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As Businesses Move to the Cloud, Cybercriminals Follow Close Behind

Nastel® Technologies
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In the wake of COVID-19, data theft is by far the top tactic, followed by crypto mining and ransomware.

COVID-19 has introduced many new normals for business, and IT operations are no exception. Despite tighter technology budgets in the wake of the economic recession, companies are moving full steam ahead toward the cloud due to the agility and scale it provides.

According to a recent report from Flexera59% of companies surveyed plan on increasing their spending on cloud services in the post-pandemic world, with 30% of companies planning to spend “significantly” more. But cybercriminals and other threat actors are adapting to the technology, too, taking advantage of the fact that organizations are still discovering best practices surrounding cloud security and incident response.

The risk is high — with cloud systems often holding an unprecedented amount of valuable and sensitive data that can put both organizations and their customers in danger if breached. Our team of security incident responders at IBM X-Force IRIS have taken the opportunity to analyze the most common types of cloud compromises we’ve seen over the past year, how they’re being used to cause harm, and where organizations should focus to reduce their risks. Here’s what we found.

How Threat Actors Are Compromising Cloud Environments
While there are several ways we’ve seen cybercriminals target cloud systems, the most common initial infection vector was remote exploitation of cloud applications. In fact, this top attack pathway accounted for 45% of the cloud-related cybersecurity events we examined in our recent “Cloud Threat Landscape Report” (registration required). In many cases, vulnerable applications were present in the environment but remained undetected. Addressing these remote vulnerabilities has been challenging, in part due to the lack of public cataloging of discovered issues.

In addition to vulnerabilities, another core issue is security flaws introduced by users via misconfigurations. We’ve seen threat actors take advantage of misconfigured cloud servers to siphon over 1 billion records from compromised environments in 2019. The subsequent data leaks remain one of the greatest sources of record loss across the board and can quickly allow access to sensitive information from organizations. Threat actors are often able to take advantage of both these configuration errors and vulnerabilities within the applications due to employees standing up new cloud apps on their own, outside of approved channels, making shadow IT a core concern when it comes to cloud security.

How Threat Actors Use the Cloud to Cause Harm
While we have seen hackers target the cloud for activities like crypto mining and ransomware, data theft is by far the top tactic we see attackers taking once they’ve breached cloud systems. The cloud is ideal for hosting large amounts of information, and this data can be stolen by threat actors and quickly sold on underground marketplaces. The types of data stolen can vary, but the most common targets are sensitive personally identifiable information and financial data such as credit card numbers. In one case, we found unauthorized access to cloud assets leading to losses of more than $50,000 in less than one hour. While the type of data stolen largely depends on threat actor motivations and sophistication, in cloud environments the amount of data available can be much greater, making the potential impact of a breach that much more damaging to the organization.

Nastel has created a feed with some new information on COVID-19! Click here.

This article originally appeared on darkreading.com To read the full article and see the images, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • zAdvanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
  • Raw information handling and analytics speed
  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

Nastel Technologies, a global leader in integration infrastructure (i2) and transaction management for mission-critical applications, helps companies achieve flawless delivery of digital services.

 

Nastel delivers Integration Infrastructure Management (i2M), Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate. To answer business-centric questions and provide actionable guidance for decision-makers.
The Nastel Platform delivers:

  • Integration Infrastructure Management (i2M)
  • Predictive and Proactive anomaly detection that virtually eliminates war room scenarios and improves root cause analysis
  • Self-service for DevOps and CI: CD teams to achieve their speed to market goals
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  • Visualization of end-to-end user experiences through the entire application stack
  • Innovative Machine Learning AI to compare real-time to the historical record and discover and remediate events before they are critical
  • Large scale, high-performance complex event processing that delivers tracing, tracking, and stitching of all forms of machine data
  • And much more

Comments

  • Dave
    December 21, 2021
    Fascinating piece of research, but what is unclear from this summary of this study is if the AI is actually more or less reliable than human analysis. 5 radiologists is quite a small sample, and the range of accuracy of fake detection is so wide that the results of the AI actually fit inside that range. Are the volumes of tests enough to be statistically viable? And of course the real issue is that compromised images could take many forms, some could be complete real images replacing the image to be tested, while others could have artifacts added or removed. So is the issue AI or the ability to secure the way an image is managed from creation to analysis. That then becomes a integration infrastructure management (i2M) problem.
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