Skip to main content

The Cloud Attack Chain

In an earlier posting on Public Cloud Security Detection Use Cases, we attempted to map
detections to the traditional Lockheed Martin Kill Chain. After further reflection,
we decided that cloud infrastructure threats are sufficiently different enough to warrant a
modified attack chain framework. We are releasing the Cloud Attack Chain framework today.
The Cloud Attack Chain is a simplified attack chain model that describes typical attacks on public cloud
infrastructure.  The attack chain describes how an attacker gains access to a victim’s cloud environment, how
they move laterally through the target cloud infrastructure, and what malicious actions they perform.   Our
new Whitepaper describes the four stages of the attack chain and provides detailed examples of some real-world
attacks.  

As a preview, the stages of the Cloud Attack Chain are:

1. Exposure: Exposure of cloud resources is at the beginning of any cloud attack. Exposure can be deliberate,
based on business trade-offs, or accidental, resulting from misconfigured resources or unpatched vulnerabilities.  
Exposures are where attackers start looking for a way in.

2. Access:  Access occurs when an attacker has figured out how to exploit an exposure and gains access to your
cloud infrastructure.

3. Lateral Movement: With access to your infrastructure, the attacker identifies targets for the attack, gaining
access to additional resources or escalating their privileges.

4. Actions: Now having access to the resources they need, the attacker performs some malicious action to fulfill
their objectives.

We invite you to learn more by downloading the paper at https://siftsecurity.com/papers/Sift-Security-The-Cloud-Attack-Chain/view

Popular posts from this blog

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 leader in …

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, espec…

Using the Security Event Graph to Drive Alert Prioritization

One of the biggest differentiators at Sift Security is our security event graph: We map security events into a graph database. We then analyze the graph structure to prioritize alerts. Specifically, we look for clusters of interrelated alerts, score the clusters, and surface the clusters to the analyst. The analyst can then investigate each cluster in order, quickly assessing the threat and resolving the alerts in bulk.  
Our algorithms do the important work of sifting through isolated alerts and separating the false alarms and low priority alerts from high priority security incidents. We identify the high priority incidents by analyzing how alerts are related to each other. Key to this approach is our security event graph. This graph is stored in a graph database, a relationship-centric database that enables rapid execution of complex queries that would be very expensive to make in a traditional RDBMS.  The graph structure enables us to rapidly traverse relationships and find interr…