What is our primary use case?
We have been researching this solution as something to provide for clients who are interested in implementing a high-security AWS environment.
How has it helped my organization?
This solution provides some security around holes that are uniquely present on AWS. We try to convey to clients and customers that when you move to AWS, the whole attack surface is different, and therefore you can't take your existing tools to AWS and then secure it in the same way as you can your traditional environment. You need to have tools that understand the nuance of AWS, and that's the reason we use Dome9. It has these unique skills and attributes in the AWS world.
Specifically, we are interested in securing IAM. It controls everything in AWS such as who can create computing instances and who can destroy them. Given that all of the power is with IAM, you have to make sure that you haven't over-privileged, or through the combination of people being users, groups, or roles, that they haven't collected too many privileges that you weren't aware of.
What is most valuable?
The feature that I found most valuable is the ability to scan IAM, the Identity and Access Management tool, for all of the privileged accounts.
What needs improvement?
Integration with other security tools would be of benefit.
I would like to see some AI on the back-end, just to assist with doing analysis and making recommendations.
For how long have I used the solution?
Trial / evaluation.
What do I think about the stability of the solution?
The stability is rock solid.
What do I think about the scalability of the solution?
I have no concerns with the scalability of this solution.
How are customer service and technical support?
Technical support for this solution is excellent.
Which solution did I use previously and why did I switch?
We did not use another solution prior to this one.
How was the initial setup?
This solution is easy to get going, although it requires a lot of training to get the best out of it.
It took us weeks to set it up, which was very quick. In terms of setting it up for a client, the strategy would depend on what holes they have in their security infrastructure, and how we can use this solution to close them.
What about the implementation team?
We implemented the solution in-house and would assume this role for our customers.
What was our ROI?
This is the sort of tool for which ROI is not really considered. People implementing this solution are concerned with addressing a significant risk, and within the AWS realm, this tool does de-risk substantially.
What's my experience with pricing, setup cost, and licensing?
It is a standard licensing fee, with no additional costs.
Which other solutions did I evaluate?
We evaluated another solution called Evident.io, but it had a lot of overlap with traditional tools, whereas Dome9 was unique in its approach.
What other advice do I have?
This is a product that I would recommend because it does unique things that I'm not aware any other product can solve those issues. It is incredibly powerful and gives our customers a lot of assurance that we're taking AWS security seriously.
My advice for those implementing this product is to use every piece of it. Explore every option and feature and leverage it to the max.
I would rate this solution a nine out of ten.
Disclosure: My company has a business relationship with this vendor other than being a customer. Reseller.
Auto-Scale Palo Alto Networks VM-Series Firewalls in a Public Cloud Environment
For environments that require an automatic deployment as scale out of the security services is required, you can
combine bootstrapping with additional automation that monitors the security services and, when performance limits
are reached, triggers (CloudWatch) the automatic deployment and bootstrap of a new firewall to the security layer.
Auto-scaling works differently in every environment because tools that are specific to each public cloud environment
monitor and trigger the firewall deployment. Auto-scaling in AWS uses AWS services such as Lambda, Amazon Cloud-
Watch, S3, and SNS, in addition to the APIs and bootstrapping on the firewalls. In Azure, you use AppInsights and
Virtual Machine Scale Sets to monitor the environment and trigger the automatic deployment of a new firewall. You
can use a number of metrics in order to trigger the auto-scale event. Examples include:
• Data Plane CPU Utilization %
• GP Gateway Utilization %
• Active Sessions
• Data Plane Packet Buffer Utilization %
• SSL Proxy Session Utilization %
• Session Utilization %
Just like in the previous example, you must create the bootstrap container before automatic scale-out. The automation
monitors the appropriate metric on the existing firewalls, and after the value is higher than allowed for the right amount
of time, the scale-out event triggers the same firewall deployment as in the previous example. After the firewall is deployed and has a configuration provided by Panorama, the auto-scale automation adds the new firewall to the backend pool of the load balancer, ensuring that traffic load is appropriately distributed to the new firewall.
Operational Response to a Changing Environment
In virtual private data center and public cloud environments where new compute instances are created as needed for
scale, the administrative overhead in managing security policy can be cumbersome. Using dynamic address groups in
security policy allows for agility and prevents disruption in services or gaps in protection.
The VM-Monitoring Agent on the firewall can pull IP address and tag information from the cloud environment. Predefined dynamic address groups use the tag information to automatically associate IP addresses to pre-defined rules in the security policy. When there are multiple firewalls in the environment, they all can monitor the same source for IP and tag information. This provides the firewalls a dynamic but consistent view of the resources within the environment.
Dynamic address groups allow the firewall security policy to respond to a changing environment, but the applications
running in the environment must be well known for the appropriate dynamic address groups and security policy rules
to be created. Configuration automation can be used to provide a security policy that automatically is configured when
new applications are deployed to the environment.
Security Response Based on Log Information
Although log information alone can be extremely valuable to a security administrator, manually sifting through the logs
and responding to security events takes too long and requires too many administrative resources. Automated security
actions in the firewall can respond when a previously identified scenario presents itself in the logs. For example, when
Panorama sees a correlation event, it can use the source IP address from the log and use auto-tagging to attach a predefined tag, such as “Compromised.”
You can configure a dynamic address group on the firewall that is associated to the IP addresses with the “Compromised” tag. You can then create a security policy that blocks the traffic or enforces multi-factor authentication (MFA) for these endpoints that uses the dynamic address group as the source. If the user on the endpoint is malicious, MFA blocks their attempt to move laterally within the network, protecting sensitive data.
If the user continues to attempt to move laterally, Panorama can automatically use additional tags to block the IP and
HTTP log forwarding to log an incident. Panorama can use the ServiceNow ticketing system HTTP API to create a ticket so that the operations team is aware of this action on the endpoint. They can then investigate the incident, remediate the endpoint if needed, and remove the associated tags the apply the enhanced security policy.
Security Response to Improper Cloud Environment Configuration
RedLock cloud security provides organizations configuration security alerting for AWS, Azure, and GCP environments
and provides integrations that allow remediation to be automated. Using auto-remediation, organizations can make
sure alerts are automatically remediated before they, or malicious actors, even know there’s an issue. For example,
reconfiguring a security group rule that allows ingress traffic from the public Internet and opening a ticket with Service-
Now for tracking minutes after it’s been created.
RedLock uses the following automation process to remediate issues:
1. Using the cloud environment’s API, continuously perform checks against the configured signatures and policies.
2. If the resulting analysis determines a signature did not pass, send the failed alert to an integration such as
ServiceNow or AWS Simple Notification Service (SNS).
3. The AWS SNS service triggers the workflow automation and launches the AWS Lambda auto-remediation
function.
4. Using the AWS API, auto-remediate and fix the offending issue.
5. Send the resulting logs to AWS CloudWatch.