Understanding the finding groups page - Amazon Detective

Understanding the finding groups page

The finding groups page lists all the finding groups collected by Amazon Detective from your behavior graph. Take note of the following attributes of finding groups:

Severity of a group

Each finding group is assigned a severity based on the AWS Security Finding Format (ASFF) severity of the associated findings. ASFF finding severity values are Critical, High, Medium, Low, or Informational from most to least severe. The severity of a grouping is equal to the highest severity finding among the findings in that grouping.

Groups that consist of Critical or High severity findings that impact a large number of entities should be prioritized for investigations, as they are more likely to represent high-impact security issues.

Group title

In the Title column, each group has a unique ID and a non-unique title. These are based on the ASFF type namespace for the group and the number of findings within that namespace in the cluster. For example, if a grouping has the title: Group with: TTP (2), Effect (1), and Unusual behavior (2) it includes five total findings consisting of two findings in the TTP namespace, one finding in the Effect namespace, and two findings in the Unusual Behavior namespace. For a complete list of namespaces, see Types taxonomy for ASFF.

Tactics in a group

The Tactics column in a group details which tactics category the activity falls into. The tactics, techniques, and procedures categories in the following list align to the MITRE ATT&CK matrix.

You can select a tactic on the chain to see a description of the tactic. Following the chain is a list of the tactics detected within the group. These categories and the activities they typically represent are as follows:

  • Initial Access – An adversary is trying to get into someone else’s network.

  • Execution – An adversary is trying to get into someone else’s network.

  • Persistence – An adversary is trying to maintain their foothold.

  • Privilege Escalation – An adversary is trying to gain higher-level permissions.

  • Defense Evasion – An adversary is trying to avoid being detected.

  • Credential Access – An adversary is trying to steal account names and passwords.

  • Discovery – An adversary is trying to understand and learn about an environment.

  • Lateral Movement – An adversary is trying to move through an environment.

  • Collection – An adversary is trying to gather data of interest to their goal.

  • Command and Control – An adversary is trying to get into someone else’s network.

  • Exfiltration – An adversary is trying to steal data.

  • Impact – An adversary is trying to manipulate, interrupt, or destroy your systems and data.

  • Other – Indicates activity from a finding that does not align with tactics listed in the matrix.

Entities within a group

The Entities column contains details on the specific entities detected within this grouping. Select this value for a breakdown of entities based on the categories: Identity, Network, Storage, and Compute. Examples of entities in each category are:

  • Identity – IAM principals and AWS accounts, such as user and role

  • Network – IP address or other networking and VPC entities

  • Storage – Amazon S3 buckets or DDBs

  • Compute Amazon EC2 instances or Kubernetes containers

Accounts within a group

The Accounts column tells you what AWS accounts own entities involved with the findings in the group. The AWS Accounts are listed by name and AWS ID so you can prioritize investigations of activity involving critical accounts.

Findings within a group

The Findings column has a lists the entities within a group by severity. The findings include Amazon GuardDuty findings, Amazon Inspector findings, AWS security findings, and evidence from Detective. You can select the graph to see an exact count of findings by severity.

GuardDuty findings are part of the Detective core package and are ingested by default. All other AWS security findings that are aggregated by Security Hub are ingested as an optional data source. See Source data used in a behavior graph for more details.