Outdated Linux Versions, Misconfigurations Triggering Cloud Attacks: Report

The “Linux Threat Report 2021 1H” from Trend Micro found that Linux cloud operating systems are heavily targeted for cyberattacks, with nearly 13 million detections in the first half of this year. As organizations expand their footprint in the cloud, correspondingly, they are exposed to the pervasive threats that exist in the Linux landscape.

This latest threat report, released Aug. 23, provides an in-depth look at the Linux threat landscape. It discusses several pressing security issues that affect Linux running in the cloud.

Key findings include that Linux is powerful, universal, and dependable, but not devoid of flaws, according to the researchers. However, like other operating systems, Linux remains susceptible to attacks.

Linux in the cloud powers most infrastructures, and Linux users make up the majority of the Trend Micro Cloud One enterprise customer base at 61 percent, compared to 39 percent Windows users.

The data comes from the Trend Micro Smart Protection Network (SPN) or the data reservoir for all detections across all Trend Micro’s products. The results show enterprise Linux at considerable risk from system configuration mistakes and outdated Linux distributions.

For instance, data from internet scan engine Censys.io revealed that nearly 14 million results for exposed devices running any sort of Linux operating system on July 6, 2021. A search for port 22 in Shodan, a port commonly used for Secure Shell Protocol (SSH) for Linux-based machines, showed almost 19 million exposed devices detected as of July 27, 2021.

Like any operating system, security depends entirely on how you use, configure, or manage the operating system. Each new Linux update tries to improve security. However, to get the value you must enable and configure it correctly, cautioned Joseph Carson, chief security scientist and advisory CISO at Thycotic.

“The state of Linux security today is rather good and has evolved in a positive way, with much more visibility and security features built-in. Nevertheless, like many operating systems, you must install, configure, and manage it with security in mind — as how cybercriminals take advantage is the human touch,” he told LinuxInsider.

Top Linux Threats

The Trend Micro Report disclosed rampant malware families within Linux systems. Unlike previous reports based on malware types, this study focused on the prevalence of Linux as an operating system and the pervasiveness of the various threats and vulnerabilities that stalk the OS.

That approach showed that the top three threat detections originated in the U.S. (almost 40 percent), Thailand (19 percent), and Singapore (14 percent).

Detections arose from systems running end-of-life versions of Linux distributions. The four expired distributions were from CentOS versions 7.4 to 7.9 (almost 44 percent), CloudLinux Server (more than 40 percent), and Ubuntu (about 7 percent).

Trend Micro tracked more than 13 million malware events flagged from its sensors. Researchers then cultivated a list of the prominent threat types consolidated from the top 10 malware families affecting Linux servers from Jan. 1 to June 30, 2021.

The top threat types found in Linux systems in the first half of 2021 are:

  • Coinminers (24.56 percent)
  • Web shell (19.92 percent)
  • Ransomware (11.56 percent)
  • Trojans (9.56 percent)
  • Others (3.15 percent)

The top four Linux distributions where the top threat types in Linux systems were found in H1-2021 are:

  • CentOS Linux (50.80 percent)
  • CloudLinux Server (31.24 percent)
  • Ubuntu Server (9.56 percent)
  • Red Hat Enterprise Linux Server (2.73 percent)

Top malware families include:

  • Coinminers (25 percent)
  • Web shells (20 percent)
  • Ransomware (12 percent)

CentOS Linux and CloudLinux Server are the top Linux distributions with the found threat types, while web application attacks happen to be the most common attack vector.

Web Apps Top Targets

Most of the applications and workloads exposed to the internet run web applications. Web application attacks are among the most common attack vectors in Trend Micro’s telemetry, said researchers.

If launched successfully, web app attacks allow hackers to execute arbitrary scripts and compromise secrets. Web app attacks also can modify, extract, or destroy data. The research shows that 76 percent of the attacks are web-based.

The LAMP stack (Linux, Apache, MySQL, PHP) made it inexpensive and easy to create web applications. In a very real way, it democratized the internet so anyone can set up a web application, according to John Bambenek, threat intelligence advisor at Netenrich.

“The problem with that is that anyone can set up a web app. While we are still waiting for the year of Linux on the desktop, it is important for organizations to use best practices for their web presences. Typically, this means staying on top of CMS patches/updates and routine scanning with even open-source tools (like the Zed Attack Proxy) to find and remediate SQL injection vulnerabilities,” he told LinuxInsider.

The report referenced the Open Web Application Security Project (OWASP) top 10 security risks, which lists injection flaws and cross-scripting (XSS) attacks remaining as high as ever. What strikes Trend Micro researchers as significant is the high number of insecure deserialization vulnerabilities.

This is partly due to the ubiquity of Java and deserialization vulnerabilities in it, according to Trend Micro. It’s report also noted that the Liferay Portal, Ruby on Rails, and Red Hat JBoss deserialization vulnerabilities as being prominent.

Attackers also try to use vulnerabilities where there is broken authentication to gain unauthorized access to systems. Plus, the number of command injection hits also poses a surprise as they are higher than what Trend Micro’s analysts expected.

Expected Trend

It is no surprise that the majority of these attacks are web-based. Every website is different, written by different developers with different skill sets, observed Shawn Smith, director of infrastructure at nVisium.

“There is a wide range of different frameworks across a multitude of languages with various components that all have their own advantages and drawbacks. Combine this with the fact that not all developers are security gurus, and you’ve got an incredibly alluring target,” he told LinuxInsider.

Web servers are one of the most common services to expose to the internet because most of the world interacts with the internet through websites. There are other areas exposed — like FTP or IRC servers — but the vast majority of the world is using websites as their main contact point to the internet.

“As a result, this is where attackers will focus to get the biggest return on investment for their time spent,” Smith said.

OSS Linked to Supply Chain Attacks

Software supply chains must be secured to deal with the Linux attack landscape as well, noted the Trend Micro report. Attackers can insert malicious code to compromise software components of third-party suppliers. That code then connects to a command-and-control server to download and deploy backdoors and other malicious payloads within the system, causing remote code.

This can lead to remote code execution to an enterprise’s system and computing resources. Supply chain attacks can also come from misconfigurations, which are the second top incident type in cloud-native environments, according to the Trend Micro report. More than 56 percent of their survey respondents had a misconfiguration or known unpatched vulnerability incident involving their cloud-native applications.

Hackers are having an easy time. “The major attack types on web-based applications have remained constant over the recent past. That, combined with the rising time-to-fix and declining remediation rates, makes the hackers’ job easier,” said Setu Kulkarni, vice president of strategy at NTT Application Security.

Organizations need to test applications in production, figuring out what their top three-to-five vulnerability types are. Then launch a targeted campaign to address them, rinse, and repeat, he recommended.

The “Linux Threat Report 2021 1H” is available here.

Jack M. Germain has been an ECT News Network reporter since 2003. His main areas of focus are enterprise IT, Linux and open-source technologies. He is an esteemed reviewer of Linux distros and other open-source software. In addition, Jack extensively covers business technology and privacy issues, as well as developments in e-commerce and consumer electronics. Email Jack.

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Charmed Kubeflow 1.4 Brings Smart, Agile MLOps to any Cloud

Machine Learning

Canonical is pushing the limits on its MLOps platform to automate the full lifecycle of feature engineering, training, and release workflows for machine learning (ML) models.

The Canonical Data Platform team on Tuesday announced the release of its MLOps platform Charmed Kubeflow 1.4. The new free release enables data science teams to securely collaborate on AI/ML innovation on any cloud, from concept to production.

Charmed Kubeflow is an open source MLOps platform released under the Apache License 2.0. The platform helps data scientists automate the workflow from ideation to production.

This latest release includes upstream Kubeflow 1.4 with many improvements over previous versions. It now includes support for MLFlow integration.

Charmed Kubeflow deploys in any environment without constraints, paywall, or restricted features. Data labs and MLOps teams only need to train their data scientists and engineers once to work consistently and efficiently on any cloud or on-premises installation.

The platform’s main benefit is a centralized, browser-based system that runs on any conformant Kubernetes. Other benefits include enhanced productivity, improved governance, and reduced risks associated with shadow IT.

The latest release adds several features for advanced model lifecycle management, including upstream Kubeflow 1.4. Future releases will continue to focus on empowering data scientists and data engineers, according to Rob Gibbon, product manager at Canonical.

“One area of focus for the product is composability and extensibility via a component ecosystem,” he told LinuxInsider.

“Additionally, we will be continually improving solution enterprise readiness, and of course tracking upstream Kubeflow to ensure data scientists continue to get access to the very latest features in a fully supported manner,” said Gibbon.

Getting Started

Kubeflow is available now. Data scientists can get started with it using Juju, the unified operator framework for hyper-automated management of applications running on both virtual machines and Kubernetes.

The new release is in the CharmHub stable channel now. It can be deployed to any conformant Kubernetes cluster using a single Juju command:
juju deploy kubeflow

The full installation guide is available here for free. The software is open source with 24/7 support or fully managed service options available from Canonical.

Engineers and data scientists can rapidly set up an evaluation environment with or without GPU acceleration using just a single system running MicroK8s. Evaluators can read the getting started guide. It takes less than 30 minutes to start improving AI automation.

Under the Hood

This release provides better model lifecycle management with Kubeflow 1.4 and MLFlow integration. Kubeflow 1.4 comes with major usability improvements over previous releases, including a unified training operator.

The new training operator supports the popular AI/ML frameworks TensorFlow, MXNet, XGBoost, and PyTorch. This greatly simplifies the solution, improving future extensibility and consumes fewer resources on the Kubernetes cluster.

Kubeflow 1.4 has support for MLFlow integration, enabling true automated model lifecycle management using MLFlow metrics and the MLFlow model registry.

MLFlow is an open-source platform for AI/ML model lifecycle management. It includes features for experimentation, reproducibility, and deployment. MLFlow also offers a centralized model registry.

Using Integration

Data scientists and data engineers can use the MLFlow integration capability to build automatic model drift detection and trigger a Kubeflow model retraining pipeline.

Model drift occurs as model accuracy starts to decline over time due to changes in the live prediction dataset versus the training dataset.

Enabling MLFlow on a Kubernetes cluster and integrating it with a Charmed Kubeflow deployment using the Juju unified operator framework is straightforward, and the MLFlow Juju operator is available in CharmHub for immediate deployment.

Charmed Kubeflow 1.4 fully supports multi-user deployment scenarios out of the box for all Kubeflow components, including Kubeflow notebooks, pipelines, and experiments.

Charmed Kubeflow 1.4

This update simplifies using Charmed Kubeflow to improve governance and reduce the occurrence of shadow-IT environments. It also helps to combat organizational data leakage.

The authentication provider integration guide provides more information on setting up multi-user access controls for the Charmed Kubeflow 1.4 MLOps platform. 

Jack M. Germain has been an ECT News Network reporter since 2003. His main areas of focus are enterprise IT, Linux and open-source technologies. He is an esteemed reviewer of Linux distros and other open-source software. In addition, Jack extensively covers business technology and privacy issues, as well as developments in e-commerce and consumer electronics. Email Jack.

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