As your organization transitions from on-premises to hybrid cloud or pure cloud, how you think about threat detection must evolve as well—especially when confronting threats across many cloud environments. A new foundational framework for thinking about threat detection in public cloud computing is needed to better secure digital transformations.
Because these terms have had different meanings over time, here’s what we mean by threat detection and detection and response. A balanced security strategy covers all three elements of a security triad: prevention, detection, and response. Prevention can improve, but never becomes perfect. Despite preventative controls, we still need to be on the lookout for threats that penetrate our defenses. Finding and confirming malicious activities, and automatically responding to them or presenting them to the security team constitutes detection and response.
Vital changes impact the transition from the traditional environment to the cloud and affect three key areas:
- Threat landscapes
- IT environment
- Detection methods
First, threat landscapes change. This means new threats evolve, old threats disappear, and the importance of many threats changes. If you perform a threat assessment on your environment and then migrate the entire environment to the public cloud, even if you use the lift and shift approach, the threat assessment will look very different. MITRE ATT&CK Cloud can help us understand how some threat activities apply to public cloud computing.
Second, the entire technology environment around you changes. This applies to the types of systems and applications you as a defender would encounter, but also to technologies and operational practices. Essentially, cloud as a realm where you have to detect threats is different —this applies to the assets being threatened and technologies doing the detecting. Sometimes cloud looks to traditional “blue teams” as some alien landscape where they would have only challenges. In reality, cloud does bring a lot of new opportunities for detection. The main theme here is change, some for the worse and some for the better.
After all, cloud is
- Usually distributed—running over many regions and data centers
- Often immutable—utilizes systems that are replaced, rather than updated
- Ephemeral uses workloads often created for the task and then removed
- API driven—enabled by pervasive APIs
- Centered on identity layer—mostly uses identities and not just network perimeter to separate workloads
- Automatically scalable—able to expand with the increasing workload
- Shared with the provider
Sometimes the combination of Distributed, Immutable, and Ephemeral cloud properties is called a DIE triad. All these affect detection for the cloud environment.
Third, telemetry sources and detection methods also change. While this may seem like it’s derived from the previous point we made, that’s not entirely true. For some cloud services, and definitely for SaaS, a popular approach of using an agent such as EDR would not work. However, new and rich sources of telemetry may be available—Cloud Audit Logs are a great example here.
Similarly, the expectation that you can sniff traffic on the perimeter, and that you even will have a perimeter, may not be entirely correct. Pervasive encryption hampers Layer 7 traffic analysis, while public APIs rewrite the rules on what a perimeter is. Finally, detection sources and methods are also inherently shared with the cloud provider, with some under cloud service provider control while others are under cloud user control.
This leads to several domains where we can and should detect threats in the cloud.
Let’s review a few cloud threat detection scenarios.
Everybody highlights the role of identity in cloud security. Naturally, it matters in threat detection as well—and it matters a lot. While we don’t want to repeat the cliche that in a public cloud you are one IAM mistake away from a data breach, we know that cloud security missteps can be costly. To help protect organizations, Google Cloud offers services that automatically and in real-time analyze every IAM grant to detect outsiders being added—even indirectly.
Detecting threats inside compute instances such as virtual machines (VM) using agents seems to be about the past. After all, VMs are just servers, right? However, this is an area where cloud brings new opportunities. For example, VM Threat Detection allows security teams to do completely agentless YARA rule execution against their entire compute fleet.
Finally, products like BigQuery require new ways of thinking about detecting data exfiltration. Security Command Center Premium detects queries and backups in BigQuery that would copy data to different Google Cloud organizations.
Naturally, some things stay the same in the cloud. These include broad threat categories such as insiders or outsiders; steps in the cyber exploit chain such as coarse-grained stages of an attack; and the MITRE ATT&CK Tactics are largely unchanged. It is also likely that broad detection use cases stay the same.
What does that mean for the defenders?
- When you move to the cloud, your threats and your IT change—and change a lot.
- This means that using on-premises detection technology and approaches as a foundation for future development may not work well.
- This also means that merely copying all your on-premise detection tools and their threat detection content is not optimal.
- Instead, moving to Google Cloud is an opportunity to transform how you can achieve your continued goals of confidentiality, integrity, and availability with the new opportunities created by the technology and process of cloud.
Call to action:
- Listen to “Threat Models and Cloud Security” (ep12)
- Listen to “What Does Good Detection and Response Look Like in the Cloud? Insights from Expel MDR” (ep72)
- Listen to “Cloud Threats and How to Observe Them” (ep69) and read the related blog “How to think about cloud threats today”
- Review how to test cloud detections
- Read the guidance on cloud threat investigation with SCC and Chronicle
By: Anton Chuvakin (Head of Solutions Strategy) and Timothy Peacock (Product Manager)
Source: Google Cloud Blog