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Ukrainian police arrest hacker who infected over 2,000 users with DarkComet RAT



Ukrainian police have arrested a 42-old-man on charges of infecting over 2,000 users across 50 countries with the DarkComet remote access trojan (RAT).

The man was arrested this week after police executed a search warrant at his residence in the city of Lviv, in Western Ukraine.

In a press release published today, Ukrainian police said they found a modified administrator panel for the DarkCommet RAT on the man’s computer, along with the malware’s installation files, and screenshots of infected victims’ computers.

Image of the suspect’s DarkComet admin panel opened on his home computer.

Image: Ukrainian Police

DarkComet was first released in 2008 and was initially advertised as a legitimate remote administration toolkit. Because of its intrusive spying capabilities, the tool was quickly adopted by malware developers, becoming a popular RAT within months [1, 2].

The tool’s author, French software developer Jean-Pierre Lesueur, stopped developing the tool in 2012 after it became evident that most of the tool’s use cases were for cybercrime and after reports surfaced that Syrian authorities had been using it to crack down on dissidents [1, 2].

Despite this, DarkComet development was picked up by other unofficial developers, and the RAT continued to plague users even to this day[1, 2], being recently spotted even in the arsenal and operations of North Korean government-backed hackers.

DarkCommet works as all your typical RATs, and is comprised of “clients” that are installed on infected computers, which send data back to a “server” module –the administration panel.

The RAT clients can take screenshots of users’ screens, log keystrokes, steal documents, install additional malware on victims’ computers, disable OS features, and steal passwords stored inside other local apps –just to name a few of its many features.

How to determine if you’ve been infected

Ukrainian police did not release the name of the suspect they arrested this week, but they did publish instructions on how to detect if users have been infected by this man’s DarkComet campaign. The instructions are as follows:

  1. Press the Windows + R keys to open a Run dialog.
  2. Type “cmd” and press Enter.
  3. In the command prompt type “netstat -nao” and press Enter.
  4. In the list of current connections search for one trying to connect to a foreign IP address of, on port 1604 or 81.

Image: Ukrainian Police

If users find that their computer is trying to connect to such an IP address, then they’ve been infected by this particular DarkComet RAT campaign. At this point, victims should either wipe and reinstall their operating systems; use an antivirus program to remove the DarkComet malware; or contact a professional to do these things for them.

If you’re a company, then you should contact your legal department first, as they might want to work with your IT staff to investigate and determine what data might have been stolen.

Ukrainian police are also interested in hearing from victims, most likely to build a better case against the suspect and determine the extent of the damage he caused.

Poor OpSec led to the man’s arrest

But while Ukrainian police didn’t reveal any details about the suspect or how they’ve tracked him down, it’s pretty clear how they’ve done it to an external observer.

Searching for the IP address of on Shodan, a search engine for Internet-connected devices, we found a listing for this IP that was marked as a “DarkComet trojan” command-and-control server.


The most obvious detail is that the IP address hosting this DarkComet administration panel wasn’t assigned to the infrastructure of a data center, but to a regular residential internet service provider, meaning the suspect was most likely hosting the DarkComet server on his home computer.

Because of this operational security (OpSec) mistake, tracking the suspect’s real-world identity was most likely a piece of cake for Ukrainian police, who only needed to send a formal request to the ISP to get the man’s real name and home address.

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Key Criteria for Evaluating a Distributed Denial of Service (DDoS) Solution



Although ransomware is making all the headlines today, it’s not the only kind of attack that can intrude between you and your customers. Distributed denial of service (DDoS) attacks, in which a target website is overwhelmed with spurious traffic, have become increasingly common.

Websites and online applications have become critical to how businesses communicate with their customers and partners. If those websites and applications are not available, there is a dollars and cents cost for businesses, both directly in business that is lost and indirectly through loss of reputation. It doesn’t matter to the users of the website whether the attacker has a political point to make, wants to hurt their victim financially, or is motivated by ego—if the website is unavailable, users will not be happy. Recent DDoS attacks have utilized thousands of compromised computers and they can involve hundreds of gigabits per second of attack bandwidth. A DDoS protection platform must inspect all of the traffic destined for the protected site and discard or absorb all of the hostile traffic while allowing legitimate traffic to reach the site.

Often the attack simply aims vast amounts of network traffic at the operating system under the application. These “volumetric” attacks usually occur at network Layer 3 or 4 and originate from compromised computers called bots. Few companies have enough internet bandwidth to mitigate this much of an attack on-premises, so DDoS protection needs to be distributed to multiple data centers around the world to be effective against these massive attacks. The sheer scale of infrastructure required means that most DDoS platforms are multi-tenant cloud services.

Other attacks target the application itself, at Layer 7, with either a barrage of legitimate requests or with requests carefully crafted to exploit faults in the site. These Layer 7 attacks look superficially like real requests and require careful analysis to separate them from legitimate traffic.

Attackers do not stand still. As DDoS protection platforms learn to protect against one attack method, attackers will find a new method to take down a website. So DDoS protection vendors don’t stand still either. Using information gathered from observing all of their protected sites, vendors are able to develop new techniques to protect their clients.

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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Cloud Data Security



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



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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