MetaHub is an automated contextual security findings enrichment and impact evaluation tool for vulnerability management. You can use it with AWS Security Hub or any ASFF-compatible security scanner. Stop relying on useless severities and switch to impact scoring definitions based on YOUR context.

MetaHub is an open-source security tool for impact-contextual vulnerability management. It can automate the process of contextualizing security findings based on your environment and your needs: YOUR context, identifying ownership, and calculate an impact scoring based on it that you can use for defining prioritization and automation. You can use it with AWS Security Hub or any ASFF security scanners (like Prowler).

MetaHub describe your context by connecting to your affected resources in your affected accounts. It can describe information about your AWS account and organization, the affected resources tags, the affected CloudTrail events, your affected resource configurations, and all their associations: if you are contextualizing a security finding affecting an EC2 Instance, MetaHub will not only connect to that instance itself but also its IAM Roles; from there, it will connect to the IAM Policies associated with those roles. It will connect to the Security Groups and analyze all their rules, the VPC and the Subnets where the instance is running, the Volumes, the Auto Scaling Groups, and more.

After fetching all the information from your context, MetaHub will evaluate certain important conditions for all your resources: exposure, access, encryption, status, environment and application. Based on those calculations and in addition to the information from the security findings affecting the resource all together, MetaHub will generate a Scoring for each finding.

Check the following dashboard generated by MetaHub. You have the affected resources, grouping all the security findings affecting them together and the original severity of the finding. After that, you have the Impact Score and all the criteria MetaHub evaluated to generate that score. All this information is filterable, sortable, groupable, downloadable, and customizable.

You can rely on this Impact Score for prioritizing findings (where should you start?), directing attention to critical issues, and automating alerts and escalations.

MetaHub can also filter, deduplicate, group, report, suppress, or update your security findings in automated workflows. It is designed for use as a CLI tool or within automated workflows, such as AWS Security Hub custom actions or AWS Lambda functions.

The following is the JSON output for a an EC2 instance; see how MetaHub organizes all the information about its context together, under associations, config, tags, account cloudtrail, and impact

Context

In MetaHub, context refers to information about the affected resources like their configuration, associations, logs, tags, account, and more.

MetaHub doesn't stop at the affected resource but analyzes any associated or attached resources. For instance, if there is a security finding on an EC2 instance, MetaHub will not only analyze the instance but also the security groups attached to it, including their rules. MetaHub will examine the IAM roles that the affected resource is using and the policies attached to those roles for any issues. It will analyze the EBS attached to the instance and determine if they are encrypted. It will also analyze the Auto Scaling Groups that the instance is associated with and how. MetaHub will also analyze the VPC, Subnets, and other resources associated with the instance.

The Context module has the capability to retrieve information from the affected resources, affected accounts, and every associated resources. The context module has five main parts: config (which includes associations as well), tags, cloudtrail, and account. By default config and tags are enabled, but you can change this behavior using the option --context (for enabling all the context modules you can use --context config tags cloudtrail account). The output of each enabled key will be added under the affected resource.

Config

Under the config key, you can find anyting related to the configuration of the affected resource. For example, if the affected resource is an EC2 Instance, you will see keys like private_ip, public_ip, or instance_profile.

You can filter your findings based on Config outputs using the option: --mh-filters-config <key> {True/False}. See Config Filtering.

Associations

Under the associations key, you will find all the associated resources of the affected resource. For example, if the affected resource is an EC2 Instance, you will find resources like: Security Groups, IAM Roles, Volumes, VPC, Subnets, Auto Scaling Groups, etc. Each time MetaHub finds an association, it will connect to the associated resource again and fetch its own context.

Associations are key to understanding the context and impact of your security findings as their exposure.

You can filter your findings based on Associations outputs using the option: --mh-filters-config <key> {True/False}. See Config Filtering.

Tags

MetaHub relies on AWS Resource Groups Tagging API to query the tags associated with your resources.

Note that not all AWS resource type supports this API. You can check supported services.

Tags are a crucial part of understanding your context. Tagging strategies often include:

• Environment (like Production, Staging, Development, etc.)
• Data classification (like Confidential, Restricted, etc.)
• Owner (like a team, a squad, a business unit, etc.)
• Compliance (like PCI, SOX, etc.)

If you follow a proper tagging strategy, you can filter and generate interesting outputs. For example, you could list all findings related to a specific team and provide that data directly to that team.

You can filter your findings based on Tags outputs using the option: --mh-filters-tags TAG=VALUE. See Tags Filtering

CloudTrail

Under the key cloudtrail, you will find critical Cloudtrail events related to the affected resource, such as creating events.

The Cloudtrail events that we look for are defined by resource type, and you can add, remove or change them by editing the configuration file resources.py.

For example for an affected resource of type Security Group, MetaHub will look for the following events:

• CreateSecurityGroup: Security Group Creation event
• AuthorizeSecurityGroupIngress: Security Group Rule Authorization event.

Account

Under the key account, you will find information about the account where the affected resource is runnning, like if it's part of an AWS Organizations, information about their contacts, etc.

Ownership

MetaHub also focuses on ownership detection. It can determine the owner of the affected resource in various ways. This information can be used to automatically assign a security finding to the correct owner, escalate it, or make decisions based on this information.

An automated way to determine the owner of a resource is critical for security teams. It allows them to focus on the most critical issues and escalate them to the right people in automated workflows. But automating workflows this way, it is only viable if you have a reliable way to define the impact of a finding, which is why MetaHub also focuses on impact.

Impact

The impact module in MetaHub focuses on generating a score for each finding based on the context of the affected resource and all the security findings affecting them. For the context, we define a series of evaluated criteria; you can add, remove, or modify these criteria based on your needs. The Impact criteria are combined with a metric generated based on all the Security Findings affecting the affected resource and their severities.

The following are the impact criteria that MetaHub evaluates by default:

Exposure

Exposure evaluates the how the the affected resource is exposed to other networks. For example, if the affected resource is public, if it is part of a VPC, if it has a public IP or if it is protected by a firewall or a security group.

Access

Access evaluates the resource policy layer. MetaHub checks every available policy including: IAM Managed policies, IAM Inline policies, Resource Policies, Bucket ACLS, and any association to other resources like IAM Roles which its policies are also analyzed . An unrestricted policy is not only an itsue itself of that policy, it afected any other resource which is using it.

Encryption

Encryption evaluate the different encryption layers based on each resource type. For example, for some resources it evaluates if at_rest and in_transit encryption configuration are both enabled.

Status

Status evaluate the status of the affected resource in terms of attachment or functioning. For example, for an EC2 Instance we evaluate if the resource is running, stopped, or terminated, but for resources like EBS Volumes and Security Groups, we evaluate if those resources are attached to any other resource.

Environment

Environment evaluates the environment where the affected resource is running. By default, MetaHub defines 3 environments: production, staging, and development, but you can add, remove, or modify these environments based on your needs. MetaHub evaluates the environment based on the tags of the affected resource, the account id or the account alias. You can define your own environemnts definitions and strategy in the configuration file (See Customizing Configuration).

Application

Application evaluates the application that the affected resource is part of. MetaHub relies on the AWS myApplications feature, which relies on the Tag awsApplication, but you can extend this functionality based on your context for example by defining other tags you use for defining applications or services (like Service or any other), or by relying on account id or alias. You can define your application definitions and strategy in the configuration file (See Customizing Configuration).

Findings Soring

As part of the impact score calculation, we also evaluate the total ammount of security findings and their severities affecting the resource. We use the following formula to calculate this metric:

(SUM of all (Finding Severity / Highest Severity) with a maximum of 1)

For example, if the affected resource has two findings affecting it, one with HIGH and another with LOW severity, the Impact Findings Score will be:

SUM(HIGH (3) / CRITICAL (4) + LOW (0.5) / CRITICAL (4)) = 0.875

Architecture

MetaHub reads your security findings from AWS Security Hub or any ASFF-compatible security scanner. It then queries the affected resources directly in the affected account to provide additional context. Based on that context, it calculates it's impact. Finally, it generates different outputs based on your needs.

Use Cases

Some use cases for MetaHub include:

• MetaHub integration with Prowler as a local scanner for context enrichment
• Automating Security Hub findings suppression based on Tagging
• Integrate MetaHub directly as Security Hub custom action to use it directly from the AWS Console
• Created enriched HTML reports for your findings that you can filter, sort, group, and download
• Create Security Hub Insights based on MetaHub context

Features

MetaHub provides a range of ways to list and manage security findings for investigation, suppression, updating, and integration with other tools or alerting systems. To avoid Shadowing and Duplication, MetaHub organizes related findings together when they pertain to the same resource. For more information, refer to Findings Aggregation

MetaHub queries the affected resources directly in the affected account to provide additional context using the following options:

• Config: Fetches the most important configuration values from the affected resource.
• Associations: Fetches all the associations of the affected resource, such as IAM roles, security groups, and more.
• Tags: Queries tagging from affected resources
• CloudTrail: Queries CloudTrail in the affected account to identify who created the resource and when, as well as any other related critical events
• Account: Fetches extra information from the account where the affected resource is running, such as the account name, security contacts, and other information.

MetaHub supports filters on top of these context* outputs to automate the detection of other resources with the same issues. You can filter security findings affecting resources tagged in a certain way (e.g., Environment=production) and combine this with filters based on Config or Associations, like, for example, if the resource is public, if it is encrypted, only if they are part of a VPC, if they are using a specific IAM role, and more. For more information, refer to Config filters and Tags filters for more information.

But that's not all. If you are using MetaHub with Security Hub, you can even combine the previous filters with the Security Hub native filters (AWS Security Hub filtering). You can filter the same way you would with the AWS CLI utility using the option --sh-filters, but in addition, you can save and re-use your filters as YAML files using the option --sh-template.

If you prefer, With MetaHub, you can back enrich your findings directly in AWS Security Hub using the option --enrich-findings. This action will update your AWS Security Hub findings using the field UserDefinedFields. You can then create filters or Insights directly in AWS Security Hub and take advantage of the contextualization added by MetaHub.

When investigating findings, you may need to update security findings altogether. MetaHub also allows you to execute bulk updates to AWS Security Hub findings, such as changing Workflow Status using the option --update-findings. As an example, you identified that you have hundreds of security findings about public resources. Still, based on the MetaHub context, you know those resources are not effectively public as they are protected by routing and firewalls. You can update all the findings for the output of your MetaHub query with one command. When updating findings using MetaHub, you also update the field Note of your finding with a custom text for future reference.

MetaHub supports different Output Modes, some of them json based like json-inventory, json-statistics, json-short, json-full, but also powerfull html, xlsx and csv. These outputs are customizable; you can choose which columns to show. For example, you may need a report about your affected resources, adding the tag Owner, Service, and Environment and nothing else. Check the configuration file and define the columns you need.

MetaHub supports multi-account setups. You can run the tool from any environment by assuming roles in your AWS Security Hub master account and your child/service accounts where your resources live. This allows you to fetch aggregated data from multiple accounts using your AWS Security Hub multi-account implementation while also fetching and enriching those findings with data from the accounts where your affected resources live based on your needs. Refer to Configuring Security Hub for more information.

Customizing Configuration

MetaHub uses configuration files that let you customize some checks behaviors, default filters, and more. The configuration files are located in lib/config/.

Things you can customize:

• lib/config/configuration.py: This file contains the default configuration for MetaHub. You can change the default filters, the default output modes, the environment definitions, and more.

• lib/config/impact.py: This file contains the values and it's weights for the impact formula criteria. You can modify the values and the weights based on your needs.

• lib/config/reources.py: This file contains definitions for every resource type, like which CloudTrail events to look for.

Run with Python

MetaHub is a Python3 program. You need to have Python3 installed in your system and the required Python modules described in the file requirements.txt.

Requirements can be installed in your system manually (using pip3) or using a Python virtual environment (suggested method).

Run it using Python Virtual Environment

1. Clone the repository: git clone [email protected]:gabrielsoltz/metahub.git
2. Change to repostiory dir: cd metahub
3. Create a virtual environment for this project: python3 -m venv venv/metahub
4. Activate the virtual environment you just created: source venv/metahub/bin/activate
5. Install Metahub requirements: pip3 install -r requirements.txt
6. Run: ./metahub -h
7. Deactivate your virtual environment after you finish with: deactivate

Next time, you only need steps 4 and 6 to use the program.

Alternatively, you can run this tool using Docker.

Run with Docker

MetaHub is also available as a Docker image. You can run it directly from the public Docker image or build it locally.

The available tagging for MetaHub containers are the following:

• latest: in sync with master branch
• <x.y.z>: you can find the releases here
• stable: this tag always points to the latest release.

For running from the public registry, you can run the following command:

docker run -ti public.ecr.aws/n2p8q5p4/metahub:latest ./metahub -h

AWS credentials and Docker

If you are already logged into the AWS host machine, you can seamlessly use the same credentials within a Docker container. You can achieve this by either passing the necessary environment variables to the container or by mounting the credentials file.

For instance, you can run the following command:

docker run -e AWS_DEFAULT_REGION -e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY -e AWS_SESSION_TOKEN -ti public.ecr.aws/n2p8q5p4/metahub:latest ./metahub -h

On the other hand, if you are not logged in on the host machine, you will need to log in again from within the container itself.

Build and Run Docker locally

Or you can also build it locally:

git clone [email protected]:gabrielsoltz/metahub.gitcd metahubdocker build -t metahub .docker run -ti metahub ./metahub -h

Run with Lambda

MetaHub is Lambda/Serverless ready! You can run MetaHub directly on an AWS Lambda function without any additional infrastructure required.

Running MetaHub in a Lambda function allows you to automate its execution based on your defined triggers.

Terraform code is provided for deploying the Lambda function and all its dependencies.

Lambda use-cases

• Trigger the MetaHub Lambda function each time there is a new security finding to enrich that finding back in AWS Security Hub.
• Trigger the MetaHub Lambda function each time there is a new security finding for suppression based on Context.
• Trigger the MetaHub Lambda function to identify the affected owner of a security finding based on Context and assign it using your internal systems.
• Trigger the MetaHub Lambda function to create a ticket with enriched context.

Deploying Lambda

The terraform code for deploying the Lambda function is provided under the terraform/ folder.

Just run the following commands:

cd terraformterraform initterraform apply

The code will create a zip file for the lambda code and a zip file for the Python dependencies. It will also create a Lambda function and all the required resources.

Customize Lambda behaviour

You can customize MetaHub options for your lambda by editing the file lib/lambda.py. You can change the default options for MetaHub, such as the filters, the Meta* options, and more.

Lambda Permissions

Terraform will create the minimum required permissions for the Lambda function to run locally (in the same account). If you want your Lambda to assume a role in other accounts (for example, you will need this if you are executing the Lambda in the Security Hub master account that is aggregating findings from other accounts), you will need to specify the role to assume, adding the option --mh-assume-role in the Lambda function configuration (See previous step) and adding the corresponding policy to allow the Lambda to assume that role in the lambda role.

Run with Security Hub Custom Action

MetaHub can be run as a Security Hub Custom Action. This allows you to run MetaHub directly from the Security Hub console for a selected finding or for a selected set of findings.

The custom action will then trigger a Lambda function that will run MetaHub for the selected findings. By default, the Lambda function will run MetaHub with the option --enrich-findings, which means that it will update your finding back with MetaHub outputs. If you want to change this, see Customize Lambda behavior

You need first to create the Lambda function and then create the custom action in Security Hub.

For creating the lambda function, follow the instructions in the Run with Lambda section.

For creating the AWS Security Hub custom action:

1. In Security Hub, choose Settings and then choose Custom Actions.
2. Choose Create custom action.
3. Provide a Name, Description, and Custom action ID for the action.
4. Choose Create custom action. (Make a note of the Custom action ARN. You need to use the ARN when you create a rule to associate with this action in EventBridge.)
5. In EventBridge, choose Rules and then choose Create rule.
6. Enter a name and description for the rule.
7. For the Event bus, choose the event bus that you want to associate with this rule. If you want this rule to match events that come from your account, select default. When an AWS service in your account emits an event, it always goes to your account's default event bus.
8. For Rule type, choose a rule with an event pattern and then press Next.
9. For Event source, choose AWS events.
10. For the Creation method, choose Use pattern form.
11. For Event source, choose AWS services.
12. For AWS service, choose Security Hub.
13. For Event type, choose Security Hub Findings - Custom Action.
14. Choose Specific custom action ARNs and add a custom action ARN.
15. Choose Next.
16. Under Select targets, choose the Lambda function
17. Select the Lambda function you created for MetaHub.

AWS Authentication

• Ensure you have AWS credentials set up on your local machine (or from where you will run MetaHub).

For example, you can use aws configure option.

aws configure

Or you can export your credentials to the environment.

export AWS_DEFAULT_REGION="us-east-1"export AWS_ACCESS_KEY_ID= "ASXXXXXXX"export AWS_SECRET_ACCESS_KEY= "XXXXXXXXX"export AWS_SESSION_TOKEN= "XXXXXXXXX"

Configuring Security Hub

• If you are running MetaHub for a single AWS account setup (AWS Security Hub is not aggregating findings from different accounts), you don't need to use any additional options; MetaHub will use the credentials in your environment. Still, if your IAM design requires it, it is possible to log in and assume a role in the same account you are logged in. Just use the options --sh-assume-role to specify the role and --sh-account with the same AWS Account ID where you are logged in.

• --sh-region: The AWS Region where Security Hub is running. If you don't specify a region, it will use the one configured in your environment. If you are using AWS Security Hub Cross-Region aggregation, you should use that region as the --sh-region option so that you can fetch all findings together.

• --sh-account and --sh-assume-role: The AWS Account ID where Security Hub is running and the AWS IAM role to assume in that account. These options are helpful when you are logged in to a different AWS Account than the one where AWS Security Hub is running or when running AWS Security Hub in a multiple AWS Account setup. Both options must be used together. The role provided needs to have enough policies to get and update findings in AWS Security Hub (if needed). If you don't specify a --sh-account, MetaHub will assume the one you are logged in.

• --sh-profile: You can also provide your AWS profile name to use for AWS Security Hub. When using this option, you don't need to specify --sh-account or --sh-assume-role as MetaHub will use the credentials from the profile. If you are using --sh-account and --sh-assume-role, those options take precedence over --sh-profile.

IAM Policy for Security Hub

This is the minimum IAM policy you need to read and write from AWS Security Hub. If you don't want to update your findings with MetaHub, you can remove the securityhub:BatchUpdateFindings action.

{    "Version": "2012-10-17",    "Statement": [        {            "Effect": "Allow",            "Action": [                "security hub:GetFindings",                "security hub:ListFindingAggregators",                "security hub:BatchUpdateFindings",                "iam:ListAccountAliases"            ],            "Resource": [                "*"            ]        }    ]}

Configuring Context

If you are running MetaHub for a multiple AWS Account setup (AWS Security Hub is aggregating findings from multiple AWS Accounts), you must provide the role to assume for Context queries because the affected resources are not in the same AWS Account that the AWS Security Hub findings. The --mh-assume-role will be used to connect with the affected resources directly in the affected account. This role needs to have enough policies for being able to describe resources.

IAM Policy for Context

The minimum policy needed for context includes the managed policy arn:aws:iam::aws:policy/SecurityAudit and the following actions:

• tag:GetResources
• lambda:GetFunction
• lambda:GetFunctionUrlConfig
• cloudtrail:LookupEvents
• account:GetAlternateContact
• organizations:DescribeAccount
• iam:ListAccountAliases

Examples

Inputs

MetaHub can read security findings directly from AWS Security Hub using its API. If you don't use Security Hub, you can use any ASFF-based scanner. Most cloud security scanners support the ASFF format. Check with them or leave an issue if you need help.

If you want to read from an input ASFF file, you need to use the options:

./metahub.py --inputs file-asff --input-asff path/to/the/file.json.asff path/to/the/file2.json.asff

You also can combine AWS Security Hub findings with input ASFF files specifying both inputs:

./metahub.py --inputs file-asff securityhub --input-asff path/to/the/file.json.asff

When using a file as input, you can't use the option --sh-filters for filter findings, as this option relies on AWS API for filtering. You can't use the options --update-findings or --enrich-findings as those findings are not in the AWS Security Hub. If you are reading from both sources at the same time, only the findings from AWS Security Hub will be updated.

Output Modes

MetaHub can generate different programmatic and visual outputs. By default, all output modes are enabled: json-short, json-full, json-statistics, json-inventory, html, csv, and xlsx.

The outputs will be saved in the outputs/ folder with the execution date.

If you want only to generate a specific output mode, you can use the option --output-modes with the desired output mode.

For example, if you only want to generate the output json-short, you can use:

./metahub.py --output-modes json-short

If you want to generate json-short, json-full and html outputs, you can use:

./metahub.py --output-modes json-short json-full html

• JSON
• HTML
• CSV
• XLSX

JSON

JSON-Short

Show all findings titles together under each affected resource and the AwsAccountId, Region, and ResourceType:

JSON-Full

Show all findings with all data. Findings are organized by ResourceId (ARN). For each finding, you will also get: SeverityLabel, Workflow, RecordState, Compliance, Id, and ProductArn:

JSON-Inventory

Show a list of all resources with their ARN.

JSON-Statistics

Show statistics for each field/value. In the output, you will see each field/value and the number of occurrences; for example, the following output shows statistics for six findings.

HTML

You can create rich HTML reports of your findings, adding your context as part of them.

HTML Reports are interactive in many ways:

• You can add/remove columns.
• You can sort and filter by any column.
• You can auto-filter by any column
• You can group/ungroup findings
• You can also download that data to xlsx, CSV, HTML, and JSON.

CSV

You can create CSV reports of your findings, adding your context as part of them.

 

XLSX

Similar to CSV but with more formatting options.

Customize HTML, CSV or XLSX outputs

You can customize which Context keys to unroll as columns for your HTML, CSV, and XLSX outputs using the options --output-tag-columns and --output-config-columns (as a list of columns). If the keys you specified don't exist for the affected resource, they will be empty. You can also configure these columns by default in the configuration file (See Customizing Configuration).

For example, you can generate an HTML output with Tags and add "Owner" and "Environment" as columns to your report using the:

./metahub --output-modes html --output-tag-columns Owner Environment

Filters

You can filter the security findings and resources that you get from your source in different ways and combine all of them to get exactly what you are looking for, then re-use those filters to create alerts.

• Security Hub Filtering
• Security Hub Filtering using YAML templates
• Config Filters
• Tags Filters

Security Hub Filtering

MetaHub supports filtering AWS Security Hub findings in the form of KEY=VALUE filtering for AWS Security Hub using the option --sh-filters, the same way you would filter using AWS CLI but limited to the EQUALS comparison. If you want another comparison, use the option --sh-template Security Hub Filtering using YAML templates.

You can check available filters in AWS Documentation

./metahub --sh-filters <KEY=VALUE>

If you don't specify any filters, default filters are applied: RecordState=ACTIVE WorkflowStatus=NEW

Passing filters using this option resets the default filters. If you want to add filters to the defaults, you need to specify them in addition to the default ones. For example, adding SeverityLabel to the default filters:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW

If a value contains spaces, you should specify it using double quotes: "ProductName="Security Hub"

You can add how many different filters you need to your query and also add the same filter key with different values:

Examples:

• Filter by Severity (CRITICAL):

./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL

• Filter by Severity (CRITICAL and HIGH):

./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL SeverityLabel=HIGH

• Filter by Severity and AWS Account:

./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL AwsAccountId=1234567890

• Filter by Check Title:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW Title="EC2.22 Unused EC2 security groups should be removed"

• Filter by AWS Resource Type:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup

• Filter by Resource ID:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceId="arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890"

• Filter by Finding Id:

./metahub --sh-filters Id="arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.19/finding/01234567890-1234-1234-1234-01234567890"

• Filter by Compliance Status:

./metahub --sh-filters ComplianceStatus=FAILED

Security Hub Filtering using YAML templates

MetaHub lets you create complex filters using YAML files (templates) that you can re-use when needed. YAML templates let you write filters using any comparison supported by AWS Security Hub like "EQUALS' | 'PREFIX' | 'NOT_EQUALS' | 'PREFIX_NOT_EQUALS". You can call your YAML file using the option --sh-template <<FILE>>.

You can find examples under the folder templates

• Filter using YAML template default.yml:

./metaHub --sh-template templates/default.yml

Config Filters

MetaHub supports Config filters (and associations) using KEY=VALUE where the value can only be True or False using the option --mh-filters-config. You can use as many filters as you want and separate them using spaces. If you specify more than one filter, you will get all resources that match all filters.

Config filters only support True or False values:

• A Config filter set to True means True or with data.
• A Config filter set to False means False or without data.

Config filters run after AWS Security Hub filters:

1. MetaHub fetches AWS Security Findings based on the filters you specified using --sh-filters (or the default ones).
2. MetaHub executes Context for the AWS-affected resources based on the previous list of findings
3. MetaHub only shows you the resources that match your --mh-filters-config, so it's a subset of the resources from point 1.

Examples:

• Get all Security Groups (ResourceType=AwsEc2SecurityGroup) with AWS Security Hub findings that are ACTIVE and NEW (RecordState=ACTIVE WorkflowStatus=NEW) only if they are associated to Network Interfaces (network_interfaces=True):

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup --mh-filters-config network_interfaces=True

• Get all S3 Buckets (ResourceType=AwsS3Bucket) only if they are public (public=True):

./metahub --sh-filters ResourceType=AwsS3Bucket --mh-filters-config public=False

Tags Filters

MetaHub supports Tags filters in the form of KEY=VALUE where KEY is the Tag name and value is the Tag Value. You can use as many filters as you want and separate them using spaces. Specifying multiple filters will give you all resources that match at least one filter.

Tags filters run after AWS Security Hub filters:

1. MetaHub fetches AWS Security Findings based on the filters you specified using --sh-filters (or the default ones).
2. MetaHub executes Tags for the AWS-affected resources based on the previous list of findings
3. MetaHub only shows you the resources that match your --mh-filters-tags, so it's a subset of the resources from point 1.

Examples:

• Get all Security Groups (ResourceType=AwsEc2SecurityGroup) with AWS Security Hub findings that are ACTIVE and NEW (RecordState=ACTIVE WorkflowStatus=NEW) only if they are tagged with a tag Environment and value Production:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup --mh-filters-tags Environment=Production

Updating Workflow Status

You can use MetaHub to update your AWS Security Hub Findings workflow status (NOTIFIED, NEW, RESOLVED, SUPPRESSED) with a single command. You will use the --update-findings option to update all the findings from your MetaHub query. This means you can update one, ten, or thousands of findings using only one command. AWS Security Hub API is limited to 100 findings per update. Metahub will split your results into 100 items chucks to avoid this limitation and update your findings beside the amount.

For example, using the following filter: ./metahub --sh-filters ResourceType=AwsSageMakerNotebookInstance RecordState=ACTIVE WorkflowStatus=NEW I found two affected resources with three finding each making six Security Hub findings in total.

Running the following update command will update those six findings' workflow status to NOTIFIED with a Note:

./metahub --update-findings Workflow=NOTIFIED Note="Enter your ticket ID or reason here as a note that you will add to the finding as part of this update."

The --update-findings will ask you for confirmation before updating your findings. You can skip this confirmation by using the option --no-actions-confirmation.

Enriching Findings

You can use MetaHub to enrich back your AWS Security Hub Findings with Context outputs using the option --enrich-findings. Enriching your findings means updating them directly in AWS Security Hub. MetaHub uses the UserDefinedFields field for this.

By enriching your findings directly in AWS Security Hub, you can take advantage of features like Insights and Filters by using the extra information not available in Security Hub before.

For example, you want to enrich all AWS Security Hub findings with WorkflowStatus=NEW, RecordState=ACTIVE, and ResourceType=AwsS3Bucket that are public=True with Context outputs:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsS3Bucket --mh-filters-checks public=True --enrich-findings

The --enrich-findings will ask you for confirmation before enriching your findings. You can skip this confirmation by using the option --no-actions-confirmation.

Findings Aggregation

Working with Security Findings sometimes introduces the problem of Shadowing and Duplication.

Shadowing is when two checks refer to the same issue, but one in a more generic way than the other one.

Duplication is when you use more than one scanner and get the same problem from more than one.

Think of a Security Group with port 3389/TCP open to 0.0.0.0/0. Let's use Security Hub findings as an example.

If you are using one of the default Security Standards like AWS-Foundational-Security-Best-Practices, you will get two findings for the same issue:

• EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports
• EC2.19 Security groups should not allow unrestricted access to ports with high risk

If you are also using the standard CIS AWS Foundations Benchmark, you will also get an extra finding:

• 4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389

Now, imagine that SG is not in use. In that case, Security Hub will show an additional fourth finding for your resource!

• EC2.22 Unused EC2 security groups should be removed

So now you have in your dashboard four findings for one resource!

Suppose you are working with multi-account setups and many resources. In that case, this could result in many findings that refer to the same thing without adding any extra value to your analysis.

MetaHub aggregates security findings under the affected resource.

This is how MetaHub shows the previous example with output-mode json-short:

"arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890": {  "findings": [    "EC2.19 Security groups should not allow unrestricted access to ports with high risk",    "EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports",    "4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389",    "EC2.22 Unused EC2 security groups should be removed"  ],  "AwsAccountId": "01234567890",  "Region": "eu-west-1",  "ResourceType": "AwsEc2SecurityGroup"}

This is how MetaHub shows the previous example with output-mode json-full:

"arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890": {  "findings": [    {      "EC2.19 Security groups should not allow unrestricted access to ports with high risk": {        "SeverityLabel": "CRITICAL",        "Workflow": {          "Status": "NEW"        },        "RecordState": "ACTIVE",        "Compliance": {          "Status": "FAILED"        },        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"      }    },    {      "EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports": {        "SeverityLabel": "HIGH",        "Workflow": {          "Status": "NEW"        },        "RecordState": "ACTIVE",<   br/>        "Compliance": {          "Status": "FAILED"        },        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"      }    },    {      "4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389": {        "SeverityLabel": "HIGH",        "Workflow": {          "Status": "NEW"        },        "RecordState": "ACTIVE",        "Compliance": {          "Status": "FAILED"        },        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"      }    },    {      "EC2.22    Unused EC2 security groups should be removed": {        "SeverityLabel": "MEDIUM",        "Workflow": {          "Status": "NEW"        },        "RecordState": "ACTIVE",        "Compliance": {          "Status": "FAILED"        },        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"      }    }  ],  "AwsAccountId": "01234567890",  "AwsAccountAlias": "obfuscated",  "Region": "eu-west-1",  "ResourceType": "AwsEc2SecurityGroup"}

Your findings are combined under the ARN of the resource affected, ending in only one result or one non-compliant resource.

You can now work in MetaHub with all these four findings together as if they were only one. For example, you can update these four Workflow Status findings using only one command: See Updating Workflow Status

Contributing

You can follow this guide if you want to contribute to the Context module guide.

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