Security Chatbots Aim To Simplify Incident Detection And Response

Emerging intelligent assistants help analyze and automate response to attacks.

Security analysts soon may get extra help from intelligent assistants that help automate incident detection and response across endpoints.
Firms including Endgame and Demisto are building security chatbots to address the lack of resources and automated solutions available to todays security analysts.
Security teams are faced with two major challenges: insufficient resources to stop attacks in-progress and lack of automated solutions to uncover malicious behavior in time to prevent information theft, said Endgame CTO Jamie Butler in a statement.
Endgame today rolled out Artemis, an intelligent assistant integrated with its endpoint detection and response (EDR) platform. Artemis detects malicious behavior and pulls from user data to suggest responses and ultimately help save time.
Security analysts interact with Artemis via chat interface; communication is typed (not spoken). They can ask questions like What anomalies were seen in the past 12 hours? Artemis will present any relevant data and based on that, analysts may ask what can be done. The assistant will offer recommendations to address the problem before it escalates.
One of the goals behind Artemis was to help businesses struggling with a lack of security talent, explains Endgame data scientist Bobby Filar. Customers had expressed frustration with their lack of employees to comb through data and decide how threats should be addressed.
We see that a lot with organizations setting up their own SOC teams or threat hunting teams, says Filar. There just arent enough resources to do that effectively.
Tier-one analysts dont need to understand another query language or how the data is structured, he continues. The tool helps them find anomalies, conduct investigations, and eliminate threats akin to a tier-three analyst.
Endgame consulted a range of security pros including threat hunters, forensics experts, and SOC analysts during development, adds data scientist Richard Seymour. They helped formulate questions that analysts should ask while searching for threats.
Artemis was built with natural language processing and machine learning so it will eventually be able to anticipate priorities and recognize patterns. As people start to ask questions, the tool will understand their individual habits and be able to better formulate responses, says Filar. Analysts can also write their own workflow scripts to customize it over time.
Both data scientists acknowledge Artemis has room for improvement, however. Right now the greatest shortcoming is a lack of use cases, says Filar. He hopes the tool will get better at understanding typos and diversity in vocabulary; for example, how businesses refer to different events.
Artemis is not the first nor the only chatbot for endpoint security. Demisto offers a similar tool called Demisto Enterprise, an automation and ChatOps platform for SOCs. It was recently adopted by mapping platform Esri.
ChatOps, like Artemis, is powered by intelligence. Its also designed to automate security operations and incident management so analysts can cut down on investigation and response time.
The tool is powered by DBot, a security chatbot that communicates with teams via ChatOps in the Demisto Enterprise platform. Analysts can share information, order DBot to perform actions, and learn the results it reports back.
ChatOps was created upon learning large enterprise customers struggled with documenting and sharing their actions with their teams, explains Demisto co-founder and marketing vice president Rishi Bhargava. The tool integrates with about 100 security products; analysts can use these integrations to build common workflows, which save time when alerts occur.
This tool is different from Artemis in the sense that it pulls data from a range of products, relying on them for information, he says. Its really a security orchestration layer; its not really a security product by itself, he explains.
Demistos tool was also built to address the talent gap, Bhargava notes. Analysts in the same chatroom can communicate across geographies, which is necessary for teams who hire remote analysts because they cant find talent nearby. The bot learns over time to identify common actions that analysts learn. New and future analysts can be instructed on these actions, helping them develop expertise.
In the future, Demisto plans to evolve its tool to give a more analytical and deconstructed view of data to analysts, says Bhargava. It also plans to expand the amount of integrations available.
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