiVersion: v1
kind: Pod
metadata:
name: pause
spec:
containers:
- name: pause
image: k8s.gcr.io/pause
EOF
The output is similar to this:
Error from server (Forbidden): error when creating "STDIN": pods "pause" is forbidden: unable to validate against any pod security policy: [] Create a new ServiceAccount named psp-sa in the namespace default.
$ cat clusterrole-use-privileged.yaml
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: use-privileged-psp
rules:
- apiGroups: ['policy']
resources: ['podsecuritypolicies']
verbs: ['use']
resourceNames:
- default-psp
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: privileged-role-bind
namespace: psp-test
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: use-privileged-psp
subjects:
- kind: ServiceAccount
name: privileged-sa
$ kubectl -n psp-test apply -f clusterrole-use-privileged.yaml
After a few moments, the privileged Pod should be created.
Create a new ClusterRole named prevent-role, which uses the newly created Pod Security Policy prevent-privileged-policy.
apiVersion: policy/v1beta1
kind: PodSecurityPolicy
metadata:
name: example
spec:
privileged: false # Don't allow privileged pods!
# The rest fills in some required fields.
seLinux:
rule: RunAsAny
supplementalGroups:
rule: RunAsAny
runAsUser:
rule: RunAsAny
fsGroup:
rule: RunAsAny
volumes:
- '*'
And create it with kubectl:
kubectl-admin create -f example-psp.yaml
Now, as the unprivileged user, try to create a simple pod:
kubectl-user create -f- <<EOF
apiVersion: v1
kind: Pod
metadata:
name: pause
spec:
containers:
- name: pause
image: k8s.gcr.io/pause
EOF
The output is similar to this:
Error from server (Forbidden): error when creating "STDIN": pods "pause" is forbidden: unable to validate against any pod security policy: [] Create a new ClusterRoleBinding named prevent-role-binding, which binds the created ClusterRole prevent-role to the created SA psp-sa.
apiVersion: rbac.authorization.k8s.io/v1
# This role binding allows "jane" to read pods in the "default" namespace.
# You need to already have a Role named "pod-reader" in that namespace.
kind: RoleBinding
metadata:
name: read-pods
namespace: default
subjects:
# You can specify more than one "subject"
- kind: User
name: jane # "name" is case sensitive
apiGroup: rbac.authorization.k8s.io
roleRef:
# "roleRef" specifies the binding to a Role / ClusterRole
kind: Role #this must be Role or ClusterRole
name: pod-reader # this must match the name of the Role or ClusterRole you wish to bind to apiGroup: rbac.authorization.k8s.io apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata:
namespace: default
name: pod-reader
rules:
- apiGroups: [""] # "" indicates the core API group
resources: ["pods"]
verbs: ["get", "watch", "list"]
32. Frage
You are configuring a Kubernetes cluster with a deployment named 'secure-app' that uses a secret named 'my-secret to access sensitive information You need to implement an Admission Controller webhook to enforce a policy that prevents the deployment from starting if the 'my-secret secret is not present in the cluster.
Antwort:
Begründung:
Solution (Step by Step) :
1. Create a Deployment with a Secret Dependency:
- Create a Deployment YAML file named 'secure-app-deployment.yaml that depends on the 'my-secret secret.
2. Create the Admission Controller Webhook Server: - You will need to create a server that will implement the Admission Controller webhook logic This can be a simple web server written in any language that can receive and process AdmissionReview requests. - Here's an example in Node.js using the 'express' framework:
3. Configure the Admission Controller Webhook in Kubernetes: - Create a ValidatingWebhookConfiguration YAML file named 'secure-app-webhook.yaml that specifies the webhook configuration:
- Create the Webhook Service: - Create a Service YAML file named 'secure-app-webhook-service.yamr to expose the webhook server:k
4. Apply the Webhook Configuration and Service: - Apply the YAML files using kubectl apply -f secure-app-webhook.yaml secure-app-webhook-service.yaml 5. Test the Admission Controller: - Try creating the 'secure-app' deployment without the 'my-secret' secret. The deployment creation should fail, and you should see the message from the webhook server - Create the 'my-secret' secret and then try creating the 'secure-app' deployment again. The deployment should now be created successfully.
33. Frage
......
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