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Microsoft shares new threat intelligence, security guidance during global crisis

April 8th, 2020 No comments

Ready or not, much of the world was thrust into working from home, which means more people and devices are now accessing sensitive corporate data across home networks. Defenders are working round the clock to secure endpoints and ensure the fidelity of not only those endpoints, but also identities, email, and applications, as people are using whatever device they need to get work done. This isn’t something anyone, including our security professionals, were given time to prepare for, yet many customers have been thrust into a new environment and challenged to respond quickly. Microsoft is here to help lighten the load on defenders, offer guidance on what to prioritize to keep your workforce secure, and share resources about the built-in protections of our products.

Attackers are capitalizing on fear. We’re watching them. We’re pushing back.

Our inboxes, mobile alerts, TVs, and news updates are all COVID-19, all the time. It’s overwhelming and attackers know it. They know many are clicking without looking because stress levels are high and they’re taking advantage of that. That’s why we’re seeing an increase in the success of phishing and social engineering attacks. Attackers don’t suddenly have more resources they’re diverting towards tricking users; instead they’re pivoting their existing infrastructure, like ransomware, phishing, and other malware delivery tools, to include COVID-19 keywords that get us to click. Once we click, they can infiltrate our inboxes, steal our credentials, share more malicious links with coworkers across collaboration tools, and lie in wait to steal information that will give them the biggest payout. This is where intelligent solutions that can monitor for malicious activity across – that’s the key word – emails, identities, endpoints, and applications with built-in automation to proactively protect, detect, respond to, and prevent these types of attacks from being successful will help us fight this battle against opportunistic attackers.

Our threat intelligence teams at Microsoft are actively monitoring and responding to this shift in focus. Our data shows that these COVID-19 themed threats are retreads of existing attacks that have been slightly altered to tie to this pandemic. This means we’re seeing a changing of lures, not a surge in attacks. Our intelligence shows that these attacks are settling into a rhythm that is the normal ebb and flow of the threat environment:

  • Every country in the world has seen at least one COVID-19 themed attack (see map below). The volume of successful attacks in outbreak-hit countries is increasing, as fear and the desire for information grows. Our telemetry shows that China, the United States, and Russia have been hit the hardest.
  • The trendy and pervasive Trickbot and Emotet malware families are very active and rebranding their lures to take advantage of the outbreak. We have observed 76 threat variants to date globally using COVID-19 themed lures (map below).
  • Microsoft tracks thousands of email phishing campaigns that cover millions of malicious messages every week. Phishing campaigns are more than just one targeted email at one targeted user. They include potentially hundreds or thousands of malicious emails targeting hundreds or thousands of users, which is why they can be so effective. Of the millions of targeted messages we see each day, roughly 60,000 include COVID-19 related malicious attachments or malicious URLs.
  • While that number sounds very large, it’s important to note that that is less than two percent of the total volume of threats we actively track and protect against daily, which reinforces that the overall volume of threats is not increasing but attackers are shifting their techniques to capitalize on fear. Attackers are impersonating established entities like the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), and the Department of Health to get into inboxes. Here’s an example of what just one of these malicious emails looks like now compared to before the COVID-19 crisis:

Comparison of malicious emails used in malware campaigns before the crisis and during

  • In a single day, SmartScreen sees and processes more than 18,000 malicious COVID-19-themed URLs and IP addresses. This again shows us that attackers are getting more aggressive and agile in the delivery of their attacks – using the same delivery methods, but swapping out the malicious URLs on a more frequent basis in an effort to evade machine learning protections.
  • Microsoft Office 365 Advanced Threat Protection prevented a big phishing campaign that used a fake Office 365 sign-in page to capture credentials. Roughly 2,300 unique HTML attachments posing as COVID-19 financial compensation information were caught in 24 hours in this one campaign. We expect to see more campaigns that utilize the economic fear from lost income, as governments widen the mandatory shutdown of their economies and stimulus funds begin to be issued in the U.S.
  • Several advanced persistent threat and nation-state actors have been observed targeting healthcare organizations and using COVID-19-themed lures in their campaigns. We continue to identify, track, and build proactive protections against these threats in all of our security products. When customers are affected by these attacks, Microsoft notifies the customer directly to help speed up investigations. We also report malicious COVID-19-themed domains and URLs to the proper authorities so that they can be taken down, and where possible, the individuals behind them prosecuted.

Map showing global impact of COVID-19-themed-attacks

Relative impact of COVID-19 themed attacks across the world by file count (as of April 7, 2020)

From endpoints and identities to the cloud, we have you covered

While phishing email is a common attack vector, it’s only one of the many points of entry for attackers. Defenders need a much broader view and solutions for remediation than visibility into just one entry method. An attacker’s primary goal is to gain entry and expand across domains so they can persist in an organization and lie in wait to steal or encrypt as much sensitive information as they can to reap the biggest payout. Defenders require visibility across each of these domains and automated correlation across emails, identities, endpoints, and cloud applications to see the full scope of compromise. Only with this view can defenders adequately remediate affected assets, apply Conditional Access, and prevent the same or similar attacks from being successful again.

During this trying time, we want to remind our customers what protections you have built into our products and offer guidance for what to prioritize:

  • Protect endpoints with Microsoft Defender ATP, which covers licensed users for up to five concurrent devices that can be easily onboarded at any time. Microsoft Defender ATP monitors threats from across platforms, including macOS. Our tech community post includes additional guidance, best practices, onboarding, and licensing information.
  • Enable multi-factor authentication (MFA) and Conditional Access through Azure Active Directory to protect identities. This is more important than ever to mitigate credential compromise as users work from home. We recommend connecting all apps to Azure AD for single sign-on – from SaaS to on-premises apps; enabling MFA and applying Conditional Access policies; and extending secure access to contractors and partners. Microsoft also offers a free Azure AD service for single sign-on, including MFA using the Microsoft Authenticator app.
  • Safeguard inboxes and email accounts with Office 365 ATP, Microsoft’s cloud-based email filtering service, which shields against phishing and malware, including features to safeguard your organization from messaging-policy violations, targeted attacks, zero-days, and malicious URLs. Intelligent recommendations from Security Policy Advisor can help reduce macro attack surface, and the Office Cloud Policy Service can help you implement security baselines.
  • Microsoft Cloud App Security can help protect against shadow IT and unsanctioned app usage, identify and remediate cloud-native attacks, and control how data travels across cloud apps from Microsoft or third-party applications.

Microsoft Threat Protection correlates signals from across each of these domains using Azure ATP, Microsoft Defender ATP, Office 365 ATP, and Microsoft Cloud App Security, to understand the entire attack chain to help defenders prioritize which threats are most critical to address and to auto-heal affected user identities, email inboxes, endpoints, and cloud apps back to a safe state. Our threat intelligence combines signals from not just one attack vector like email phishing, but from across emails, identities, endpoints, and cloud apps to understand how the threat landscape is changing and build that intelligence into our products to prevent attack sprawl and persistence. The built-in, automated remediation capabilities across these solutions can also help reduce the manual workload on defenders that comes from the multitude of new devices and connections.

Azure Sentinel is a cloud-native SIEM that brings together insights from Microsoft Threat Protection and Azure Security Center, along with the whole world of third-party and custom application logs to help security teams gain visibility, triage, and investigate threats across their enterprise. As with all Microsoft Security products, Azure Sentinel customers benefit from Microsoft threat intelligence to detect and hunt for attacks. Azure Sentinel makes it easy to add new data sources and scale existing ones with built-in workbooks, hunting queries, and analytics to help teams identify, prioritize, and respond to threats. We recently shared a threat hunting notebook developed to hunt for COVID-19 related threats in Azure Sentinel.

Cloud-delivered protections are a critical part of staying up to date with the latest security updates and patches. If you don’t already have them turned on, we highly recommend it. We also offer advanced hunting through both Microsoft Threat Protection and Azure Sentinel.

We’ll keep sharing and protecting – stay tuned, stay safe

Remember that we at Microsoft are 3,500 defenders strong. We’re very actively monitoring the threat landscape, we’re here to help: we’re providing resources, guidance, and for dire cases we have support available from services like the Microsoft Detection and Response (DART) team to help investigate and remediate.

All of our guidance related to COVID-19 is and will be posted here. We will continue to share updates across channels to keep you informed. Please stay safe, stay connected, stay informed.

THANK YOU to our defenders who are working tirelessly to keep us secure and connected during this pandemic.

 

 

-Rob and all of us from across Microsoft security

 

 

To stay up to date with verified information on the COVID-19 crisis, the following sites are available:

 

The post Microsoft shares new threat intelligence, security guidance during global crisis appeared first on Microsoft Security.

How artificial intelligence stopped an Emotet outbreak

February 14th, 2018 No comments

At 12:46 a.m. local time on February 3, a Windows 7 Pro customer in North Carolina became the first would-be victim of a new malware attack campaign for Trojan:Win32/Emotet. In the next 30 minutes, the campaign tried to attack over a thousand potential victims, all of whom were instantly and automatically protected by Windows Defender AV.

How did Windows Defender AV uncover the newly launched attack and block it at the outset? Through layered machine learning, including use of both client-side and cloud machine learning (ML) models. Every day, artificial intelligence enables Windows Defender AV to stop countless malware outbreaks in their tracks. In this blog post, well take a detailed look at how the combination of client and cloud ML models detects new outbreaks.

Figure 1. Layered detected model in Windows Defender AV

Client machine learning models

The first layer of machine learning protection is an array of lightweight ML models built right into the Windows Defender AV client that runs locally on your computer. Many of these models are specialized for file types commonly abused by malware authors, including, JavaScript, Visual Basic Script, and Office macro. Some models target behavior detection, while other models are aimed at detecting portable executable (PE) files (.exe and .dll).

In the case of the Emotet outbreak on February 3, Windows Defender AV caught the attack using one of the PE gradient boosted tree ensemble models. This model classifies files based on a featurization of the assembly opcode sequence as the file is emulated, allowing the model to look at the files behavior as it was simulated to run.

Figure 2. A client ML model classified the Emotet outbreak as malicious based on emulated execution opcode machine learning model.

The tree ensemble was trained using LightGBM, a Microsoft open-source framework used for high-performance gradient boosting.

Figure 3a. Visualization of the LightBGM-trained client ML model that successfully classified Emotet’s emulation behavior as malicious. A set of 20 decision trees are combined in this model to classify whether the files emulated behavior sequence is malicious or not.

Figure 3b. A more detailed look at the first decision tree in the model. Each decision is based on the value of a different feature. Green triangles indicate weighted-clean decision result; red triangles indicate weighted malware decision result for the tree.

When the client-based machine learning model predicts a high probability of maliciousness, a rich set of feature vectors is then prepared to describe the content. These feature vectors include:

  • Behavior during emulation, such as API calls and executed code
  • Similarity fuzzy hashes
  • Vectors of content descriptive flags optimized for use in ML models
  • Researcher-driven attributes, such as packer technology used for obfuscation
  • File name
  • File size
  • Entropy level
  • File attributes, such as number of sections
  • Partial file hashes of the static and emulated content

This set of features form a signal sent to the Windows Defender AV cloud protection service, which runs a wide array of more complex models in real-time to instantly classify the signal as malicious or benign.

Real-time cloud machine learning models

Windows Defender AVs cloud-based real-time classifiers are powerful and complex ML models that use a lot of memory, disk space, and computational resources. They also incorporate global file information and Microsoft reputation as part of the Microsoft Intelligent Security Graph (ISG) to classify a signal. Relying on the cloud for these complex models has several benefits. First, it doesnt use your own computers precious resources. Second, the cloud allows us to take into consideration the global information and reputation information from ISG to make a better decision. Third, cloud-based models are harder for cybercriminals to evade. Attackers can take a local client and test our models without our knowledge all day long. To test our cloud-based defenses, however, attackers have to talk to our cloud service, which will allow us to react to them.

The cloud protection service is queried by Windows Defender AV clients billions of times every day to classify signals, resulting in millions of malware blocks per day, and translating to protection for hundreds of millions of customers. Today, the Windows Defender AV cloud protection service has around 30 powerful models that run in parallel. Some of these models incorporate millions of features each; most are updated daily to adapt to the quickly changing threat landscape. All together, these classifiers provide an array of classifications that provide valuable information about the content being scanned on your computer.

Classifications from cloud ML models are combined with ensemble ML classifiers, reputation-based rules, allow-list rules, and data in ISG to come up with a final decision on the signal. The cloud protection service then replies to the Windows Defender client with a decision on whether the signal is malicious or not all in a fraction of a second.

Figure 4. Windows Defender AV cloud protection service workflow.

In the Emotet outbreak, one of our cloud ML servers in North America received the most queries from customers; corresponding to where the outbreak began. At least nine real-time cloud-based ML classifiers correctly identified the file as malware. The cloud protection service replied to signals instructing the Windows Defender AV client to block the attack using two of our ML-based threat names, Trojan:Win32/Fuerboos.C!cl and Trojan:Win32/Fuery.A!cl.

This automated process protected customers from the Emotet outbreak in real-time. But Windows Defender AVs artificial intelligence didnt stop there.

Deep learning on the full file content

Automatic sample submission, a Windows Defender AV feature, sent a copy of the malware file to our backend systems less than a minute after the very first encounter. Deep learning ML models immediately analyzed the file based on the full file content and behavior observed during detonation. Not surprisingly, deep neural network models identified the file as a variant of Trojan:Win32/Emotet, a family of banking Trojans.

While the ML classifiers ensured that the malware was blocked at first sight, deep learning models helped associate the threat with the correct malware family. Customers who were protected from the attack can use this information to understand the impact the malware might have had if it were not stopped.

Additionally, deep learning models provide another layer of protection: in relatively rare cases where real-time classifiers are not able to come to a conclusive decision about a file, deep learning models can do so within minutes. For example, during the Bad Rabbit ransomware outbreak, Windows Defender AV protected customers from the new ransomware just 14 minutes after the very first encounter.

Intelligent real-time protection against modern threats

Machine learning and AI are at the forefront of the next-gen real-time protection delivered by Windows Defender AV. These technologies, backed by unparalleled optics into the threat landscape provided by ISG as well as world-class Windows Defender experts and researchers, allow Microsoft security products to quickly evolve and scale to defend against the full range of attack scenarios.

Cloud-delivered protection is enabled in Windows Defender AV by default. To check that its running, go to Windows Settings > Update & Security > Windows Defender. Click Open Windows Defender Security Center, then navigate to Virus & threat protection > Virus &threat protection settings, and make sure that Cloud-delivered protection and Automatic sample submission are both turned On.

In enterprise environments, the Windows Defender AV cloud protection service can be managed using Group Policy, System Center Configuration Manager, PowerShell cmdlets, Windows Management Instruction (WMI), Microsoft Intune, or via the Windows Defender Security Center app.

The intelligent real-time defense in Windows Defender AV is part of the next-gen security technologies in Windows 10 that protect against a wide spectrum of threats. Of particular note, Windows 10 S is not affected by this type of malware attack. Threats like Emotet wont run on Windows 10 S because it exclusively runs apps from the Microsoft Store. Learn more about Windows 10 S. To know about all the security technologies available in Windows 10, read Microsoft 365 security and management features available in Windows 10 Fall Creators Update.

 

Geoff McDonald, Windows Defender Research
with Randy Treit and Allan Sepillo

 

 


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