This blog includes content from Episode One “Confidentially Speaking” of our Cloud Security Podcast, hosted by Anton Chuvakin (Head of Solutions Strategy) and Timothy Peacock (Product Manager). You should listen to the whole conversation for more insights and deeper context.LEARN MORECloud Security Podcast – Confidentially SpeakingListen to the Cloud Security Podcast with guest Nelly Porter, Group Product Manager @ Google.

We all deal with a lot of sensitive data and today, enterprises must entrust all of this sensitive data to their cloud providers. With on-premises systems, companies used to have a very clear idea about who could access data and who was responsible for protecting that data. Now, data lives in many different places—on-premises, at the edge, or in the cloud. 

You may already know that Google Cloud provides encryption for data when it is in transit or at rest by default, but did you also know we also allow you to encrypt data in use—while it’s being processed? 

In this podcast episode, Product Manager Nelly Porter gave us a peek under the hood of  confidential computing at Google Cloud. 

What is confidential computing? 

Google Cloud’s Confidential Computing started with a dream to find a way to protect data when it’s being used. We developed breakthrough technology to encrypt data when it is in use, leveraging Confidential VMs and GKE Nodes to keep code and other data encrypted when it’s being processed in memory. The idea is to ensure encrypted data stays private while being processed, reducing exposure.

During the episode, Nelly Porter explained that Google Cloud’s approach is based on hardware and CPU capability. Confidential Computing is built on the newest generation of AMD CPU processors, which have a Secure Encrypted Virtualization extension that enables the hardware to generate encryption keys that are ephemeral and associated with a single VM.  Basically, they are never stored anywhere else and are not extractable—the software will never have access to those keys. 

“You can do whatever you need to do, but you will be in a cryptographically isolated space that no other strangers passing by can see.”

Memory controllers use the keys to quickly decrypt cache lines when you need to execute an instruction and then immediately encrypts them again. In the CPU itself, data is decrypted but it remains encrypted in memory. 

Confidential computing aims to mitigate gaps in data security

Nelly also shed some light on why confidential computing will continue to play a central role in the future of cloud computing. She pointed out that one of the biggest gaps companies are looking to cover is securing data when it is in use. 

Data that is encrypted on-premises or in cloud storage, but the biggest risk for companies is when they start working with that data. For instance, imagine you encrypted your data on-premises and only you hold the keys. You upload that data into Cloud Storage buckets—simple, safe, and secure. 

But now, you want to train machine learning models based on that data. When you upload it into your environment, it’s no longer protected. Specifically, data in reserved memory is not encrypted.We’re trying to ensure that your data is always protected in whatever state it exists, so fewer people have the opportunity to make mistakes or maliciously expose your data.

Top takeaways about confidential computing 

Throughout the conversation, Nelly also shared interesting points about the development and direction of confidential computing at Google Cloud. 

Here were our favorite takeaways from the podcast: 

We worked hard to make Google Cloud’s approach simple.
We’ve invested a lot of time and effort into investigating the possibilities (and limitations) of confidential computing to avoid introducing residual risks to our approach. For instance, the early introduction of hardware capable of confidential computing in the industry required IT teams to have the resources to rewrite or refactor their app, severely limiting their ability to adopt it within their organizations. 

With Confidential Computing, teams can encrypt data in use without making any code changes in their applications.  All Google Cloud workloads can run as Confidential VMs, enabled with a single checkbox, making the transition to confidential computing completely simple and seamless. 

“A lot of customers understand the values of confidential computing, but simply cannot support re-writing the entire application. It’s why Google Cloud, in particular, decided to take a different approach and use models that were incredibly easy to implement, ensuring that our customers would not have those barriers to cross.”

Confidential computing is for more than just fintech. 
There is, of course, a compelling use case for confidential computing at highly-regulated companies in financial, government, life sciences, and public sectors. However, Nelly shared that her team didn’t anticipate that even verticals without significant regulation or compliance requirements would be so interested in this technology, mostly to pre-empt privacy concerns. 

Many companies see confidential computing as a way to create cryptographic isolation in the public cloud, allowing them to further ease any user or client concerns about what they are doing to protect sensitive data. For instance, during COVID-19, there was an increase in small research organizations that wanted to collaborate across large datasets of sensitive data. 

“Prior to confidential computing, it wasn’t possible to collaborate because you needed the ability to share very sensitive data sets among multiple parties while ensuring none of them will have access to this data, but the results will benefit all of them—and us.”

An open community, working together will be key for the future. 
Nelly also shared that there are plans to extend memory protections beyond just CPUs to cover GPUs, TPUs, and FPGAs. Google Cloud is working with multiple industry vendors and companies to develop confidential computing solutions that will cover specific requirements and use cases.

Confidential computing will not be achieved by a single organization – it will require many people to come together. We are a member of the Confidential Computing Consortium, which aims to solve security for data in use and includes other vendors like Red Hat, Intel, IBM, and Microsoft. 

“Google alone would not be able to accomplish confidential computing. We need to ensure that all vendors, GPU, CPU, and all of them follow suit. Part of that trust model is that it’s third parties’ keys and hardware that we’re exposing to a customer.”

There are no magic bullets when it comes to security. 
Confidential computing is still an emerging, very new technology and unsurprisingly, there are a lot of questions about what it does and how it works. It’s important to remember that there is no such thing as the one-tool-fits-all-threats security solution. Instead, Nelly notes that confidential computing is yet another tool that can be added to your security arsenal. 

“No solution will ever be the magic bullet that will make everyone happy and secure, guaranteed. But confidential computing is an addition to our toolbox of defense against gaps we have to take super seriously and invest in solving.” 

Did you enjoy this blog post? To listen to the full conversation, head over to Episode One “Confidentially Speaking” of our Cloud Security Podcast, hosted by Anton Chuvakin (Head of Solutions Strategy) and Timothy Peacock (Product Manager). 

We also recommend checking out other episodes of the Cloud Security Podcast by Google for more interesting stories and insights about security in the cloud, from the cloud, and of course, what we’re doing at Google Cloud.

Broadcom is a global technology leader that designs, develops, and supplies many semiconductor and infrastructure software solutions. Broadcom’s category-leading product portfolio serves critical markets including data center, networking, software, broadband, wireless, storage, and industrial sectors. 

Our customers, many of whom operate in the federal public sector, need ready-made SaaS solutions to secure their infrastructure while meeting compliance requirements. As head of platform engineering for Broadcom and its subsidiaries, my team is responsible for designing, testing, and building the common orchestration platform and services for our federal customers.

Since early 2021, we’ve partnered with Google Cloud to deliver best-in-class cloud solutions for  our multinational customers with speed, scale and efficiency, which earned us the Google Cloud Customer of the Year Award. When it came to creating plug-and-play security and compliance solutions for federal organizations in the United States, we turned to Assured Workloads.

Simplifying the path to compliance 

Assured Workloads provides out-of-the-box capabilities that allow us to easily create and maintain controlled environments that address security and compliance needs across different verticals and sectors. This includes enforcement of data residency, administrative and personnel controls, and managing encryption keys. 

For example, in the United States, federal government agencies need to use solutions that comply with FedRAMP, the government-wide standard for cloud computing security, while the Department of Defense (DoD) needs to comply with Impact Level (IL) standards. Assured Workloads helps us create solutions with built-in guardrails to ensure our customers automatically operate within whichever standard applies.  

Additionally, Assured Workloads guarantees that only personnel with the necessary clearance and permissions have access to information, and ​​it offers integrated cryptographic control over data, including customer-managed encryption keys based on the chosen compliance program. 

As a result of using Assured Workloads, our Symantec Security suite can provide a comprehensive set of security services that are being certified for FedRAMP. These include Web Security Service, Data Loss Prevention, Cloud Access Security Broker, and Symantec Endpoint Protection (SEP). 

We also offer our enterprise software products as services through Google Cloud. Rally Software, our enterprise agility tool, and Clarity PPM, our project and portfolio management tool, are already certified for FedRAMP. Additionally Clarity PPM is undergoing certification for IL4 compliance for our DoD clients. 

Sophisticated solutions for a secure future 

Given the intricate nature of securing the cloud environment and the business processes it handles, integrating Assured Workloads into our service offering has been simple and streamlined. Many of our services already run on Google Cloud, using Google Kubernetes Engine and Google Compute Engine, and since those Google Cloud services can be configured for all programs in an Assured Workloads environment, we were able to provide solutions to federal agencies without making significant changes to our deployment or configurations. This has helped save enormous engineering effort by avoiding a customized one-off effort to manage a Federal environment.

Google Kubernetes Engine (GKE) is one of the critical services in our environment, and Google Cloud releases many new GKE capabilities each year. Assured Workloads allows us to benefit from all the latest GKE innovations that come through automatic updates, maintaining parity with the commercial cloud without compromising on security and compliance requirements.

Compliance is a must-have for our federal clients, and our duty as providers of security and software services is to supply them with easy-to-use, efficient solutions they can trust. With the power of Assured Workloads streamlining our infrastructure software solutions hosted in Google Cloud, we can better support our regulated customers and further grow our software and security service businesses.

As the way people work continues to evolve, keeping security policies in place that protect organizations but give workers the ability to get things done is more important than ever. IT and security teams must aim to stay a step ahead of web-based security threats that come their organization’s way. To help, the Center for Internet Security (CIS) team has released the latest CIS Benchmark 2.1 for Google Chrome. This Benchmark offers independent recommendations on which Chrome policies to configure to help support organizations’ security and compliance needs. Thanks to Chrome being built with security at its core, in many cases, Chrome default settings are aligned with CIS recommendations.

Chrome is secure by default, but we also pride ourselves on providing customizations for enterprises to allow Chrome to better fit the needs of their business. And with hundreds of policies available through Chrome Browser Cloud Management and Group Policy Objects (Note: The CIS Benchmark is also available as a GPO), organizations can do just that. 

Throughout the CIS guide you’ll notice that there are different designations for configuration profiles. Any labeled Level 1, are considered to be a good baseline for an organization. Level 2 profiles are recommended for deployments that require the highest level of security, but note that these settings could have a trade off on user productivity. We recommend looking at each setting and determining if it’s a good fit for your business. 

The benchmark is made up of five sections:

• Enforced Defaults — Notes policies that are configured by default when you install Chrome. Enforcing these settings at an enterprise level can prevent these settings from being changed by business users to less secure options.
• Attack Surface Reduction — Details how to disable web features that may not be necessary in your enterprise environment and could reduce your overall attack surface.
• Privacy — Surfaces settings that improve user privacy.
• Data Loss Prevention — Contains settings that can help prevent data loss and protect your organization’s data. (Note: These recommendations cover additional capabilities that can be added to Chrome through BeyondCorp Enterprise). 
• Forensics (Post Incident) — Shares recommendations on policies that give insights into post incident forensics and analysis. 

Organizations can use these benchmarks to optimize the best way to secure Chrome in their environment. Download the CIS Benchmark here and check out our team’s configuration guide for additional recommendations on how to configure Chrome.

Note: This benchmark was created using a consensus review process composed of subject matter experts. Consensus participants provide perspective from a diverse set of backgrounds such as consulting, software development, audit and compliance, security  research, operations, government, and legal. While these recommendations come from a trusted source, it’s important for each organization to weigh which policies make the most sense for their business.

The security world keeps changing, with new tools and new threats in the ever-evolving arms race that is cybersecurity. To keep you up to speed on all that Google Cloud is doing to help safeguard your data and your applications, welcome to the first installment of the Security Roundup. In this regular series, I’ll be sharing a selection of news and guidance to help ensure you have the resources you need for your hectic, high-stakes harm-preventing job.

Applying the principle of least privilege to GKE clusters

Access to your GKE clusters – just like any other resource – should be based on the principle of least privilege. Use groups, individual roles, and Identity and Access Management tools to limit who can do what with your Kubernetes clusters in Google Cloud. These principles can help you control who uses which elements of the Kubernetes API as well as how they access your clusters. More details are in Anthony Bushong’s video.

Ensuring CI/CD pipeline security

To make sure only trusted code artifacts enter your continuous integration and deployment pipeline, you can take advantage of Binary Authorization on Google Cloud, and then only permit signed builds to go through. Learn more in Martin Omander’s video interview and walkthrough with XIaowen Lin.

Protecting against denial of service and flooding attacks

Once your applications are on the web, they become potential targets for attack. You can use Cloud Armor to protect against many types of traffic attacks, including distributed denial-of-service (DDoS), and HTTP POST flood attacks. After learning the normal traffic patterns of your apps, Cloud Armor monitors for anomalies and then generates alerts or intervenes on your behalf to block malicious traffic. Learn more with Arman Rye in this video.

Defending against cyberattacks with Palo Alto Networks

If you use Palo Alto Networks products for endpoint protection or network monitoring, now you can integrate the signals from those systems into Google Cloud security tools. You can ingest device health conclusions from Palo Alto Networks Cortex XDR to boost your visibility into those endpoints’ state and improve your trust decisions. BeyondCorp Enterprise users can incorporate Cortex XDR metadata into access policies, leveraging additional posture information to add another level of trusted device information and operate with more confidence. Check out the details in this interview with Mason Yan at Palo Alto Networks.

Dealing with Apache Log4j 2 vulnerability(ies)

Attackers who exploit the Apache Log4j 2 vulnerability can execute arbitrary code on a vulnerable server. Read this post by the Google Cybersecurity Action Team for more details on log4j vulnerabilities (CVE-2021-44228 and CVE-2021-45046) and how you can find out if you’re affected. It includes advice for how to use Google Cloud products like Binary Authorization rules and Security Command Center to keep your cloud deployments safe.

Good luck out there, and remember: Keep your data yours!