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The Python Exe Extractor Readme said that this problem could occur and to use the -p flag on the file to fix this issue. After running the script on the file, not only does it append the correct magic number to the file, but it also extracts the python code for me! Now we have a fully functional Python script that we can work with.
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This is simply grabbing the content from the webpage, in our case it is jus grabbing the picture content and returning it. In the main function we use this data to call get_encoded_data. This function uses the Python Image library to convert the weird static image into raw bytes and return it to the main function, which then passes it to load_level2 which then uses the VirtualAlloc function to create space for these raw bytes. It then moves those bytes into memory and runs it as a function. We can use a Python script to decode these raw bytes the same way the challenge does and output them to a file.
Nice, now Stage 3 requires us to guess an RGB value to get the flag. This consists of three values ranging from 0 to 255. If we were to bruteforce it, that would be 16,581,375 possible combinations. Assuming we can perform 255 guesses per second that would still be around 18 hours to crack the code. I do not have that long to wait, so we can jump into the Python code and see what is in store for us there. The function we will need to analyze is the decode_pasted function.
This function gets the handle of actxprxy.dll and uses that handle to generate a base64 encoded, zlib compressed string. Now we could figure out this string by hand, but I decided to change the python script to print it out for me at this function. The outputted value is this:
I then developed a script that would xor each of these values by the values in the range 0x20-0x7E. This gave me a smaller list of combinations that could be used to xor the data into printable characters. I then outputted all of these to a file along with the integer equivalent of these combinations, so I could grep through it easily and find something that looked like Python code. The code for this is as follows:
A malvertising campaign used a copycat website for anti-malware software provider Malwarebytes to distribute the Raccoon infostealer. Malwarebytes learned of the campaign when someone notified the security firm that someone was abusing its brand using the lookalike domain "malwarebytes-free[.]com." Registered on March 29 via REGISTRAR OF DOMAIN NAMES REG.RU LLC, this domain was hosted in Russia at 173.192.139[.]27 at the time of discovery. Researchers at Malwarebytes subsequently examined the source code of the fake website. Through these efforts, they confirmed that someone had stolen the source code of the firm's website. Those actors had then injected a JavaScript snipped into this code that specifically redirected visitors using Internet Explorer to a malicious URL hosting the Fallout exploit kit.
The fake Malwarebytes website and a view of the code used to redirect visitors to Fallout EK (Source: Malwarebytes) The Fallout exploit code isn't new to the security community. Back in October 2018, for instance, researchers observed that Fallout had become a new distribution method for Kraken ransomware. In this newest campaign, Fallout launched samples of the Raccoon infostealer on a victim's machine. The threat intelligence team at Malwarebytes posited that the individuals behind this campaign could have been some of the same malicious actors whom they've been tracking for months. The security firm observed that some of those attackers had even created other lookalike websites to serve as malvertising gates. With that said, the anti-malware provider admitted in its research that it didn't know how it should respond to attackers using a lookalike website:
Once you have created your Malwarebytes account using your unique offer code, you will be presented with your licence key. You can follow the below guides on how to download and install Malwarebytes Premium, depending on your device;
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We systematically study code reuse as well as functional commonalities between all the samples used in different stages of the previously reported attacks (i.e., packers, downloaders, and RAT payloads). We have also found that while the tools fall into the mentioned families, there are different variants of the tools which have been deployed in the reported attacks. For the RAT payloads, we have found three versions with distinct capabilities. For the downloaders we have found two versions, one with and the other without persistence capabilities.
There are several other functions (i.e., 0x140001bf0, 0x140002030, 0x140002860) that appear in 27 or 26 samples. From the table, we can establish that the packed samples are clearly related. All of them have two functions in common and there are various subsets of the samples that feature substantial code reuse.
We could also confirm the presence of junk code to avoid detection technologies. Figure 4 shows the same function decrypt_payload() in two different samples. We can see junk functions like GetFontUnicodeRanges(), GetSysColorBrush() and CreateBitMap() which are called but whose return values are not being used. In the figure, the effective unpacking code, which in this case is the XOR decryption algorithm, is contained within the green boxes shown.
Additionally, we found that all packer variants follow the same common packing scheme, whereas the variants of the scheme are determined by two parameters. One parameter is whether or not the packed payload is Base64 encoded, the other is where the packed payload is stored within a PE file.
In this section, we will establish through code reuse analysis that all the unpacked binaries fall into a downloader or RAT family. We are calling these families the TigerDownloader and TigerRAT malware family. These names were introduced in the KrCERT report to refer to the downloader and RAT components in their investigation.
In this section, we take a closer look at the two downloader variants: Downloader-Malwarebytes-x64 and Downloader-Kaspersky-x64. From the cluster and code reuse analysis (see Figure 8) we know that they share 97% of code and thus are minor variants of the TigerDownloader family.
We recall from the code reuse and cluster analysis (see Figure 8) that we could connect all RATs to the same TigerRAT family through code-reuse analysis. We have also seen that there are RAT variants that differ more substantially than the downloader variants. For instance, the variants RAT-Kaspersky-x64 and RAT-KrCERT-x64 share only about 50% of their code.
Our analysis revealed new evidence and insights enabling us to attribute the previously reported Andariel APT binaries by Malwarebytes, Kaspersky and KrCERT to two new malware families. We call these the TigerDownloader and TigerRAT families, using names originally introduced by KrCERT. We have also seen that all the binaries are related by the same packing scheme. Our results are based on both automated code-reuse analysis and manual analysis of the malware tooling reported in the previous reports.
At the core of Threatray are highly scalable code similarity search algorithms that find code reuse between a new and millions of known samples in seconds. Our core search algorithms do not make use of traditional byte pattern matches and are thus highly resilient to code mutations.
Some Windows users are encountering the error code 403 (The usage level has exceeded the max volume allowed) when trying to install and activate Malwarebytes on a fresh installation of Windows. This issue is mostly reported to occur with PC configurations that have new motherboards.
Several affected users that were dealing with this issue have reported that the error code 403 was resolved entirely after they have uninstalled the current version of Malwarebytes and installed the latest available build from the official channels.
A 403 error code is almost always related to an activation or reactivation count, most commonly due to an exceeded or fixed preset limit. According to most affected users, this will occur regardless of casualization and will require some degree of manual intervention from a support agent in order to be resolved.
A spear-phishing attack operated by a North Korean threat actor targeting its southern counterpart has been found to conceal its malicious code within a bitmap (.BMP) image file to drop a remote access trojan (RAT) capable of stealing sensitive information.
"The dropped payload was a loader that decoded and decrypted the second stage payload into memory. The second stage payload has the capability to receive and execute commands/shellcode as well as perform exfiltration and communications to a command and control server."
Created on March 31, 2021, the lure document (in Korean) purports to be a participation application form for a fair in one of the South Korean cities and prompts users to enable macros upon opening it for the first time, only to execute the attack code that triggers the infection chain, ultimately dropping an executable called "AppStore.exe."
The payload then proceeds to extract an encrypted second-stage payload appended to itself that's decoded and decrypted at run time, followed by establishing communications with a remote server to receive additional commands and transmit the results of those commands back to the server. 589ccfa754
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