Detection Use Cases

We wanted to share update on Sift Security detection. At Sift Security, we are focused on enabling ingestion, analysis and investigation of a wide variety of data sources. As it relates to analysis, this has led us to develop a very flexible suite of detection mechanisms. Currently, Sift Security provides two distinct detection mechanisms: a custom rules engine and an advanced anomaly detection platform. Both tools come with built-in support for common use cases and are extensible, enabling users to add detections on the fly.
Some of our customers have been asking to share more information about specific use cases we detect. In response to these requests, we created a new document called Sift Security Detection Use Cases. Please check it out and let us know if you have any questions!

Data Exfiltration from AWS S3 Buckets

You will have no doubt heard by now about the recent Booz Allen Hamilton breach that took place on Amazon Web Services – in short, a shocking collection of 60,000 government sensitive files were left on a public S3 bucket (file storage in Amazon Web Services) for all to see. We are all probably too overwhelmed to care, given all the recent breaches we have been hearing about in the news. But with this breach it was different, it involved a trusted and appointed contractor whose job it was to follow security policies, put in place to avoid such incidents. So was this incident accidental or malicious? More, later about the tools we can use to tell the difference between the two. First, lets recap what happened. The Incident According to Gizmodo , the 28GB of data that was leaked not only contained sensitive information on recent government projects, but at least a half dozen unencrypted passwords belonging to government contractors with Top Secret Clearance – meaning anyone who got

Sift Joins Netskope, the Cloud Security Leader

Four years ago, we started Sift with the mission of simplifying security operations and incident response for the public cloud. In that time, we have assembled a fantastic team, created an innovative cloud detection and response solution, and have worked with many market-leading customers. I’m delighted to share that we’ve taken yet another step forward — as announced today, Sift is now officially part of Netskope. You can read more about this on Netskope CEO Sanjay Beri’s blog or in the official announcement on the Netskope website. For our customers, investors, partners, and team, this is an exciting new chapter. Let me tell you why we’re so excited. Since the beginning, Netskope has had an unmatched vision for the cloud security market. Having started in 2012, they initially focused on SaaS security and quickly followed that with IaaS security capabilities. Six years later, they are now more than 500 employees strong and used by a quarter of the Fortune 100. They are a l

Sift Security vs. Elastic Search and Elastic Graph

We are often asked, “What is the difference between Sift Security and Elastic Graph ?” This is a great question that typically comes from folks who are already familiar with Elasticsearch [0] and Elastic Graph [1]. The answer boils down to the following: Elastic Graph is a tool for visualizing arbitrary aggregate search results. Elasticsearch is a Restful search that distributed, and has analytics engine that solves a number of use cases such as mapping from Python to ES REST endpoints. Sift Security uses a graph database to simplify and accelerate specific security use cases. In this blog post, we describe the advantages of each of these approaches, and conclude with a discussion of when to use each. Advantages of Sift Security vs ElasticSearch and Elastic Graph Query speed Sift Security builds a property graph to represent security log events at ingestion time. We do this work at ingestion time for one reason: to speed up common investigative queries. When investi

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