If you are following my blog, you’ve probably noticed that I’ve been focusing on security-specific AWS services in my previous several posts. It’s time to bring them all together into one consolidated view. I’m talking, of course, about the AWS Security Hub.
You can group, filter and prioritise findings from these services in many different ways. And, of course, you can visualise and make dashboards out of them.
Apart from consolidating findings from other services, it also assesses your overall AWS configuration against PCI DSS and/or the CIS Amazon Web Services Foundations Benchmark, which covers identity and access management, logging, monitoring and networking, giving you the overall score (example below) and actionable steps to improve your security posture.
Similar to the many other AWS services, Security Hub is regional, so it will need to be configured in every active region your organisation operates. I also recommend setting up your security operations account as a Security Hub master account and then inviting all other accounts in your organisation as members for centralised management (as described in this guidance or using a script).
If you are not a big fan of the Security Hub’s interface or don’t want to constantly switch between regions, the service sends all findings to CloudWatch Events by default, so you can forward them on to other AWS resources or external systems (e.g. chat or ticketing systems) for further analysis and remediation. Better still, you can configure automated response using Lambda, similar to what we did with Inspector findings discussed previously.
I wrote about automating application security testing in my previous blog. If you host your application or API on AWS and would like an additional layer of protection agains web attacks, you should consider using AWS Web Application Firewall (WAF).
It is relatively easy to set up and Amazon kindly provide some preconfigured rules and tutorials. AWS WAF is deployed in front of CloudFront (your CDN) and/or Application Load Balancer and inspects traffic before it reaches your assets. You can create multiple conditions and rules to watch for.
If you’ve been configuring firewalls in datacentres before the cloud services became ubiquitous, you will feel at home setting up IP match conditions to blacklist or whitelist IP addresses. However, AWS WAF also provides more sophisticated rules for detecting and blocking known bad IP addresses, SQL Injections and Cross Site Scripting (XSS) attacks.
Additionally, you can chose to test your rules first, counting the times it gets triggered rather than setting it to block requests straight away. AWS also throw in a standard level of DDoS protection (AWS Shield) with WAF at no extra cost, so there is really no excuse not to use it.
If you rely on EC2 instances in at least some parts of your cloud infrastructure, it is important to reduce the attack surface by hardening them. You might want to check out my previous blogs on GuardDuty, Config, IAM and CloudTrail for other tips on securing your AWS infrastructure. But today we are going to be focusing on yet another Amazon service – Inspector.
To start with, we need to make sure the Inspector Agent is installed on our EC2 instances. There are a couple of ways of doing this and I suggest simply using the Inspector service Advance Setup option. In addition, you can specify the instances you want to include in your scan as well as its duration and frequency. You can also select the rules packages to scan against.
After the agent is installed, the scan will commence in line with the configuration you specified in the previous step. You will then be able to download the report detailing the findings.
The above setup gives you everything you need to get started but there is certainly room for improvement.
It is not always convenient to go to the Inspector dashboard itself to check for discovered vulnerabilities. Instead, I recommend creating an SNS Topic which will be notified if Inspector finds new weaknesses. You can go a step further and, in the true DevSecOps way, set up a Lambda function that will automatically remediate Inspector findings on your behalf and subscribe it to this topic. AWS kindly open sourced a Lambda job (Python script) that automatically patches EC2 instances when an Inspector assessment generates a CVE finding.
You can see how Lambda is doing its magic installing updates in the CloudWatch Logs:
Or you can connect to your EC2 instance directly and check yum logs:
You will see a number of packages updated automatically when the Lambda function is triggered based on the Inspector CVE findings. The actual list will of course depend on how many updates you are missing and will correspond to the CloudWatch logs.
You can run scans periodically and still choose to receive the notifications but the fact that security vulnerabilities are being discovered and remediated automatically, even as you sleep, should give you at least some peace of mind.
This AWS service certainly has its imperfections (e.g. it doesn’t support all AWS resources) but it is easy to set up and can be quite useful too. When you first enable it, Config will analyse the resources in your account and make the summary available to you in a dashboard (example below). It’s a regional service, so you might want to enable it in all active regions.
Config, however, doesn’t stop there. You can now use this snapshot as a reference point and track all changes to your resources on a timeline. It can be useful when you need to analyse historical records, demonstrate compliance or gain visibility in your change management practices. It can also notify you of any configuration changes if you set up SNS notifications.
Config rules allow you to continuously track compliance with various baselines. AWS provide quite a few out of the box and you can create your own to tailor to the specific environment you operate in. You have to pay separately for rules, so I encourage you to check out pricing first.
As with some other AWS services, you can aggregate the data in a single account. I recommend using the account used for security operations as a master. You will then need to establish a two-way handshake, inviting member accounts and authorising the master account to be able to consolidate the results.
There are several ways to implement threat detection in AWS but by far the easiest (and perhaps cheapest) set up is to use Amazon’s native GuardDuty. It detects root user logins, policy changes, compromised keys, instances, users and more. As an added benefit, Amazon keep adding new rules as they continue evolving the service.
To detect threats in your AWS environment, GuardDuty ingests CloudTrail, VPC FlowLogs and VPC DNS logs. You don’t need to configure these separately for GuardDuty to be able to access them, simplifying the set up. The price of the service depends on the number of events analysed but it comes with a free 30-day trial which allows you to understand the scope, utility and potential costs.
It’s a regional service, so it should be enabled in all regions, even the ones you currently don’t have any resources. You might start using new regions in the future and, perhaps more importantly, the attackers might do it on your behalf. It doesn’t cost extra in the region with no activity, so there is really no excuse to switch it on everywhere.
To streamline the management, I recommend following the AWS guidance on channelling the findings to a single account, where they can be analysed by the security operations team.
It requires establishing master-member relationship between accounts, where the master account will be the one monitored by the security operations team. You will then need to enable GuardDuty in every member account and accept the invite from the master.
You don’t have to rely on the AWS console to access GuardDuty findings, as they can be streamed using CloudWatch Events and Kinesis to centralise the analysis. You can also write custom rules specific to your environment and mute existing ones customising the implementation. These, however, require a bit more practice, so I will cover them in future blogs.
Committing passwords, SSH keys and API keys to your code repositories is quite common. This doesn’t make it less dangerous. Yes, if you are ‘moving fast and breaking things’, it is sometimes easier to take shortcuts to simplify development and testing. But these broken things will eventually have to be fixed, as security of your product and perhaps even company, is at risk. Fixing things later in the development cycle is likely be more complicated and costly.
I’m not trying to scaremonger, there are already plenty of news articles about data breaches wiping out value for companies. My point is merely about the fact that it is much easier to address things early in the development, rather than waiting for a pentest or, worse still, a malicious attacker to discover these vulnerabilities.
Disciplined engineering and teaching your staff secure software development are certainly great ways to tackle this. There has to, however, be a fallback mechanism to detect (and prevent) mistakes. Thankfully, there are a number of open-source tools that can help you with that:
You will have to assess your own environment to pick the right tool that suits your organisation best.
If you read my previous blogs on integrating application testing and detecting vulnerable dependencies, you know I’m a big fan of embedding such tests in your Continuous Integration and Continuous Deployment (CI/CD) pipeline. This provides instant feedback to your development team and minimises the window between discovering and fixing a vulnerability. If done right, the weakness (a secret in the code repository in this case) will not even reach the production environment, as it will be caught before the code is committed. An example is on the screenshot at the top of the page.
For this reason (and a few others), the tool that I particularly like is detect-secrets, developed in Python and kindly open-sourced by Yelp. They describe the reasons for building it and explain the architecture in their blog. It’s lightweight, language agnostic and integrates well in the development workflow. It relies on pre-commit hooks and will not scan the whole repository – only the chunk of code you are committing.
Yelp’s detect-secrets, however, has its limitations. It needs to be installed locally by engineers which might be tricky with different operating systems. If you do want to use it but don’t want to be restricted by local installation, it can also run out of a container, which can be quite handy.
I bet you already know that you should set up CloudTrail in your AWS accounts, if you haven’t already. This service captures all the API activity taking place in your AWS account and stores it in an S3 bucket for that account by default. This means you would have to configure the logging and storage permissions for every AWS account your company has. If you are tasked with securing your cloud infrastructure, you will first need to establish how many accounts your organisation owns and how CloudTrail is configured for them. Additionally, you would want to have access to S3 buckets storing these logs in every account to be able to analyse them.
If this doesn’t sound complicated already, think of a potential error in permissions where logs can be deleted by an account administrator. Or situations where new accounts are created without your awareness and therefore not part of the overall logging pipeline. Luckily, these scenarios can be avoided if you are using the Organization Trail.
Your accounts have to be part of the same AWS Organization, of course. You would also need to have a separate account for security operations. Hopefully, this has been done already. If not, feel free to refer to my previous blogs on inventorying your assets and IAM fundamentals for further guidance on setting it up.
Establishing an Organization Trail not only allows you to collect, store and analyse logs centrally, it also ensures all new accounts created will have CloudTrail enabled and configured by default (and it cannot be turned off by child accounts).
Switch on Insights while you’re at it. This will simply the analysis down the line, alerting unusual API activity. Logging data events (for both S3 and Lambda) and integrating with CloudWatch Logs is also a good idea.
Where can all these logs be stored? The best destination (before archiving) is the S3 bucket in your account used for security operations, so that’s where it should be created.
Enabling encryption and Object Lock is always a good idea. While encryption will help with confidentiality of your log data, Object Lock will ensure redundancy and prevent objects from accidental deletion. It requires versioning to be enabled and is best configured on bucket creation. Don’t forget to block public access!
You must then use your organisational root account to set up Organization Trail, selecting the bucket you created in your operational security account as a destination (rather than creating a new bucket in your master account).
If you had other trails in your accounts previously, feel free to turn them off to avoid unnecessary duplication and save money. It’s best to give it a day for these trails to run in parallel though to ensure nothing is lost in transition. Keep your old S3 buckets used for collection in your accounts previously; you will need these logs too. You can configure lifecycle policies and perhaps transfer them to Glacier to save on storage costs later.
And that’s how you set up CloudTrail for centralised collection, storage and analysis.
Let’s build on my previous blog on inventorying your AWS assets. I described how to use CloudMapper‘s collect command to gather metadata about your AWS accounts and report on resources used and potential security issues.
This open source tool can do more than that and it’s functionality is being continuously updated. Once the data on the accounts in scope is downloaded, various operations can be performed on it locally without the need to continuously query the accounts.
One of interesting use cases is to visualise your AWS environment in the browser. An example based on the test data of such a visualisation is at the top of this blog. You can apply various filters to reduce complexity which can be especially useful for larger environments.
Another piece of CloudMapper’s functionality is the ability to display trust relationships between accounts using the weboftrust command. Below is an example from Scott’s guidance on the use of this command. It demonstrates the connections between accounts, including external vendors.
I’m not going co cover all the commands here and suggest checking the official GitHub page for the latest list. I also recommend running CloudMapper regularly, especially in environments that constantly evolve.
An approach of that conducts regular audits. saving reports and integrating with Slack for security alerts is described here.
In the previous blog, I wrote about how you as a security specialist can succeed in the world of agile development, where the requirements are less clear, environment more fluid and change is celebrated not resisted.
Adjusting your mindset and embracing the fact that there will be plenty of unknowns is the first step in adopting agile security practices. You can still influence the direction of the product development to make it more resilient, safe and secure by working with the Product Owner and contributing your requirements to the product backlog.
Simply put, product backlog is a list of desired functionality, bug fixes and other requirements needed to deliver a viable product. There are plethora of tools out there to help manage dependencies and prioritisation to make the product owner’s job easier. The image at the top of this post is an example of one of such tools and you can see some example requirements there.
As a security specialist, you can communicate your needs in a form of user stories or help contribute to existing ones, detailing security considerations. For example, ”Customer personal data should be stored securely” or “Secure communication channels should be used when transmitting sensitive information”. Below are a couple more examples from different categories.
When writing security user stories, you should try and elaborate as much as possible on the problem you are trying to solve, what value it will provide if solved and the acceptance criteria. Each story will then have points assigned which signifies how much effort a particular functionality will require. The process of arriving to the final number is quite democratic and usually involves playing planning (sometimes also called Scrum) poker in which every developer will estimate how long each story is going to take with some discussion and eventual consensus. You can do it with an app as on the image below, or the old school way with a deck of cards.
You don’t have to use the above number pattern, and opt-in instead for the Fibonacci sequence or T-shirt sizes.
It’s important that the security team is involved in sprint planning to contribute to the estimates and help the product owner with prioritisation. Other Scrum meetings, like backlog refinement and daily stand-ups are also worthwhile to attend to be able clarify your requirements (including value, risk, due dates and dependencies) and help remove security related impediments.
A culture of collaboration between teams is essential for the DevSecOps approach to be effective. Treating security as not something to workaround but as a value adding product feature is the mindset product and engineering teams should adopt. However, it’s up to security specialists to recognise the wider context in which they operate and accept the fact that security is just one of the requirements the team needs to consider. If the business can’t generate revenue because crucial features that customers demand are missing, it’s little consolation that security vulnerabilities have been addressed. After all, it’s great to have a secure product, but less so when nobody uses it.