Stay protected against Ransomware

Ransomware is here to stay. This is something becoming clearer by the minute. It is a very lucrative business if we judge it by the successful infection effectiveness rate and, to a lesser extent, due to rescue payment rates by the affected parts.

To the already infamous Cryptolocker, CryptoWall, TorrentLocker, TeslaCrypt and others, we have to add the recent HydraCrypt and UmbreCrypt. All of them with slight variations over the previous ones in an attempt to avoid the scarce barriers that Antivirus institutions are introducing, together with some initiatives more or less imaginative, and somewhat effective, in order to identify the activity of this kind of threat.

Recently, the CNI (Spanish National Intelligence Center), through the CCN-CERT, published a Ransomware guide where they had compiled some ransomware variants together with file decrypting tools that different Antivirus companies provided, after disarticulating several criminal networks or after deep analysis of malware samples.

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Yara for Incident Handling: a practical case

Yara is an initiative that’s become more and more popular for incident handling, especially over the last year. This project has been widely spoken about on this and other blogs.

Here I’m going to show you a practical example for using incident handling triggered by ransomware. Over the last months there has been an increase in this type of malware that, in spite of the many warnings from those of us working in security and incident handling, is still having quite a big impact. Fortunately, the most recent incidents of ransomware where I have been involved, the compromise has only affected one user each time, which allowed us to focus more on the scope of the encrypted archives than on identifying the equipment that may have been compromised.

Extension identification

One of the first cases we were involved in was an incident with CTB-Locker. On this occasion, a user reported a message appearing on his desktop informing him that his archives had been encrypted and asking for a ransom to recover them. Once part of the incident had been contained by disconnecting the equipment from the network and identifying it as the only one affected (let’s not go into this here) we went on to determine which archives had been encrypted and which ones could be recovered (we would never recommend paying the ransom).

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Snort’s Reputation Preprocessor

Snort’s reputation preprocessor is not something new; in fact, it appeared in August 2011 in version 2.9.1. Up to that moment, the only way to manage blacklists was to create a rule with the list of IP addresses blacklisted, such as BotCC rules (emerging-botcc.rules).

alert tcp $HOME_NET any -> [,,,,,,,,,,,,,,,,] any (msg:"ET CNC Shadowserver Reported CnC Server TCP (group 1)"; flags:S; 
reference:url,; reference:url,; 
threshold: type limit, track by_src, seconds 3600, count 1; classtype:trojan-activity; 
flowbits:set,ET.Evil; flowbits:set,ET.BotccIP; sid:2404000; rev:3259;)

However, this method has a length restriction and you end up with tens of backlisted IP rules with names such as “ET CNC Shadowserver Reported CnC Server UDP (group 49)” or “ET COMPROMISED Known Compromised or Hostile Host Traffic UDP (group 43)”.

However, that’s not the main problem of this method: the main issue is performance. Taking into account that they are detection rules, packet processing is much more expensive and global performance worsens. When packet throughput is very high and there are many blacklist entries such as Shadowserver,, Malwaredomains… and our own lists, Snort performance becomes a problem and it is necessary to find a better way to manage blacklists. Then it’s time to use this preprocessor.

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Nmap –script http-joomla-brute. Where THC-Hydra doesn’t fit.

During a recent audit I wanted to try the strongness of the passwords used and I tried a simple dictionary attack against the login form of Joomla! just in case there was any account with one of those weak passwords. The form was as follows:... Leer Más

New MFTParser plugin in the alpha version of Volatility

Last week, playing with a forensics challenge left by Jack Crook (@jackcr) in the GCIH LinkedIn group, I upgraded Volatility to version 2.3_alpha. In this challenge, the author had included the RAM dump and the disk timeline of each one of the affected computers, and a capture file of the network traffic. However, reviewing the novelties included in this Alpha version I saw a couple of them quite interesting: mbrparser and mftparser.... Leer Más