Python Infostealer Patching Windows Exodus App, (Wed, Sep 18th)

A few months ago, I wrote a diary[1] about a Python script that replaced the Exodus[2] Wallet app with a rogue one on macOS. Infostealers are everywhere these days. They target mainly browsers (cookies, credentials) and classic applications that may handle sensitive information. Cryptocurrency wallets are another category of applications that are juicy for attackers. I spotted again an interesting malware that mimics an Exodus wallet by displaying a small GUI:

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23:59, Time to Exfiltrate!, (Tue, Sep 17th)

Last week, I posted a diary about suspicious Python modules. One of them was Firebase [1], the cloud service provided by Google[2]. Firebase services abused by attackers is not new, usually, it’s used to host malicious files that will be available to download[3]. This is a nice location because who will think that a Google link is malicious?

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Managing PE Files With Overlays, (Mon, Sep 16th)

There is a common technique used by attackers: They append some data at the end of files (this is called an overlay). This can be used for two main reasons: To hide the appended data from the operating system (steganography). By example, you can append a text file at the end of a JPEG image. When your favourite image viewer will process the picture, it will just ignore the “rogue” data. Here is a PNG picture that has a text file (dir output) added at the end:

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Finding Honeypot Data Clusters Using DBSCAN: Part 2, (Fri, Sep 13th)

In an earlier diary [1], I reviewed how using tools like DBSCAN [2] can be useful to group similar data. I used DBSCAN to try and group similar commands submitted to Cowrie [3] and URL paths submitted to the DShield web honeypot [4]. DBSCAN was very helpful to group similar commands, but it was also very useful when trying to determine whether commands from one honeypot were seen in another. How much overlap in attack data is there between honeypots? Is there any targeting based on the hosting location of the honeypot?

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