SAN CARLOS, Calif., Jan. 13, 2023 (GLOBE NEWSWIRE) -- Check Point Software Technologies Ltd. (NASDAQ: CHKP), a leading provider of cybersecurity solutions globally, has published its Global Threat Index for December 2022. Last month saw Glupteba Malware, an ambitious blockchain-enabled Trojan botnet, return to the top ten list for the first time since July 2022, moving into eighth place. Qbot, a sophisticated Trojan that steals banking credentials and keystrokes, overtook Emotet to be the most prevalent malware after its return last month, impacting 7% of organizations worldwide. Meanwhile, android malware Hiddad made a comeback, and education continued to be the most impacted industry worldwide.
Yahoo! Spread Bitcoin Mining Botnet Malware Via Ads
Criminals have found a safe haven abusing legitimate processes, such as real-time bidding, implemented by online advertising networks to move exploits and malware, and build botnets and fraud campaigns.
Another ad fraud botnet that has been leveraged by other bigger campaigns, Kovter is still out there. Like other long lasting malware, Kovter has managed to hide itself in longer lines of code, including Windows registry files.
A case in point that click fraud and ad fraud continues to evolve; DrainerBot was a malware botnet embedded in a software development kit (SDK) found in Android devices. This SDK was used to build hundreds or thousands of apps, many of which contained the DrainerBot code.
Fortunately, you can help protect your computer from these botnet attacks. The key is to avoid clicking on suspicious links in emails or visiting websites known to spread viruses. You should also invest in trusted phishing emails and quickly approve any updates to this online protection or adjust your settings to allow automatic updates.
Scammers often send phishing emails to victims, tricking them into clicking on links that infect their computers. You might infect your computer, too, if you visit a website that spreads malware or if you download an infected file.
High-Profile Activity: the U.S. Government assesses that GTsSS cyber actors have deployed Drovorub malware against victim devices as part of their cyber espionage operations.[16] The U.S. Government and UK Government assess that GTsSS actors used a Kubernetes cluster to conduct widespread, distributed, and anonymized brute force access attempts against hundreds of government and private sector targets worldwide.[17]
Overview: SALTY SPIDER is a cybercrime group that develops and operates the Sality botnet. Sality is a polymorphic file infector that was discovered in 2003; since then, it has been replaced by more advanced peer-to-peer (P2P) malware loaders.[35]
Overview: SCULLY SPIDER is a cybercrime group that operates using a malware-as-a-service model; SCULLY SPIDER maintains command and control infrastructure and sells access to their malware and infrastructure to affiliates, who distribute their own malware.[36][37] SCULLY SPIDER develops and operates the DanaBot botnet, which originated primarily as a banking Trojan but expanded beyond banking in 2021 and has since been used to facilitate access for other types of malware, including TrickBot, DoppelDridex, and Zloader. Like Emotet, Danabot effectively functions as an initial access vector for other malware, which can result in ransomware deployment.
For example, malicious programs can be delivered to a computer with a USB drive or spread over the internet with drive-by downloads, which automatically install the program without the user's approval. USBs are particularly popular because they can reduce the chance antivirus software identifies the malware because it sits on external hardware rather than the computer's hard drive.
Fraudulent websites and peer-to-peer file sharing services that pretend to be providing legitimate software is another way to spread malware. Pirated software programs can often install a form of malware too.
More sophisticated malware attacks often feature the use of a command-and-control server that allows attackers to communicate with the infected machine, extract sensitive data and even add the device to a botnet.
Android devices are more commonly infected than iOS devices because Android is a more open platform than iOS. Signs that an Android device is infected include unusual data usage, poor battery life and texts and emails being sent from the device without your knowledge. Similarly, if you receive a text from a colleague that seems suspicious, their device could be infected and trying to spread malware between devices.
One of the most famous malware attacks was the WannaCry ransomware computer worm which spread by exploiting the EternalBlue vulnerability in old versions of the Windows operating system. It remains a cyber risk, despite being patched because organizations still haven't updated their operating systems.
Before the Internet became popular, malware was spread on personal computers by executing programs on floppy disks. The malware, often a virus, would install itself on the computer and run itself whenever the computer was turned on.
In the 1900s, there was a rise in Microsoft Office macro-based malware programs that spread by infected documents and templates. From 2002-07, there was a rise in instant messaging based worms that spread through AOL, AIM, MSN and Yahoo Messenger.
The history of modern viruses begins with the first computer virus, called Elk Cloner. It was discovered on a Mac in 1982 when it started infecting Apple II systems. This virus spread to all floppy disks connected to a system and it was considered the first large-scale computer virus outbreak. This was prior to any Windows PC malware.
Ransomware is one of the most common and most profitable types of malware. It installs itself, encrypts files, and demands a ransom to return data to the user. This financial payout usually comes in the form of bitcoins. Once this is paid, the hackers can give the user their key back to decrypt the data or they can choose to keep the money and the data. The point is you can never know with ransomware, so think before you pay the ransom.
Botnets are very popular in the hacker community. The more bots you collect, the more famous you can become as a hacker. They are also used to spread ransomware. Botnets can spread undetected to millions of devices. They are typically used for DDoS attacks, keylogging, screenshot and webcam access, spreading other types of malware, and sending spam and phishing messages.
Rootkits are typically deployed using Trojans by being fed into applications, kernels, virtual machines, boot records, or firmware. But they can also be spread through malicious downloads, compromised shared devices, malicious attachments, and phishing attacks. Rootkits can also be a hideout for other malware, such as keyloggers.
A computer infected by Trojan malware can also spread it to other computers. A cyber criminal turns the device into a zombie computer, which means they have remote control of it without the user knowing. Hackers can then use the zombie computer to continue sharing malware across a network of devices, known as a botnet.
Finally, a spread of Linux.Encoder.1, an encryption ransomware that managed to infect more than 3,000 websites located on Linux servers, became one of the most notable events in 2015. This Trojan is far from being the first malware for Linux. In August 2014, Doctor Web announced a new Trojan called Trojan.Encoder.737 that was able to encrypt files stored on Synology NAS servers. However, the distribution area of Linux.Encoder.1 has broken all records.
Throughout the whole year, Doctor Web security researchers have been keeping a close watch on several botnets activity created by cybercriminals using different malware. At that, activity of the Win32.Rmnet.12 botnet was gradually decreasing during the year. This dangerous virus consists of several modules and can embed content into loaded webpages, redirect users to the specified websites, and send data entered by a user to the remote servers. Besides, Win32.Rmnet.12 can steal passwords stored by popular FTP clients and execute various commands from cybercriminals. It is also able to replicate itself infecting executable files. Moreover, the virus can spread with the help of scripts written in VBScript and embedded into webpages. Activity of two subnets of the Win32.Rmnet.12 botnet is shown in the graphs below:
Another file virus, Win32.Sector, has been known to security researchers since 2008. Its purpose is to download executable files from a P2P network and run them on a compromised computer. The virus can plant itself into running processes and spread itself infecting files stored on local disks, removable media, and in shared folders. At the beginning of the year, activity of this botnet increased a little. However, by autumn, the tendency to its decrease was registered:
It should be noted that attacks using banking Trojans for Android are popular among virus makers all over the world. In 2015, such Trojans were widely used against Russians and South Koreans. For example, Android.BankBot.65.origin, a dangerous malware program designed to steal money from Russian users, was incorporated in a legitimate online banking application and spread masquerading as an update for the corresponding software on a popular website dedicated to mobile devices. For more details about Android.BankBot.65.origin, refer to the corresponding news article.
The Internet is constantly growing, providing a myriad of new services both legitimate and malicious. Criminals take advantage of the scalable, distributed, and rather easily accessible naming, hosting and routing infrastructures of the Internet. As a result, the battle against malware is raging on multiple fronts: the endpoint, the network perimeter, and the application layer. The need for innovative measures to gain ground against the enemy has never been greater. In this talk, we will present a novel and effective multi-pronged strategy to catch malware at the DNS and IP level, as well as our unique 3D visualization engine. We will describe the detection systems we built, and share several successful war stories about hunting down malware domains and associated rogue IP space.At the DNS level, we will describe original methods for tracking botnets, both fast flux and DGA-based. We use a combination of fast, light-weight graph clustering and DNS traffic analysis techniques and threat intelligence feeds to rapidly detect botnet domain families, identify new live CnC domains and IPs, and mitigate them.At the IP level, classical reputation methods assign "maliciousness" scores to IPs, BGP prefixes, or ASNs by merely counting domains and IPs. Our system takes an unconventional approach that combines two opposite, yet complementary views and leads to more effective predictive detections.On one hand, we abstract away from the ASN view. We build the AS graph and investigate its topology to uncover hotspots of malicious or suspicious activities and then scan our DNS database for new domains hosted on these malicious IP ranges. To confirm certain common patterns in the AS graph and isolate suspicious address space, we will demonstrate novel forensics and investigative methods based on the monitoring of BGP prefix announcements.On the other hand, we drill down to a granularity finer than the BGP prefix. For this, we zero in on re-assigned IP ranges reserved by bad customers within large prefixes to host Exploit kit domains, browlock, and other attack types. We will present various techniques we devised to efficiently discover suspicious reserved ranges and sweep en masse for candidate suspicious IPs.Our system provides actionable intelligence and preemptively detects and blocks malicious IP infrastructures prior to, or immediately after some of them are used to wage malware campaigns, therefore decisively closing the detection gap. During this presentation, we will publicly share some of the tools we built to gather this predictive intelligence.The discussion of these detection engines and "war stories" wouldn't be complete without a visualization engine that adequately displays the use cases and offers a graph navigation and investigation tool.Therefore, in this presentation, we will present and publicly release for the first time our own 3D visualization engine, demonstrating the full process which transforms raw data into stunning 3D visuals. We will also present different techniques used to build and render large graph datasets: Force Directed algorithms accelerated on the GPU using OpenCL, 3D rendering and navigation using OpenGL ES, and GLSL Shaders. Finally, we will present a few scripts and methods used to explore our large networks. Every concept is intended to detect and highlight precise features and will be presented with its corresponding visual representation related to malware detection use cases. 2ff7e9595c
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