> For the complete documentation index, see [llms.txt](https://docs.expel.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.expel.io/detection-strategy-guides/s-z/vectra-ai-ndr-detection-strategy.md). # Vectra AI (NDR) Detection Strategy ## Product Overview Vectra AI is a cybersecurity company that uses artificial intelligence to detect and respond to cyber threats, particularly in hybrid and multi-cloud environments. They offer a platform that analyzes network traffic and behavior to identify and prioritize malicious activities, ultimately helping security teams to investigate and remediate threats more effectively. ## Detection Strategy for Vectra AI (NDR) ### Detection Network traffic monitoring is a critical element of our detection strategy, offering insight into the activity of data as it moves across an organization's systems. The network traffic data source focuses on network connection creation (the initial construction of a network connection such as socket information, and src and dst IP and Ports ), network traffic content (logged network traffic data showing both protocol header and body values like PCAP), and network traffic flow (summarized network packet data, with metrics, such as protocol headers and volume like netflow or http logs). For Vectra, Expel focuses on ingesting detection events and enriching them with additional entity details. We can then leverage our detection pipeline to surface relevant alerts based on a number of criteria: * **Severity** - Vectra’s AI assigns a ‘Severity Score’ to every detection. This score is calculated based on threat score, certainty, and potential impact. * **Certainty** - Vectra’s AI assigns a ‘Certainty Score’ to every detection. This score represents how confident Vectra is that the activity is not a false positive. * **Entity Urgency** - Vectra’s AI assigns an ‘Urgency Score’ to hosts and users in your environment. This score increases and decreases based on observed activity. * **Redundancy** - We prioritise detections that are not already covered by another integration in order to avoid duplication. Our strategy for Vectra also aligns with our overall detection strategy, see [About Detection Strategy](/workbench-reference/detections/about-detection-strategy.md) in the Help Center for more information. ### Response Network technologies are utilized for support across many types of Expel Alerts such as endpoint and cloud. The main focus of the response strategy is on source IP, destination IP, and domain tracking to identify related connections, along with user activity summaries to give extra alert context. ## What We Support for Vectra AI (NDR) To see a comprehensive list of the most up-to-date Expel detection rules, vendor detection rules, opt-in detections, and available DUETs (**d**id yo**u** **e**xpect **t**his) that we support for Vectra AI (NDR), you can visit the [Detections page](https://workbench.expel.io/tools/detections/all?filter=%7B%22supportedTech%22%3A%7B%22is%22%3A%5B%22vectra%3A1.0.0%22%5D%7D%7D) in Workbench or ask your Sales or Support rep for the most recent download. | **Supported versions** | | | ------------------------------------------- | ------------------------------------------------------------------------------ | | **Supported platform** | | | **Vectra AI (NDR) detection rules support** | Yes. | | **Detection rules written by Expel** | No. | | **Investigative support through Workbench** | No. We access the console directly with a "SOC Analyst" role account. | | **Hunting support** |

No. Hunting is not currently available for this integration.


| ## Additional Details and Common Questions ### Console Access A vendor alert does not typically include all of the contextual timeline activity surrounding the event of interest. Because this integration does not allow us to get all necessary data via the API, we will ask you for a certain level of console access during onboarding. The level of access that we require is meant to support essential triage and research activities, and to help us determine the vector and extent of attacker activity for an identified threat. At minimum, we will ask for visibility into alert data, timeline events recorded, and live response/real time response shell (if applicable). ### DUET A DUET (**d**id yo**u** **e**xpect **t**his) rule flags certain events as needing an immediate verification or notification, and bypasses the normal internal event triage process. The events subject to DUET rules contain behaviors that are not typically indicative of true security incidents, as they are related to policy violations or potential risk. There are a number of workflows that a DUET may follow. When enabled, the activity will be flagged for investigation and will be routed to you (rather than to us) to take a specified first action. To see the specific DUET rules currently supported for this integration, visit the [Detections page](https://workbench.expel.io/tools/detections/all) in Workbench. ### Use Cases Not Supported * We do not support custom or community-provided rules for Vectra. * We do not support any remediation/auto-remediation actions with our Vectra integration. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.expel.io/detection-strategy-guides/s-z/vectra-ai-ndr-detection-strategy.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.