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Sift Security and WannaCry

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The WannaCry ransomware attack has left security teams around the world scrambling to make sure they are protected and to assess whether they have been victimized. To protect themselves, organizations need to have visibility into which systems are vulnerable and be able to rapidly roll out patches.  To understand whether they have been targeted, they need visibility into the channels over which the ransomware is distributed.  To understand whether they have been infected, they need visibility into the endpoints. Over the past weekend, I was bombarded with questions from current customers, potential customers, former colleagues, friends, and family.  Am I vulnerable? How do I protect myself? How do I know if I’ve been hit? What do I do if I’ve been hit? What can you do to help me? This post focuses primarily on the last question.  What can we at Sift Security do to help an organization respond to a massive ransomware attack? I break this down into four categories, visibility, analytics…
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Next-Generation SIEMs

Intelligence, Speed, Simplicity, AutomationOverviewMajor network and security trends, including exponentially increasing network traffic, cloud architectures, complex attack surfaces, and advanced adversaries, have created new challenges for security operations in adapting to this changing threat landscape.
Increased Traffic, Hybrid Cloud Architectures, and Sophisticated Adversaries Are Overwhelming SOCs
The Security Operations Center is faced with alert overload, often paralyzed with too much information to filter, prioritize, and act upon. The end result is an inability to find the true risk amongst thousands of alerts every day with the largest of organizations easily facing millions of alerts per day.Incident responders are challenged at finding relevant information or seeing the relationships amongst disparate indicators of compromise that are buried within logs, causing delays in assessing, understanding, and mitigating incidents.T…

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 investigating alerts an…

Sift Security Tools Release for AWS Monitoring - CloudHunter

We are excited to release CloudHunter, a web service similar to AWS CloudTrail that allows customers to visually explore and investigate their AWS cloud infrastructure.  At Sift, we felt this integration would be important for 2 main reasons:
Investigating events happening in AWS directly from Amazon is painful, unless you know exactly what event you're looking for.There are not many solutions that allow customers to follow chains of events spanning across the on-premises network and AWS on a single screen. At Netflix, we spent a lot of time creating custom tools to address security concerns in our AWS infrastructure because we needed to supplement the AWS logs, and created visualizations based on that data.  The amazing suite of open source tools from Netflix are the solutions they used to resolve their own pain points.  Hosting microservices in the cloud with continuous integration and continuous deployment can be extremely efficient and robust.  However, tracking events, especi…

Applying Machine Learning to Cybersecurity

In a recent article on the OPM hack, the author describes a pretty typical security situation for a large enterprise:The Office of Personnel Management repels 10 million attempted digital intrusions per month—mostly the kinds of port scans and phishing attacks that plague every large-scale Internet presence—so it wasn’t too abnormal to discover that something had gotten lucky and slipped through the agency’s defenses.Enormous pressure at scale from criminals makes automated systems essential for security. While humans can inspect packages coming into the building, only a computer can work quickly enough to inspect packets. Firewalls are the prototypical example: you allow certain traffic through according to a set of rules based on the source and destination IPs and the ports and protocols being used.In recent years, there's been a lot of buzz about machine learning in cybersecurity--wouldn't it be great if your automated system could learn and adapt, stop threats you don’t ev…