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Turla turns PowerShell into a weapon in attacks against EU diplomats

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Attacks have dropped dramatically since 2015: Is hacktivism dead?
Hacktivist scene collapses as Anonymous hacker collective dies a slow death.

A cyberespionage group believed to be from Russia is once again striking political targets, and this time, PowerShell scripts have been weaponized to increase the power of their attacks.

Turla, also known as Snake or Uroburos, has been active since at least 2008. The advanced persistent threat (APT) group was previously linked to a backdoor implanted in Germany’s Federal Foreign Office for the purposes of data exfiltration in 2017, alongside attacks against the US military, a defense contractor, and a variety of European government entities.

The Russian hacking group is rarely quiet for long, and now, the APT has returned with a fresh wave of attacks against diplomatic entities in Eastern Europe.

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Previous attacks believed to be the work of Turla.


Kaspersky Labs

According to researchers from ESET, Turla has recently employed PowerShell scripts. The scripts allow “direct, in-memory loading and execution of malware executables and libraries,” the team says, which can also help them circumvent discovery on victim machines when a malicious executable is dropped on to a disk.

The use of PowerShell is not completely foreign to Turla. Last year, Kaspersky Labs said the APT was experimenting with PowerShell in-memory loads to bypass security protections, in the form of a customized open-source PoshSec-Mod system.

Turla’s loader was based on the legitimate PoshSec-Mod software, but in 2018, the custom code was considered flawed and would often crash due to bugs.

ESET says that now, a year later, it seems most of the cracks in the system have been smoothed over.

Turla has now improved its use of PowerShell and is using scripts to load an array of malware. However, the scripts in question are not considered simple droppers as they are able to “persist on the system as they regularly load into memory only the embedded executables,” according to ESET.

The PowerShell loader uses both a Windows Management Instrumentation (WMI) event subscription and alters the PowerShell profile (profile.ps1 file) to maintain persistence on an infected system.

In total, two WMI event filters and two WMI event consumers are created, of which the consumers are simple command lines to load PowerShell into the Windows registry.

See also: Cybersecurity 101: Protect your privacy from hackers, spies, and the government

When it comes to decrypting payloads stored in the registry, the 3DES algorithm is used. Once decrypted, a PowerShell reflective loader then comes into play.

“The executable is hardcoded in the script and is loaded directly into the memory of a randomly chosen process that is already running on the system,” the researchers say.

However, the selection process is not completely random as some processes, including avp.exe, avpsus.exe, klnagent.exe and vapm.exe, are excluded. These processes specifically refer to legitimate Kaspersky anti-virus protection software, which may indicate exclusion to avoid detection.

In some samples, ESET also found that Turla’s PowerShell script had been modified to bypass the Antimalware Scan Interface (AMSI), a Windows feature which permits the OS to integrate with antivirus products. Ithe script is also able to patch the AmsiScanBuffer process, which prevents the antivirus product from being able to perform any malware scans.

TechRepublic: How WannaCry is still launching 3,500 successful attacks per hour

The PowerShell loader is used to launch malware including a backdoor based on the RPC protocol which is able to exfiltrate data, facilitates the execution of commands, and support plugins for additional malware modules.

“Many variants of this RPC backdoor are used in the wild,” ESET says. “Among some of them, we have seen local proxies (using upnprpc as the endpoint and ncalrpc as the protocol sequence) and newer versions embedding PowerShellRunner to run scripts directly without using powershell.exe.”

A PowerShell backdoor is also available for download. Known as PowerStallion, the lightweight backdoor uses cloud storage — such as Microsoft OneDrive — as a form of command-and-control (C2) server. The researchers believe the backdoor is included as a recovery access tool for the major Turla backdoor.

CNET: Amazon’s new Alexa features put more emphasis on privacy

Earlier this month, the company discovered the existence of another major backdoor used by Turla. Dubbed LightNeuron, the malware has been specifically designed for Microsoft Exchange email servers and works as a mail transfer agent (MTA).

ESET says that while the PowerShell scripts have been used against political targets in Eastern Europe, the cybersecurity firm believes “the same scripts are used more globally against many traditional Turla targets in Western Europe and the Middle East.”

Previous and related coverage


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Cloud Data Security

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Data security has become an immutable part of the technology stack for modern applications. Protecting application assets and data against cybercriminal activities, insider threats, and basic human negligence is no longer an afterthought. It must be addressed early and often, both in the application development cycle and the data analytics stack.

The requirements have grown well beyond the simplistic features provided by data platforms, and as a result a competitive industry has emerged to address the security layer. The capabilities of this layer must be more than thorough, they must also be usable and streamlined, adding a minimum of overhead to existing processes.

To measure the policy management burden, we designed a reproducible test that included a standardized, publicly available dataset and a number of access control policy management scenarios based on real world use cases we have observed for cloud data workloads. We tested two options: Apache Ranger with Apache Atlas and Immuta. This study contrasts the differences between a largely role-based access control model with object tagging (OT-RBAC) to a pure attribute-based access control (ABAC) model using these respective technologies.

This study captures the time and effort involved in managing the ever-evolving access control policies at a modern data-driven enterprise. With this study, we show the impacts of data access control policy management in terms of:

  • Dynamic versus static
  • Scalability
  • Evolvability

In our scenarios, Ranger alone took 76x more policy changes than Immuta to accomplish the same data security objectives, while Ranger with Apache Atlas took 63x more policy changes. For our advanced use cases, Immuta only required one policy change each, while Ranger was not able to fulfill the data security requirement at all.

This study exposed the limitations of extending legacy Hadoop security components into cloud use cases. Apache Ranger uses static policies in an OT-RBAC model for the Hadoop ecosystem with very limited support for attributes. The difference between it and Immuta’s attribute-based access control model (ABAC) became clear. By leveraging dynamic variables, nested attributes, and global row-level policies and row-level security, Immuta can be quickly implemented and updated in comparison with Ranger.

Using Ranger as a data security mechanism creates a high policy-management burden compared to Immuta, as organizations migrate and expand cloud data use—which is shown here to provide scalability, clarity, and evolvability in a complex enterprise’s data security and governance needs.

The chart in Figure 1 reveals the difference in cumulative policy changes required for each platform configuration.

Figure 1. Difference in Cumulative Policy Changes

The assessment and scoring rubric and methodology is detailed in the report. We leave the issue of fairness for the reader to determine. We strongly encourage you, as the reader, to discern for yourself what is of value. We hope this report is informative and helpful in uncovering some of the challenges and nuances of data governance platform selection. You are encouraged to compile your own representative use cases and workflows and review these platforms in a way that is applicable to your requirements.

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GigaOm Radar for Data Loss Prevention

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Data is at the core of modern business: It is our intellectual property, the lifeblood of our interactions with our employees, partners, and customers, and a true business asset. But in a world of increasingly distributed workforces, a growing threat from cybercriminals and bad actors, and ever more stringent regulation, our data is at risk and the impact of losing it, or losing access to it, can be catastrophic.

With this in mind, ensuring a strong data management and security strategy must be high on the agenda of any modern enterprise. Security of our data has to be a primary concern. Ensuring we know how, why, and where our data is used is crucial, as is the need to be sure that data does not leave the organization without appropriate checks and balances.

Keeping ahead of this challenge and mitigating the risk requires a multi-faceted approach. People and processes are key, as, of course, is technology in any data loss prevention (DLP) strategy.

This has led to a reevaluation of both technology and approach to DLP; a recognition that we must evolve an approach that is holistic, intelligent, and able to apply context to our data usage. DLP must form part of a broader risk management strategy.

Within this report, we evaluate the leading vendors who are offering solutions that can form part of your DLP strategy—tools that understand data as well as evaluate insider risk to help mitigate the threat of data loss. This report aims to give enterprise decision-makers an overview of how these offerings can be a part of a wider data security approach.

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Key Criteria for Evaluating Data Loss Prevention Platforms

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Data is a crucial asset for modern businesses and has to be protected in the same way as any other corporate asset, with diligence and care. Loss of data can have catastrophic effects, from reputational damage to significant fines for breaking increasingly stringent regulations.

While the risk of data loss is not new, the landscape we operate in is evolving rapidly. Data can leave data centers in many ways, whether accidental or malicious. The routes for exfiltration also continue to grow, ranging from email, USB sticks, and laptops to ever-more-widely-adopted cloud applications, collaboration tools, and mobile devices. This is driving a resurgence in the enterprise’s need to ensure that no data leaves the organization without appropriate checks and balances in place.

Keeping ahead of this challenge and mitigating the risk requires a multi-faceted approach. Policy, people, and technology are critical components in a data loss prevention (DLP) strategy.

As with any information security strategy, technology plays a significant role. DLP technology has traditionally played a part in helping organizations to mitigate some of the risks of uncontrolled data exfiltration. However, both the technology and threat landscape have shifted significantly, which has led to a reevaluation of DLP tools and strategy.

The modern approach to the challenge needs to be holistic and intelligent, capable of applying context to data usage by building a broader understanding of what the data is, who is using it, and why. Systems in place must also be able to learn when user activity should be classified as unusual so they can better interpret signs of a potential breach.

This advanced approach is also driving new ways of defining the discipline of data loss prevention. Dealing with these risks cannot be viewed in isolation; rather, it must be part of a wider insider risk-management strategy.

Stopping the loss of data, accidental or otherwise, is no small task. This GigaOM Key Criteria Report details DLP solutions and identifies key criteria and evaluation metrics for selecting such a solution. The corresponding GigOm Radar Report identifies vendors and products in this sector that excel. Together, these reports will give decision-makers an overview of the market to help them evaluate existing platforms and decide where to invest.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

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