Bitcoin mining trojan source code

These attacks often work by getting a victim to click a malicious link in an email that then loads crypto mining code onto their computer - or by infecting an online ad with JavaScript code that executes through a browser. There is no doubt, however, that the practice is widespread. This rapid growth is due partly to the fact that cryptojacking relies on techniques developed to facilitate a much older form of attack: botnets. Indeed, some cryptojacking mechanisms make explicit use of botnets. The rise in cryptojacking is being driven by how easy it is to implement.

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WATCH RELATED VIDEO: Best Bitcoin Mining Software for FREE / LEGIT AND WORK 2021

GitHub Actions being actively abused to mine cryptocurrency on GitHub servers

The complexity of the modern software development process and its reliance on large community-maintained codebases introduces a risk for developers to inadvertently include malicious code into the project. The implications can be severe: in many cases, it can mean a complete takeover of the developed program or device by an attacker. Attackers attempt to generate this scenario in several ways, among them trying to introduce malicious or vulnerable code into open-source projects and using Typosquatting — adding malicious code into software repositories such as PyPI and npm under names which could be included in a project by mistake such as misspelled names of legitimate software packages.

In this blog post, we present our own additional research done on top of a novel detection by Sonatype, where a few PyPI packages were detected as malicious packages, packing a crypto-miner payload that mines Ethereum or Ubiq for the attacker. The typosquatting attack flow of the malicious published packages can be summarized in the following way:.

This can then further be used for Phishing and code injection attacks. The practice applies to many different resources, such as web pages, software package names, and even executable names.

For example, in this previous attack, a malicious npm package provided colorful logging features for the console, along with a hidden credential stealer. From a high-level perspective, it operates similarly — namely downloading the T-Rex crypto miner from its GitHub repository and running it, but there are a couple of differences:. Additionally, the obfuscation technique used here is a bit more sophisticated, and all arithmetic operations are replaced with lambdas:. The code also periodically connects to one of these popular URLs, probably to check for network connectivity:.

The dropper is specifically a shell script named aza. As we can see, the dropper just downloads and executes a crypto miner, in this case PhoenixMiner, and sends the results to a hardcoded Kryptex wallet. No obfuscation efforts were made here, and this shell script is also something that can be easily detected, if only due to the use of a well-known crypto miner tool.

The attackers used obfuscation to protect the malicious logic from manual analysis and automated static analyzers. The code may appear highly obfuscated at first — the first lines of code are gibberish, including base64 strings and arithmetic operations —. The rest of the code is a lot clearer, but still challenging to read:. As we can see from the figure above, the attackers based the obfuscation mainly on string encryption. The obfuscation can be easily reversed by printing out the output of the function in the interpreter.

This can be done, for example, by grepping for all invocations of the obfuscator function and wrapping them with print … and then re-running inside a safe environment ex. After automating this task through a suitable script, we will get the actual malicious code, which in this case downloads and executes a shell script seo. In our case, the JFrog security research team formerly Vdoo detected these packages as potentially malicious due to the obfuscation that was used. Specifically, we can see that eval-based obfuscation was used in maratlib and maratlib Coupled with the suitable filters to avoid false positives, the usage of eval is a powerful indicator of malicious activity.

The targeted package necessarily needs to be highly visible: to be located in a widely used repository and be sufficiently widespread. The selected misspelled name should be close enough to the name of the targeted package, which is easy to quantify using well-known metrics Levenshtein or edit distance.

Thus, even from very shallow metadata package names and usage statistics , one can easily find candidates for Typosquatting by selecting packages that have a short edit distance from another popular package. Using this as a first-order filter, one can then study the source code of the suspicious packages either manually or automatically and look for other indicators of malicious behavior, such as network interfaces, use of cryptographic API, or any of the malicious indicators that were previously mentioned.

To prevent Dependency Confusion — Manage the way that repositories are queried and artifacts are pulled when resolving dependencies in the build process, for example by setting up exclusion rules to prevent searches for internal private artifacts in remote repositories, or defining the order in which varied repositories are searched in order to resolve a dependency.

More information is available in our recent blog post. Contact us at research jfrog. In addition to discovering and responsibly disclosing vulnerabilities as part of our day-to-day activities, the JFrog security research team works to enhance software security by empowering organizations to discover vulnerabilities through automated security analysis.

I have read and agreed to the Privacy Policy. You have been redirected to the JFrog website. Blog Home. Reviewers: Shachar Menashe, Sr. Director Security Research Itay Vaknin, Threat Intelligence Researcher The complexity of the modern software development process and its reliance on large community-maintained codebases introduces a risk for developers to inadvertently include malicious code into the project.

The funds are transferred into several mining pools, including: Kryptex 0xaec7fb7deb13eb31b57 Kryptex 0xbaef4a87e8a92adbc5b0a2a02edc Daggerhashimoto. Sign up for blog updates. Get Started. Something went wrong. Click Here. X Vdoo is now part of JFrog helping to deliver secure software updates from code to the edge.

Security 101: The Impact of Cryptocurrency-Mining Malware

F5 threat researchers have discovered a new Linux crypto-miner botnet that is spreading over the SSH protocol. Targeting online Linux systems to construct botnets is a very common attack vector in the wild, especially in the last couple of years with the rise of IoT devices. We recently noticed an interesting crypto-miner botnet that seems to be going under the radar. Based on the Python scripting language, it seems to be spreading silently.

Cryptocurrency Mining Malware Detections from. , courtesy of several inspecting the source code of the webpage, the script below is identified.

Infected with Bitcoin Mining pool zombie??

On 6th December , FortiGuard Labs discovered a compromised website - acenespargc[. Looking into the source code, we noticed a suspicious encrypted script which the uses eval function to convert all the characters into numbers. We used a tool called CharCode Translator to reverse the numbers back into characters. We were then able to retrieve a link which redirects to a scam page or phishing website. The above is just a simple example. The threat actor can actually customize the phishing content by geographical location, and to better avoid detection, it will also disappear when it detects that you have visited the phishing page before. On the 28th of December, FortiGuard Labs learned about another malicious website using the very obfuscation technique we described above — romance-fire[. This website contained obscured malicious code for cryptocurrency mining. We uncovered the encoded script, and by using the packer tool to unpack it, we found the script has a connection to CoinHive. Below is the result:.

OSX.CpuMeaner: New Crypto Mining Trojan Targets macOS

bitcoin mining trojan source code

The great deal of money in these currencies has enticed more black market cybercrime groups into joining leagues of malicious cryptocurrency miners. By monitoring botnet families on the cloud, the Alibaba Cloud Security team found that malicious cryptocurrency mining has become the primary profit-making approach for black market cybercrime groups. By the end of August , a total of 58 large-scale cybercrime groups spreading cryptocurrency mining Trojans were detected. In this article, we will be looking at some of the most common technologies and development trends of cryptocurrency mining trojans from a macroscopic perspective to provide enterprises with security protection insights.

Symantec has uncovered a Trojan that appears to be targeting users of Bitcoin, a decentralized P2P-based online currency. Bitcoin consultants, however, downplayed the threat.

How to Tell if you've Been Cryptojacked

The Australian government has just recognized digital currency as a legal payment method. Since July 1, purchases done using digital currencies such as bitcoin are exempt from the country's Goods and Services Tax to avoid double taxation. As such, traders and investors will not be levied taxes for buying and selling them through legal exchange platforms. Japan, which legitimized bitcoin as a form of payment last April, already expects more than 20, merchants to accept bitcoin payments. Other countries are joining the bandwagon, albeit partially: businesses and some of the public organizations in Switzerland, Norway , and the Netherlands.

How To Block Cryptomining Scripts In Your Web Browser

A few hours ago, an npm package with more than 7 million weekly downloads was compromised. Three new versions of this package were released in an attempt to get users to download them. While the previous clean version was 0. This annotated screenshot of registry information shows that around 4 hours elapsed from attack to workaround:. Unfortunately, the malicious code was still available to download from npm for at least three more hours at the time of writing this post. Most malicious packages being uploaded on a daily basis to npm attempt to steal environment keys in a generic way.

2 Extremely aggressive, Sysrv contains a component that hunts for and shuts down other crypto-mining botnets. Key Takeways. A botnet is a piece of malware that.

LemonDuck is a new crypto-mining malware targeting Windows and Linux systems

While far behind Bitcoin in market capitalization, Monero has several features that make it a very attractive cryptocurrency to be mined by malware. While the world is holding its breath, wondering where notorious cybercriminal groups like Lazarus or Telebots will strike next with another destructive malware such as WannaCryptor or Petya, there are many other, less aggressive, much stealthier and often very profitable operations going on. One such operation has been going on since at least May , with attackers infecting unpatched Windows webservers with a malicious cryptocurrency miner. To achieve this, attackers modified legitimate open source Monero mining software and exploited a known vulnerability in Microsoft IIS 6.

Crypto mining on the rise among hackers


Image source: Beware of traps , by Carmen. In this post, we analyze a new cryptocurrency mining trojan targeting macOS. While the idea is similar to OSX. Pwnet , the means and method of implementation are closer to that of the adware industry.

Crypto-currency miners use a lot of resources to optimize the earning of crypto-coins, so users may experience slow computers. This detection means that your machine is being used as such.

February 5, 9 minute read. Cybereason is following an active campaign to deliver an arsenal of malware that is able to steal data, mine for cryptocurrency, and deliver ransomware to victims all over the world. Due to the variety of malware types deployed in this attack, attackers are able to hit victims from all sides and do not have to limit themselves to one attack goal or another. The payloads observed in this campaign originated from different accounts in code repository platform Bitbucket , which was abused as part of the attackers delivery infrastructure. Cybereason reached out to Bitbucket Support and the malicious repositories mentioned in the report were deactivated within a few hours. The flow of the Bitbucket multi-payload attack. This research highlights an ongoing trend with cybercriminals where they abuse legitimate online storage platforms like Github, Dropbox, Google Drive, and Bitbucket to distribute commodity malware.

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  2. Vukinos


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  4. Sterling

    all this is dynamic and very positive