Introducing AI Assistant for F5 Distributed Cloud, F5 NGINX One and BIG-IP
This article is an introduction to AI Assistant and shows how it improves SecOps and NetOps speed across all F5 platforms (Distributed Cloud, NGINX One and BIG-IP) , by solving the complexities around configuration, analytics, log interpretation and scripting.
Adopting SRE practices with F5: Layered Security Policy for North-South Traffic
In an organization with enough maturity in cybersecurity and modern application architectures, there are two different cybersecurity teams that operate the more advanced security policies for the company. NetSecOps and DevSecOps are the two cybersecurity teams in an organization, and they typically have different security requirements. NetSecOps requires a ‘Standardized Application Security Policy'. They aim to block common attacks to the production network with a high level of confidence, resulting in a ‘low-false positive rate,’ at the network level. The OWASP Top 10 threats is a good example here. Moreover, the responsibility of NetSecOps is not limited to stopping basic attack types like the OWASP Top 10, but it also covers more advanced and complicated application-based attacks such as ‘Bot Attacks,’ ‘Fraud Attacks,’ and ‘DDoS Attacks.’ However, when it comes to the ‘Modern-App environment,’ it is not easy for the NetSecOps team to understand the details of the application traffic flow inside the Kubernetes or OpenShift cluster. For this reason, as far as modern applications are concerned, the security policies of NetSecOps often focus more on compliance and audit purposes. However, DevSecOps wants the application-specific security policies for different types of applications to be operating inside their Kubernetes or OpenShift clusters. This is possible since DevSecOps understands how their applications work and they want to apply more optimized security policies for their backend applications. This is why it is sometimes difficult to achieve both security team’s goals with a single security solution. This is why the enterprise needs to deploy two different WAFs to meet the different requirements from both NetSecOps and DevSecOps. This article will cover how two different security teams can achieve their goals with two separate WAF (Web Application Firewall) deployments in the network - F5 Advanced WAF for NetSecOps and NGINX App Protect for DevSecOps. Solution Overview The solution includes two F5 components – F5 Advanced WAF and NGINX App Protect. From a technological point of view, NGINX App Protectutilizes s a subset of F5 Advanced WAF functionality, meaning that their underlying technologies are the same. Each of those WAF components can run with different security policies in order to achieve different goals. In F5 Advanced WAF, NetSecOps can apply the WAF policy for the ‘coarse-grained model’ of security, while DevSecOps adopts the ‘fine-grained model’ with the NAP. In other words, this means that F5 Advanced WAF can be configured with a ‘Negative Policy,’ and NGINX App Protect can be configured with a ‘Positive Policy.’ In our use-case, we assumed that NetSecOps wants to block the OWASP Top 10 threats while DevSecOps has a different 'file accessing' policy for each backend application. The brief architecture is depicted below. Combining F5 Advanced WAF and NGINX App Protect enables layered application security policies to prevent the most complicated and advanced application-based attacks efficiently. This architecture utilizes the following workflow: 1. The F5 Advanced WAF blocks the most commonly used attack types including ‘Command Injection,’ ‘SQL Injection,’ ‘Cross-Site Scripting,’ and ‘Server Side Request Forgery’ attacks. 2. When the attacker tries to access the different files in each application, NGINX App Protect manually specifies the file types that are allowed (or disallowed) in traffic based on the security policies configured by the DevSecOps team. 3. All alert details from F5 Advanced WAF and NGINX App Protect are sent to the ‘Elasticsearch’ for central monitoring purposes. Each of the above workflows will be discussed in the following sections. · This blog doesn’t include all the required steps to reproduce the use-case in the environment. Please refer to this link for all the required configuration steps. NGINX App Protect provides ‘Application-Specific’ policies NGINX App Protect can provide security protection and controls at the microservice level inside the Kubernetes or OpenShift cluster. The NGINX App Protect can be deployed in the OpenShift cluster as a container image. The NGINX App Protect policy configuration uses the declarative format built on a pre-defined base template. The policy uses the JSON format to represent the policy details. This file can be edited to apply a unique security policy to the NGINX App Protect instance. Once the policy is created, the policy can be attached to the 'nginx.conf' file by referencing the policy file. In this example, we used the ‘nginx_sre.conf’ file as the main configuration file for NGINX and the ‘NginxSRELabPolicy.json’ file represents the NGINX App Protect policy. NginxSRELabPolicy.json: | { "policy": { "name": "SRE_DVWA01_POLICY", "template": { "name": "POLICY_TEMPLATE_NGINX_BASE" }, "applicationLanguage": "utf-8", "enforcementMode": "blocking", "response-pages": [ { "responseContent": "<html><head><title>SRE DevSecOps - DVWA01 - Blocking Page</title></head><body><font color=green size=10>NGINX App Protect Blocking Page - DVWA01 Server</font><br><br>Please consult with your administrator.<br><br>Your support ID is: <%TS.request.ID()%><br><br><a href='javascript:history.back();'>[Go Back]</a></body></html>", "responseHeader": "HTTP/1.1 302 OK\\r\\nCache-Control: no-cache\\r\\nPragma: no-cache\\r\\nConnection: close", "responseActionType": "custom", "responsePageType": "default" } ], "blocking-settings": { "violations": [ { "name": "VIOL_FILETYPE", "alarm": true, "block": true } ] }, "filetypes": [ { "name": "*", "type": "wildcard", "allowed": true, "checkPostDataLength": false, "postDataLength": 4096, "checkRequestLength": false, "requestLength": 8192, "checkUrlLength": true, "urlLength": 2048, "checkQueryStringLength": true, "queryStringLength": 2048, "responseCheck": false }, { "name": "pdf", "allowed": false } ] } } --- The above configuration file shows the NAP policy of application #01, where the DevSecOps team wants to disallow file access to the ‘PDF’ file format. For application #02, the NAP policy is configured to reject the access to the ‘JPG’ file. And the ‘remote logging’ configuration needs to be applied on the NGINX to export the NGINX App Protect's alert details. The below configuration shows how we exported the NGINX App Protect logging details to an external device, Elasticsearch. server { listen 8080; server_name dvwa02-http; proxy_http_version 1.1; real_ip_header X-Forwarded-For; set_real_ip_from 0.0.0.0/0; app_protect_enable on; app_protect_security_log_enable on; app_protect_policy_file "/etc/nginx/NginxSRELabPolicy.json"; app_protect_security_log "/etc/app_protect/conf/log_default.json" syslog:server=your_elk_ip_here; location / { client_max_body_size 0; default_type text/html; proxy_pass http://dvwa02; proxy_set_header Host $host; } Preventing OWASP Top 10 threats in F5 Advanced WAF F5 Advanced WAF is the next-generation WAF solution designed to prevent advanced application-based attacks. It supports 1000+ proven application-level signatures, custom signatures, Machine-Learning based DDoS prevention, Intelligence-based attack mitigation, and Behavioural-based WAF functions. But in this use-case, we focused on the prevention of the OWASP Top 10 attacks, which is only a small part of the F% Advanced WAF attack overall coverage. The important point here is how we can configure the F5 Advanced WAF to apply the WAF's efficient ‘Negative Security’ model. In order to configure the correct F5 Advanced WAF policy, one should follow the procedures below: 1. Go to 'Security' -> 'Application Security' -> 'Security Policies' -> 'Create' 2. Click the security policy that was just created (SRE_DEVSEC_01) · Click the 'View Learning and Blocking Settings' under the 'Enforcement Mode' menu 3. Expand 'Attack Signatures' and Click 'Change' menu 4. Apply the check box. · Click 'Close' -> click 'Save' -> click 'Apply Policy' · Apply the policy to the virtual server. (Please make sure that we're on OCP partition.) 5. 'Local Traffic' -> 'Virtual Servers' -> 'devsecops_http_vs' -> Security -> Policies Please note that the ‘virtual server’ configuration is required in the BIG-IP before proceeding to this step. Configuring custom blocking page for F5 Advanced WAF 1. Click the security policy that was created (SRE_DEVSEC_01) 2. Go to 'Response and Blocking page' -> 'Blocking page default' -> 'Custom response' -> 'Response Body' <html><head><title>SRE DevSecOps Blocking Page</title></head><body><font color=red size=12>F5 Advanced WAF Blocking Page</font><br><br>Please consult with your administrator.<br><br>Your support ID is: <%TS.request.ID()%><br><br><a href='javascript:history.back();'>[Go Back]</a></body></html> Simulating the Attack The following steps show how to simulate the application-based attacks and to see how F5 Advanced WAF and NGINX App Protect can protect the applications efficiently. Preventing OWASP Top 10 Attacks - NetSecOps First, log in to the application through the GUI and go to the ‘Command Injection’ menu. And type the command ‘8.8.8.8 | cat /etc/passwd’ and click the ‘Submit’ button. If F5 Advanced WAF works correctly, you should be able to see the below ‘blocking page’. · You can find the instructions from the Github link here how to simulate other attack types – SQL Injection, SSRF and XSS. Restrict file accessing based on the application types - DevSecOps 1. Access to application 01 on the browser with URL -> "http://your_app_domain.com/hackable/uploads/" 2. When the ‘PDF’ file is clicked on in this directory, the following blocking screen should be shown. Summary In modern application architectures, security concerns are becoming more serious. WAF is the major security solution available to enterprise applications. The security policy of the WAF has to protect backend applications correctly, but at the same time, it must also ensure legitimate user traffic access to the backend resources without creating issues. This sounds straightforward, but it is not easy to configure the right security policies to achieve both goals simultaneously. When it comes to modern application architectures, it is even more difficult to achieve this goal. Since traditional security teams lack understanding about the application flow inside a Kubernetes or OpenShift environment, it is challenging to apply the required security policies in the WAF to protect the microservices. Due to the nature of their microservices, different applications spin up and down frequently, and security requirements are also changed on a regular basis. The cybersecurity team needs to have a solution that can fit these unique requirements. For NetSecOps, they would require a solution that can have enterprise-level protection features and operational-efficiency for their SOC team. F5 Advanced WAF is designed to efficiently prevent known and unknown types of advanced application-based attacks, while NGINX App Protect easily provides ‘application-specific’ security policies for each application inside the microservice environment. The enterprises can acquire the proper protection for their modern app environment through the combination of F5 Advanced WAF and NGINX App Protect. Please visit the DevCentral GitHub repo and follow the guidelines to try this use-case in your environment.Protecting Critical Apps against EastWest Attack
In the previous article, we explained how NetSecOps and DevSecOps could manage their application security policies to prevent advanced attacks from external organization networks. But in advanced persistent hacking, hackers sometimes exploit application vulnerabilities and use advanced malware with phishing emails to the operators. This is an old technique but still valid and utilized by many APT (Advanced Persistent Threat) Hacking Groups. And if the advanced hackers obtain a DevOps operator's ID and password using the malware, they could access a Kubernetes or OpenShift cluster through the normal login process and easily bypass advanced WAF(Web Application Firewall) solutions deployed in front of the cluster. Once the attacker can get a user ID and password of the Kubernetes or OpenShift cluster, the attacker also can access each application that is running inside of the cluster. Since most people on the SecOps team normally install very basic security functions inside the Kubernetes or OpenShift cluster, the hacker who logged in to the cluster can attack other applications in the same cluster without any security barrier. F5 Container Ingress Service is not designed to stop these sort of attacks within the cluster. To overcome this challenge, we have another tool, NGINX App Protect. NGINX App Protect delivers Layer 7 visibility and granular control for the applications while enabling an advanced application security policies. With an NGINX App Protect deployment, DevSecOps can ensure only legitimate traffic is allowed while all other unwanted traffic is blocked. NGINX App Protect can monitor the traffic traversing namespace boundaries between pods and provide advanced application protection at layer 7 for East-West traffic. Solution Overview This article will cover how NGINX App Protect can protect the critical applications in an OpenShift environment against an attack originating within the same cluster. Detecting advanced application attacks inside the cluster is beneficial for the DevSecOps team but this can increase the complexity of security operations. To provide a certain level of protection for the critical application the NGINX App Protect instance should be installed as a ‘PoD Proxy’ or a ‘Service Proxy’ for the application. This means the customer may need multiple NGINX App Protect instances to have the required level of protection for their applications. On the face of it this might seem like a dramatic increase in the complexity of security related operations. Security automation is the recommended solution to overcome the increased complexity of this security operations challenge. In this use case, we use Red Hat Ansible as our security automation tool. With Red Hat Ansible, the user can automate their incident response process with their existing security solutions. This can dramatically reduce the security team’s response time from hours to minutes. We use Ansible and Elasticsearch to provide all the required ‘security automation’ processes in this demo. With all these combined technologies, the solution provides WAF protection for the critical applications deployed in the OpenShift cluster. Once it detects the application-based attack from the same cluster subnet, it immediately blocks the attack and deletes the compromised pod with a pre-defined security automation playbook. The workflow is organized as shown below: The malware of 'Phishing email' infects the developer's laptop. The attacker steals the ID/PW of the developer using the malware. In this demo, the stolen ID is 'dev_user.' The attacker logs in the 'Test App' on the 'dev-test01' namespace, owned by the 'dev_user'. The attacker starts the network-scanning process on the internal subnet of the OpenShift cluster. And the attacker finds the 'critical-app' application pod. The attacker starts the web-based attack against 'critical-app'. NGINX App Protect protects the 'critical-app'; thus, the attack traffic is blocked immediately. NGINX exports the alert details to the external Elasticsearch. If this specific alert meets a pre-defined condition, Elasticsearch will trigger the pre-defined Ansible playbook. Ansible playbook accesses OpenShift and deletes the compromised 'Test App’ pod automatically. * Since this demo focuses on an attack inside the OpenShift cluster, the demo does not include the 'Step#1' and 'Step#2' (Phishing email). Understanding of the ‘Security Automation’ process The ‘Security Automation’ is the key part of this demo because the organizations don’t want to respond to each WAF alert manually, one by one. Manual incident-response processes are a time-consuming job and inefficient, especially in a modern-app environment with hundreds of container-based applications. In this demo, Red Hat Ansible and Elasticsearch take the security automation. Below is the brief workflow of the security automation of this use case. In this use case, the F5 Advanced WAF has been deployed in front of the OpenShift cluster and has inserted the X-Forwarded-For header value at each session. Since F5 Advanced WAF inserts the X-Forwarded-For header into the packet that comes from the external, if the packet doesn’t include the X-Forwarded-For header, it is likely coming from the internal network. NGINX App Protect installed as a pod proxy’ with the critical application we want to protect. Because NGINX App Protect runs as a pod proxy, all the traffic must be sent through this to reach the ‘critical-application.’ If the NGINX App Protect detects any malicious activities, it sends the alert details to the external Elasticsearch System. When any new alerts come from the NGINX App Protect, Elasticsearch analyzes the details of the alerts. If the alert meets the below conditions, Elasticsearch triggers the notification to the Logstash. If the source IP address of the alert is a part of the OpenShift cluster subnet… If the WAF alert severity is Critical… Once the Logstash system receives the notification from the Elasticsearch, it creates the ip.txt file, which includes the source IP address of the attack and executes the pre-defined Ansible playbook. Ansible playbook reads the ip.txt file and extracts the IP address from the file. And Ansible accesses the OpenShift and finds the compromised pod using that Source IP Address from the ip.txt file. Then Ansible deletes the compromised pod and ip.txt files automatically. Creates Ansible Playbook Red Hat Ansible is the automation tool that enables network and security automation for users with enterprise-ready functions. F5 and Red Hat have a strategic partnership and deliver the joint use cases for our customer base. With Ansible integration with F5 solutions, organizations can have the single pane of glass management for network and security automation. In this use-case, we implement an automated security response process with the Ansible playbook when the F5 NGINX App Protect detects malicious activities in the OpenShift cluster. Below is the Ansible playbook to execute the incident response process for the attacker's compromised pod. ansible_ocp.yaml --- - hosts: localhost gather_facts: false tasks: - name: Login to OCP cluster k8s_auth: host: https://yourocpdomain:6443 username: kubeadmin password: your_ocp_password validate_certs: no register: k8s_auth_result - name: Extract IP Address command: cat /yourpath/ip.txt register: badpod_ip - name: Extract App Label from OpenShift shell: | sudo oc get pods -A -o json --field-selector status.podIP={{ badpod_ip.stdout }} | grep "\"app\":" | awk '{print $2}' | sed 's/,//' register: app_label - name: Delete Malicious Deployments shell: | sudo oc delete all --selector app={{ app_label.stdout }} -A register: delete_pod - name: Delete IP and Info File command: rm -rf /yourpath/ip.txt - name: OCP Service Deletion Completed debug: msg: "{{ delete_pod.stdout }}" Configuring Elasticsearch Watcher and Logstash To trigger the Ansible playbook for the Security Automation, SOC analysts need to validate the alert from the NGINX App Protect first. And based on the difference of the alert details, the SOC analyst might want to execute a different playbook. For example, if the alert is related to a Credential Stuffing Attack, the SOC analysts may want to block the user's application access. But if the alert is related to the known IP Blacklist, the analyst might want to block that IP address in the firewall. To support these requirements, the security team needs to have a tool that can monitor the security alerts and trigger the required actions based on them. Elasticsearch Watcher is the feature of the commercial version of Elasticsearch that users can use to create actions based on conditions, which are periodically evaluated using queries on the data. Configuring the Watcher of Kibana * You need an Elastic Platinum license or Eval license to use this feature on the Kibana. * Go to Kibana UI. * Management -> Watcher -> Create -> Create advanced watcher * Copy and paste below JSON code watcher_ocp.json { "trigger": { "schedule": { "interval": "1m" } }, "input": { "search": { "request": { "search_type": "query_then_fetch", "indices": [ "nginx-*" ], "rest_total_hits_as_int": true, "body": { "query": { "bool": { "must": [ { "match": { "outcome_reason": "SECURITY_WAF_VIOLATION" } }, { "match": { "x_forwarded_for_header_value": "N/A" } }, { "range": { "@timestamp": { "gte": "now-1h", "lte": "now" } } } ] } } } } } }, "condition": { "compare": { "ctx.payload.hits.total": { "gt": 0 } } }, "actions": { "logstash_logging": { "webhook": { "scheme": "http", "host": "localhost", "port": 1234, "method": "post", "path": "/{{watch_id}}", "params": {}, "headers": {}, "body": "{{ctx.payload.hits.hits.0._source.ip_client}}" } }, "logstash_exec": { "webhook": { "scheme": "http", "host": "localhost", "port": 9001, "method": "post", "path": "/{{watch_id}}", "params": {}, "headers": {}, "body": "{{ctx.payload.hits.hits[0].total}}" } } } } 2. Configuring 'logstash.conf' file. Below is the final version of the 'logstash.conf' file. Please note that you have to start the logstash with 'sudo' privilege logstash.conf input { syslog { port => 5003 type => nginx } http { port => 1234 type => watcher1 } http { port => 9001 type => ansible1 } } filter { if [type] == "nginx" { grok { match => { "message" => [ ",attack_type=\"%{DATA:attack_type}\"", ",blocking_exception_reason=\"%{DATA:blocking_exception_reason}\"", ",date_time=\"%{DATA:date_time}\"", ",dest_port=\"%{DATA:dest_port}\"", ",ip_client=\"%{DATA:ip_client}\"", ",is_truncated=\"%{DATA:is_truncated}\"", ",method=\"%{DATA:method}\"", ",policy_name=\"%{DATA:policy_name}\"", ",protocol=\"%{DATA:protocol}\"", ",request_status=\"%{DATA:request_status}\"", ",response_code=\"%{DATA:response_code}\"", ",severity=\"%{DATA:severity}\"", ",sig_cves=\"%{DATA:sig_cves}\"", ",sig_ids=\"%{DATA:sig_ids}\"", ",sig_names=\"%{DATA:sig_names}\"", ",sig_set_names=\"%{DATA:sig_set_names}\"", ",src_port=\"%{DATA:src_port}\"", ",sub_violations=\"%{DATA:sub_violations}\"", ",support_id=\"%{DATA:support_id}\"", ",unit_hostname=\"%{DATA:unit_hostname}\"", ",uri=\"%{DATA:uri}\"", ",violation_rating=\"%{DATA:violation_rating}\"", ",vs_name=\"%{DATA:vs_name}\"", ",x_forwarded_for_header_value=\"%{DATA:x_forwarded_for_header_value}\"", ",outcome=\"%{DATA:outcome}\"", ",outcome_reason=\"%{DATA:outcome_reason}\"", ",violations=\"%{DATA:violations}\"", ",violation_details=\"%{DATA:violation_details}\"", ",request=\"%{DATA:request}\"" ] } break_on_match => false } mutate { split => { "attack_type" => "," } split => { "sig_ids" => "," } split => { "sig_names" => "," } split => { "sig_cves" => "," } split => { "sig_set_names" => "," } split => { "threat_campaign_names" => "," } split => { "violations" => "," } split => { "sub_violations" => "," } remove_field => [ "date_time", "message" ] } if [x_forwarded_for_header_value] != "N/A" { mutate { add_field => { "source_host" => "%{x_forwarded_for_header_value}"}} } else { mutate { add_field => { "source_host" => "%{ip_client}"}} } geoip { source => "source_host" database => "/etc/logstash/GeoLite2-City.mmdb" } } } output { if [type] == 'nginx' { elasticsearch { hosts => ["127.0.0.1:9200"] index => "nginx-%{+YYYY.MM.dd}" } } if [type] == 'watcher1' { file { path => "/yourpath/ip.txt" codec => line { format => "%{message}"} } } if [type] == 'ansible1' { exec { command => "ansible-playbook /yourpath/ansible_ocp.yaml" } } } Simulate the demo You should start the Kibana watcher and logstash services first before proceeding with this step. Kubeadmin Console Please make sure you're logged in to the OCP cluster using a cluster-admin account. And confirm the 'critical-app' is running correctly. j.lee$ oc whoami kube:admin j.lee$ j.lee$ oc get projects NAME DISPLAY NAME STATUS critical-app Active default Active dev-test02 Active kube-node-lease Active kube-public Active kube-system Active openshift Active openshift-apiserver Active openshift-apiserver-operator Active openshift-authentication Active openshift-authentication-operator Active openshift-cloud-credential-operator Active j.lee$ oc get pods -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES critical-app-v1-5c6546765f-wjhl9 2/2 Running 1 85m 10.129.2.71 ip-10-0-180-68.ap-southeast-1.compute.internal <none> <none> j.lee$ dev_user Console Please make sure you're logged in to the OCP cluster using 'dev_user' account on the compromised pod and confirm the 'dev-test-app' is running correctly. PS C:\Users\ljwca\Documents\ocp> oc whoami dev_user PS C:\Users\ljwca\Documents\ocp> PS C:\Users\ljwca\Documents\ocp> oc get projects NAME DISPLAY NAME STATUS dev-test02 Active PS C:\Users\ljwca\Documents\ocp> PS C:\Users\ljwca\Documents\ocp> oc get pods -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES dev-test-v1-674f467644-t94dc 1/1 Running 0 6s 10.128.2.38 ip-10-0-155-159.ap-southeast-1.compute.internal <none> <none> 2. Login to 'dev-test' container using remote shell command of the OCP PS C:\Users\ljwca\Documents\ocp> oc rsh dev-test-v1-674f467644-t94dc $ $ uname -a Linux dev-test-v1-674f467644-t94dc 4.18.0-193.14.3.el8_2.x86_64 #1 SMP Mon Jul 20 15:02:29 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux 3. Network scanning This step takes 1~2 hours to complete all scanning. $ nmap -sP 10.128.0.0/14 Starting Nmap 7.80 ( https://nmap.org ) at 2020-09-29 17:20 UTC Nmap scan report for ip-10-128-0-1.ap-southeast-1.compute.internal (10.128.0.1) Host is up (0.0025s latency). Nmap scan report for ip-10-128-0-2.ap-southeast-1.compute.internal (10.128.0.2) Host is up (0.0024s latency). Nmap scan report for 10-128-0-3.metrics.openshift-authentication-operator.svc.cluster.local (10.128.0.3) Host is up (0.0023s latency). Nmap scan report for 10-128-0-4.metrics.openshift-kube-scheduler-operator.svc.cluster.local (10.128.0.4) Host is up (0.0027s latency). . . . After completion of the scanning, you will be able to find the 'critical-app' on the list. 4. Application Scanning for the target You can find the open service ports on the target using nmap. $ nmap 10.129.2.71 Starting Nmap 7.80 ( https://nmap.org ) at 2020-09-29 17:23 UTC Nmap scan report for 10-129-2-71.critical-app.critical-app.svc.cluster.local (10.129.2.71) Host is up (0.0012s latency). Not shown: 998 closed ports PORT STATE SERVICE 80/tcp open http 8888/tcp open sun-answerbook Nmap done: 1 IP address (1 host up) scanned in 0.12 seconds $ But you will see the 403 error when you try to access the server using port 80. This happens because the default Apache access control only allows the traffic from the NGINX App Protect. $ curl http://10.129.2.71/ <!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML 2.0//EN"> <html><head> <title>403 Forbidden</title> </head><body> <h1>Forbidden</h1> <p>You don't have permission to access this resource.</p> <hr> <address>Apache/2.4.46 (Debian) Server at 10.129.2.71 Port 80</address> </body></html> $ Now, you can see the response through port 8888. $ curl http://10.129.2.71:8888/ <html> <head> <title> Network Operation Utility - NSLOOKUP </title> </head> <body> <font color=blue size=12>NSLOOKUP TOOL</font><br><br> <h2>Please type the domain name into the below box.</h2> <h1> <form action="/index.php" method="POST"> <p> <label for="target">DNS lookup:</label> <input type="text" id="target" name="target" value="www.f5.com"> <button type="submit" name="form" value="submit">Lookup</button> </p> </form> </h1> <font color=red>This site is vulnerable to Web Exploit. Please use this site as a test purpose only.</font> </body> </html> $ 5. Performing the Command Injection attack. $ curl -d "target=www.f5.com|cat /etc/passwd&form=submit" -X POST http://10.129.2.71:8888/index.php <html><head><title>SRE DevSecOps - East-West Attack Blocking</title></head><body><font color=green size=10>NGINX App Protect Blocking Page</font><br><br>Please consult with your administrator.<br><br>Your support ID is: 878077205548544462<br><br><a href='javascript:history.back();'>[Go Back]</a></body></html>$ $ 6. Verify the logs in Kibana dashboard You should be able to see the NGINX App Protect alerts on your Elasticsearch. You should be able to see the NGINX App Protect alerts on your ELK. 7. Verify the Ansible terminates the compromised pod Ansible deletes the compromised pod. Summary Today’s cyber based threats are getting more and more sophisticated. Attackers keep attempting to find out the weakest link in the company’s infrastructure and finally move from there to the data in the company using that link. In most cases, the weakest link of the organization is the human and the company stores its critical data in the application. This is why the attackers use the phishing email to compromise the user’s laptop and leverage it to access the application. While F5 is working very closely with our key alliance partners such as Cisco and FireEye to stop the advanced malware at the first stage, our NGINX App Protect can work as another layer of defence for the application to protect the organization's data. F5, Red Hat, and Elastic have developed this new protection mechanism, which is an automated process. This use case allows the DevSecOps team to easily deploy the advanced security layer in their OpenShift cluster. If you want to learn more about this use case, please visit the F5 Business Development official Github link here.F5 Essential App Protect and AWS CloudFront - Better Together.
What is the function of any application? In the simplest of terms an application must provide a value to the user. While the definition of "value" may differ, it is universally true that the user experience is critical to the perception of value. The user experience, loyalty, and your brand are predicated on the fact that the application be useable. So, what does it mean to be useable? It means that the application must be available, it must be secure, and it must be fast. Recently we announced that F5 Essential App Protect (EAP) would be integrating with AWS CloudFront to provide both security and Content Delivery Network (CDN) services for customers. This is an evolutionary step for F5 in our transition to a software and services company. Now, from the same portal where customers deploy applications and employ F5 Essential App Protect for security, in just a couple of clicks or a single API call, they can also access a global CDN leveraging AWS CloudFront. Let's review why EAP is cool, why AWS CloudFront is interesting, and take a look at the steps to enable the feature. F5 EAP is a high value, low time investment, WAF solution allowing customers to leverage F5's leading WAF Engine as a service using an intuitive interface. Customers can leverage EAP to meet security needs while incurring minimal operational overhead and pay based on traffic patterns. F5 EAP offers customers access to the sensitive data masking, security signatures, new threat campaigns, and IP reputation services that we have developed over nearly 20 years and continue to evolve. By subscribing to EAP customers can increase the efficacy of their SOC without increasing headcount or adding to operational burdens while gaining access to security protections that go far beyond what other services can provide. Below, the overview dashboard of an application protected by F5 Essential App Protect AWS CloudFront is a global CDN that allows users to deploy cacheable content across the globe in over 200 edge points of presence (PoP). AWS CloudFront is based on AWS best in class technology, expansive know how on building cloud services and leverages the AWS global network between the PoP closest to your customers and your Essential App Protect deployment (built on AWS). AWS CloudFront becomes the entry point for all traffic into the application, caching the content that is cacheable and passing the dynamic or non-cacheable portions to the origin. So why would you want to enable a CDN for your application? The simple answer is user experience. The better performing an application is the more likely it is that it will be used. By leveraging a CDN your content can be placed closer to your users and cached. This decreases page load time, something that always makes users happy. A more complete answer includes attributes such as reducing your WAF costs by not having to process cacheable content for each request and removing that traffic load from your origin application systems. The use of a CDN provides benefits for both the content provider and the content consumer. In the graph below you can clearly see the impact of enabling caching had on the origin servers in one of our test applications. So what does the high level architecture look like? Below you can see that DNS traffic is processed by AWS Route 53, directing the traffic to one of the AWS CloudFront edge locations. Traffic that has passed basic validations such as the host header matches the certificate name is either served from the edge cache or directed to F5 EAP for further processing. Traffic that passes WAF validation by F5 EAP is then passed to your origin application no matter if it is in AWS or located in your data center. For applications that reside in AWS all of this network traffic uses the AWS global network between the AWS CloudFront edge, F5 EAP and your app. For applications that reside in a non-AWS based location you can still use F5 EAP with the AWS CloudFront Integration (no AWS account required on your part) noting the slight difference in the data path as shown in the architecture below. Enabling your CDN Assuming that you already have an application deployed and protected by F5 EAP let's take a look at updating and adding AWS CloudFront functionality. From our F5 EAP portal we can see that our application has an FQDN of na2-auction.cloudservicesdemo.net. This application is already deployed and the DNS flow is as follows, a user's computer performs a DNS look up for na2-auction.cloudservicesdemo.net and it is a CNAME for your enabled F5 EAP dataplane locations. First let's enable caching on our Application which will enable AWS CloudFront. Next we need to configure the EdgeTiers (which geographies) that we would like to leverage to place the content closer to the users. Now we should filter any cookies or headers that we would like forwarded and enable compression. Since our application was already deployed on F5 EAP we will use the same CNAME and direct our traffic into AWS CloudFront. After a brief period our F5 Essential App Protect deployment will now have an integrated AWS CloudFront distribution and you will start to see caching metrics as traffic traverses the data path as described in the architecture. What if you need to invalidate some content? Well that is just as easy as enabling the feature! First you need to create the invalidation (purge), and when you click save the process will run deleting the items that match from the cache based on your EdgeTier selections. What about support for AWS CloudFront? That is on F5. We will deploy the AWS CloudFront distribution for you and it is part of our service that you subscribed to. If you experience issues you contact us at F5. We will diagnose and, if necessary, work with AWS to resolve the issue. No more having to coordinate multiple vendors for your application and no more getting stuck in the middle of two vendors not agreeing to a resolution. That's it! You have enabled an integrated security and CDN based on F5 EAP and AWS CloudFront in a few clicks from a single user interface! F5 Essential App Protect with our integrated AWS CloudFront offering can handle the the full lifecycle of your application security and edge performance optimization needs. Take it for a test drive from the F5 CloudServices portal.Adopting Site Reliability Engineering with F5
Foreword The role of the Site Reliability Engineering (SRE) is common in cloud first enterprises and becoming more widespread in traditional IT teams. Here, we would like to kick off this article series to look at the concepts that give SRE shape, outline the primary tools and best practices that make it possible, and explore some common use cases around Continuous Deployment (CD) strategy, visibility and security. While SRE and DevOps share many areas of commonality, there are significant differences between them. DevOps is a loose set of practices, guidelines, and culture designed to break down silos in Development, IT operations, Network, and Security team. DevOps does not tell you how to run operations at a detailed level. On the other hand, SRE, a term pioneered by Google, brings an opinionated framework to the problem of how to run operations effectively. If you think of DevOps as a philosophy, you can argue that SRE implements some of the philosophy that DevOps describes. In a way, SRE implements DevOps practices. After all, SRE only works at all if we have tools and technologies to enable it. Balancing Release Velocity and Reliability SRE aims to find the balance between feature velocity and reliability, which are often treated as opposing goals. Despite the risk of making changes to software, these changes are necessary for the business to succeed. Instead of advocating against change, SRE uses the concept of Service Level Objectives (SLOs) and error budgets to measure the impact of releases on reliability. The goal is to ship software as quickly as possible while meeting the reliability targets the users expect. While there are a wide range of ways an SRE-focused IT team might optimize the balance between agility and stability, two deployment models stand out for their widespread applicability and general ease of execution: Blue-green deployment For SRE, availability is currently the most common SLO. If getting new software to your users and uninterrupted access is truly required, there needs to be engineering work to implement load balancing or fractional release measures like blue-green or canary deployments to minimize any downtime. Recovery is a factor too. The idea behind blue-green deployment is that your blue environment is your existing production environment carrying live traffic. In parallel, you provision a green environment, which is identical to the blue environment other than the new version of your code. As you prepare a new version of your software, deployment and the final stage of testing takes place in the environment that is not live: in this example, Green (or new OpenShift Cluster). When it's time to deploy, you route production traffic from the blue environment to the green environment. This technique can eliminate downtime due to app deployment. In addition, blue-green deployment reduces risk: if something unexpected happens with your new version on Green, you can immediately roll back by reverting traffic to the original blue environment. When you are looking for manipulating the traffic with more flexibility, reliability, across different clusters, different clouds, or geo locations, this is when F5 DNS Load Balancer Cloud Service comes into the picture. F5 Cloud service GSLB is a SaaS offering. It can provide automatic failover, load balancing across multiple locations, increased reliability by avoiding a single point of failure, and increased performance by directing traffic to the optimal site. This allows SRE to move fast while still maintaining enterprise grade. Targeted Canary deployment Another approach to promote availability for SRE SLO is canary deployment. In some cases, swapping out the entire deployment via a blue-green environment may not be desired. In a canary deployment, you upgrade an application on a subset of the infrastructure and allow a limited set of users to access the new version. This approach allows you to test the new software under a Production-like load, evaluate how well it meets users’ needs, and assess whether new features are profitable. One approach often used by Azure DevOps is ring deployment model. Users fall into three general buckets based on their respective different risk profiles: Ring 1 - Canaries who voluntarily test bleeding edge features as soon as they are available. Ring 2 - Early adopters who voluntarily preview releases, considered more refined than the canary bits. Ring 3 - Users who consume the products, after passing through canaries and early adopters. Developer can promote and target new versions of the same application (version 1.2, 1.1, 1.0) to targeted users (ring 1, 2 and 3) respectively, without involving and waiting the infrastructure operations team (NoOps). To identify the user for the right version, you may choose to simply use IP address, authenticate directly by backend, or add an authentication layer in front of the backend. F5 technologies can help enable this targeted canary use case: BIG-IP APM in N-S will authenticate and identify users as ring 1, 2 or 3, and inject user identification into HTTP header This identification is passed on to NGINX plus micro-gateway to direct users to the correct microservice versions. Combining BIG-IP and NGINX, this architecture uniquely gives SRE the flexibility to adapt with the ability to define the baseline service control and security (for NetOps or SecOps), while extending controls for more granular and enhanced security to the developer team (for DevOps). The need for observability For SRE, at the heart of implementing SLOs practically is monitoring. You can't understand what you can't see. A classic and common approach to monitoring is to watch for a specific value or condition, and then to trigger an alert when that value is exceeded or that condition occurs. One of the valid monitoring outputs is logging, which is recorded for diagnosis or forensic purposes. The ELK stack, a collection of three open source projects, namely Elasticsearch, Logstash and Kibana, provides IT project stakeholders the capabilities of multi-system and multi-application log aggregation and analysis. ELK can be utilized for the analysis and visualization of application metrics through a centralized dashboard. With general visibility in place, tracking can be enabled in order to add a level of specificity to what is being observed. Taking advantage of iRule on BIG-IP, NetOps can generate UUID and insert it into the HTTP header of every HTTP request packet arriving at BIG-IP. All traffic access logs containing UUIDs, from BIG-IP and NGINX, are sent to the ELK server, for validation of information such as user location, response time by user location, response time etc. Through the dashboard, end-users can easily correlate North-South traffic (processed by BIG-IP) with East-West traffic (processed by NIGNX+ inside cluster), for an end-to-end performance visibility. In turn, tracking performance metrics opens up the possibility of defining service level objectives (SLO). With observability, security is possible Security incident will always occur, and hence it's essential to integrate security into observability. What’s most important is giving reliability engineers the tools so that they can identify the security problem, work around it, and fix it as quickly as possible. Using the right set of tools, you can build custom autogenerated dashboards and tooling to expose the generated information to engineers in a way that makes it much easier to sort through everything and determine the root cause of a security problem. These include things like Kibana dashboard, which allows engineers to investigate incident, apply filters, quickly pinpoint suspicious data traffic and source. In concert with F5 Advanced WAF and NGINX App Protect, SRE can protect applications against software vulnerabilities and common attacks from both inside and outside microservice clusters. Upon BIG-IP Advance WAF or NGINX App Protect detect suspicious traffic, it sends alert with details to ELK stack, which will index, and process the data, and then execute the pre-defined ‘Ansible Playbook’, to enforce security policy into Kubernetes or NGINX App Protect for immediate remediation. SRE does not only identify but rectify the anomalies by enacting security policy enforcement along the data path. Detect once and protect everywhere. What’s next? This serves as an introduction to or the first article of this SRE article series. In the coming articles, we will deep dive into each of the use cases, to showcase the technical details about how we are leveraging F5 technologies and capabilities to help SRE bring together DevOps, NetOps, and SecOps to develop the safeguards and implement the best practices. To learn more about developing a business case for SRE in your organization, please reach out to an F5 Business Development. For technical details and additional information, see this DevCentral GitHub repo.
How to Setup Shape Log Analysis in Fastly
Update 8/3: Shape Log Analysis is now a supported log streaming endpoint on Fastly. Read the full details here. Shape Log Analysis is a non-invasive technique used to analyze HTTP and application logs for a clearer view into attackers that are bypassing current security measures. Oftentimes bad actors, botnets, and drive by attacks will consume system resources and commit fraud against APIs in the form of Credential Stuffing, Scraping, Account Takeover and more. Without the proper defenses in place, these attacks are a pain to stop for most security teams who are forced to play “whack-a-mole" with solutions that are not built to permanently defeat fraudulent and automated attacks. Shape Security has a unique corpus of data from attacks that have been identified and blocked over the years for the world's largest banks, airlines, hotels and many other types of infrastructure exposed to the public internet. This anonymized attack data is used to examine application logs revealing automation and fraud that is bypassing perimeter security mechanisms and making its way to your origin servers. Through analyzing data points in Layer 7 traffic, Shape will create a threat assessment on old and new campaigns that are currently attacking specific parts of your applications. Log Analysis Example - Figure 1 The visualization shown in Figure 1 represents all malicious and fraudulent traffic against a specific application. The green pattern hidden in the back is the normal diurnal flow of legitimate user traffic. All other colors are automated attacks driving abuse of APIs and important parts of the application. This type of reporting can be used to not only understand types of attacks and abuse but can also be used to create a plan for integrating a mitigation solution. Types of attacks that will be uncovered: Credential Stuffing Account Takeover Scraping API Abuse System Resource Consumption Getting Started Shape Log Analysis is a free service that is now integrated with Fastly CDN. To avoid complications of compressing, securing and manually sending log data to Shape, we now have the ability to securely send logs to Shape through Fastly's real time log streaming configuration. This is a simple “flip of the switch” configuration, doesn't involve sending any PII data to Shape, and gives organizations the visibility required to take action and prevent these types of attacks. To configure Fastly CDN for Shape Log Analysis, follow these steps: 1) Request a secure S3 Bucket from Shape (send an email to fastly@f5.com with title "Fastly Log Streaming Setup") Once Shape has setup your designated S3 bucket, you will receive an email with a private access key that will be required to complete the configuration in the next step. Keep in mind that Shape uses network and security access controls between Fastly and AWS to ensure data is kept private and confidential. If there are any concerns around how log data is kept safe and secure, please ask in the setup request email. 2) Follow Fastly’s well written instructions on creating a new log endpoint and copy in the Shape specific configuration from below. Log format for Shape Log Analysis (Non-PII data) { "timestamp": "%{begin:%Y-%m-%dT%H:%M:%S%z}t", "ts": "%{time.start.sec}V", "id.orig_h": "%h", "status_code": "%>s", "method": "%m", "host": "%{Host}i", "uri": "%U%q", "accept_encoding": "%{Accept-Encoding}i", "request_body_len": "%{req.body_bytes_read}V", "response_body_len": "%{resp.body_bytes_written}V", "location": "%{Location}i", "x_forwarded_for": "%{X-Forwarded-For}i", "user_agent": "%{User-Agent}i", "referer": "%{Referer}i", "accept": "%{Accept}i", "accept_language": "%{Accept-Language}i", "content_type": "%{Content-Type}o", "geo_city": "%{client.geo.city}V", "geo_country_code": "%{client.geo.country_code}V", "is_tls": %{if(req.is_ssl, "true", "false")}V, "tls_version": "%{tls.client.protocol}V", "tls_cipher_request": "%{tls.client.cipher}V", "tls_cipher_req_hash": "%{tls.client.ciphers_sha}V", "tls_extension_identifiers_hash": "%{tls.client.tlsexts_sha}V" } S3 Bucket Details When you receive the S3 Bucket confirmation from the fastly@f5.com email address, it will contain the following 5 items that you'll need to insert into your Fastly configuration. 1.) Bucket Name 2.) Access Key 3.) Secret Key 4.) Path 5.) Domain Click on "Advanced options" and add the following: After completing the setup, your configuration summary for Shape Log Analysis will look like the following: Once the Fastly logging configuration is complete, logs will be sent to Shape's secure S3 bucket for analysis. Typically we collect around two weeks worth of log data to provide a comprehensive analysis of attack traffic. Additionally, an F5 or Shape representative will be available to provide support during the logging setup and a Threat Assessment Report will be provided as part of the service. Additional Information on Shape and Fastly
