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sandfly-entropyscan is a utility to quickly scan files or running processes and report on their entropy (measure of randomness) and if they are a Linux/Unix ELF type executable. Some malware for Linux is packed or encrypted and shows very high entropy. This tool can quickly find high entropy executable files and processes which often are malicious.
Entropy is a measure of randomness. For binary data 0.0 is not-random and 8.0 is perfectly random. Good crypto looks like random white noise and will be near 8.0. Good compression removes redundant data making it appear more random than if it was uncompressed and usually will be 7.7 or above.
A lot of malware executables are packed to avoid detection and make reverse engineering harder. Most standard Linux binaries are not packed because they aren't trying to hide what they are. Searching for high entropy files is a good way to find programs that could be malicious just by having these two attributes of high entropy and executable.
Usage of sandfly-entropyscan:
-csv output results in CSV format (filename, path, entropy, elf_file [true|false], MD5, SHA1, SHA256, SHA512)
-delim change the default delimiter for CSV files of "," to one of your choosing ("|", etc.)
-dir string directory name to analyze
-file string full path to a single file to analyze
-proc check running processes (defaults to ELF only check)
-elf only check ELF executables
-entropy float show any file/process with entropy greater than or equal to this value (0.0 min - 8.0 max, defaults 0 to show all files)
-version show version and exit
Search for any file that is executable under /tmp:
sandfly-entropyscan -dir /tmp -elf
Search for high entropy (7.7 and higher) executables (often packed or encrypted) under /var/www:
sandfly-entropyscan -dir /var/www -elf -entropy 7.7
Generates entropy and cryptographic hashes of all running processes in CSV format:
sandfly-entropyscan -proc -csv
Search for any process with an entropy higher than 7.7 indicating it is likely packed or encrypted:
sandfly-entropyscan -proc -entropy 7.7
Generate entropy and cryptographic hash values of all files under /bin and output to CSV format (for instance to save and compare hashes):
sandfly-entropyscan -dir /bin -csv
Scan a directory for all files (ELF or not) with entropy greater than 7.7: (potentially large list of files that are compressed, png, jpg, object files, etc.)
sandfly-entropyscan -dir /path/to/dir -entropy 7.7
Quickly check a file and generate entropy, cryptographic hashes and show if it is executable:
sandfly-entropyscan -file /dev/shm/suspicious_file
Do spot checks on systems you think have a malware issue. Or you can automate the scan so you will get an output if we find something show up that is high entropy in a place you didn't expect. Or simply flag any executable ELF type file that is somewhere strange (e.g. hanging out in /tmp or under a user's HTML directory). For instance:
Did a high entropy binary show up under the system /var/www directory? Could be someone put a malware dropper on your website:
sandfly-entropyscan -dir /var/www -elf -entropy 7.7
Setup a cron task to scan your /tmp, /var/tmp, and /dev/shm directories for any kind of executable file whether it's high entropy or not. Executable files under tmp directories can frequently be a malware dropper.
sandfly-entropyscan -dir /tmp -elf
sandfly-entropyscan -dir /var/tmp -elf
sandfly-entropyscan -dir /dev/shm -elf
Setup another cron or automated security sweep to spot check your systems for highly compressed or encrypted binaries that are running:
sandfly-entropyscan -proc -entropy 7.7
git clone https://github.com/sandflysecurity/sandfly-entropyscan.git
go build
./sandfly-entropyscan
There are a some basic build scripts that build for various platforms. You can use these to build or modify to suit. For Incident Responders, it might be useful to keep pre-compiled binaries ready to go on your investigation box.
build.sh - Build for current OS you're running on when you execute it.
We use a simple method for seeing if a file may be an executable ELF type. We can spot ELF format files for multiple platforms. Even if malware has Intel/AMD, MIPS and Arm dropper binaries we will still be able to spot all of them.
It's possible to flag a legitimate binary that has a high entropy because of how it was compiled, or because it was packed for legitimate reasons. Other files like .zip, .gz, .png, .jpg and such also have very high entropy because they are compressed formats. Compression removes redundancy in a file which makes it appear to be more random and has higher entropy.
On Linux, you may find some kinds of libraries (.so files) get flagged if you scan library directories.
However, it is our experience that executable binaries that also have high entropy are often malicious. This is especially true if you find them in areas where executables normally shouldn't be (such as again tmp or html directories).
The entropy calculation requires reading in all the bytes of the file and tallying them up to get a final number. It can use a lot of CPU and disk I/O, especially on very large file systems or very large files. The program has an internal limit where it won't calculate entropy on any file over 2GB, nor will it try to calculate entropy on any file that is not a regular file type (e.g. won't try to calculate entropy on devices like /dev/zero).
Then we calculate MD5, SHA1, SHA256 and SHA512 hashes. Each of these requires going over the file as well. It's reasonable speed on modern systems, but if you are crawling a very large file system it can take some time to complete.
If you tell the program to only look at ELF files, then the entropy/hash calculations won't happen unless it is an ELF type and this will save a lot of time (e.g. it will ignore massive database files that aren't executable).
If you want to automate this program, it's best to not have it crawl the entire root file system unless you want that specifically. A targeted approach will be faster and more useful for spot checks. Also, use the ELF flag as that will drastically reduce search times by only processing executable file types.
For incident responders, running sandfly-entropyscan against the entire top-level "/" directory may be a good idea just to quickly get a list of likely packed candidates to investigate. This will spike CPU and disk I/O. However, you probably don't care at that point since the box has been mining cryptocurrency for 598 hours anyway by the time the admins noticed.
Again, use the ELF flag to get to the likely problem candidate executables and ignore the noise.
There is a script called scripts/testfiles.sh that will make two files. One will be full of random data and one will not be random at all. When you run the script it will make the files and run sandfly-entropyscan in executable detection mode. You should see two files. One with very high entropy (at or near 8.0) and one full of non-random data that should be at 0.00 for low entropy. Example:
./testfiles.sh
Creating high entropy random executable-like file in current directory.
Creating low entropy executable-like file in current directory.
high.entropy.test, entropy: 8.00, elf: true
low.entropy.test, entropy: 0.00, elf: true
You can also load up the upx utility and compress an executable and see what values it returns.
Sandfly Security produces an agentless endpoint detection and incident response platform (EDR) for Linux. Automated entropy checks are just one of thousands of things we search for to find intruders without loading any software on your Linux endpoints.
Get a free license and learn more below:
https://www.sandflysecurity.com @SandflySecurity
With this application, it is aimed to accelerate the incident response processes by collecting information in linux operating systems.
Information is collected in the following contents.
/etc/passwd
cat /etc/group
cat /etc/sudoers
lastlog
cat /var/log/auth.log
uptime/proc/meminfo
ps aux
/etc/resolv.conf
/etc/hosts
iptables -L -v -n
find / -type f -size +512k -exec ls -lh {}/;
find / -mtime -1 -ls
ip a
netstat -nap
arp -a
echo $PATH
git clone https://github.com/anil-yelken/pylirt
cd pylirt
sudo pip3 install paramiko
The following information should be specified in the cred_list.txt file:
IP|Username|Password
sudo python3 plirt.py
https://twitter.com/anilyelken06
https://medium.com/@anilyelken
With this application, it is aimed to accelerate the incident response processes by collecting information in windows operating systems via winrm.
Information is collected in the following contents.
IP Configuration
Users
Groups
Tasks
Services
Task Scheduler
Registry Control
Active TCP & UDP ports
File sharing
Files
Firewall Config
Sessions with other Systems
Open Sessions
Log Entries
git clone https://github.com/anil-yelken/pywirt
cd pywirt
pip3 install pywinrm
The following information should be specified in the cred_list.txt file:
IP|Username|Password
https://twitter.com/anilyelken06
https://medium.com/@anilyelken
Today we’re examining some of the revelations in the Q3 Cisco Talos Incident Response Trends Report. This document is an anonymized look at of all the engagements that the Cisco Talos Incident Response team have been involved in over the previous three months. It also features threat intelligence from our team of researchers and analysts.
To start, take a watch of this episode of ThreatWise TV which explores how these trends have evolved since the previous quarter. Our guests also talk about incidents and cyber-attacks that they themselves have consulted on recently, including a particularly interesting insider threat case.
Ransomware returned as the top threat this quarter, after commodity trojans narrowly surpassed ransomware last quarter. Ransomware made up nearly 18 percent of all threats observed, up from 15 percent last quarter. Cisco Talos Incident Response (CTIR) observed high-profile families, such as Vice Society and Hive, as well as the newer family Blast Basta, which first emerged in April of this year.
Also noteworthy is the fact that CTIR saw an equal number in ransomware and pre- ransomware engagements this quarter, totalling nearly 40 percent of threats observed. Pre-ransomware is when we have observed a ransomware attack is about to happen, but the encryption of files has not yet taken place.
Pre-ransomware comprised 18 percent of threats this quarter, up from less than 5 percent previously. While it’s difficult to determine an adversary’s motivations if encryption does not take place, several behavioral characteristics bolster Talos’ confidence that ransomware may likely be the final objective. In these engagements adversaries were observed deploying frameworks such as Cobalt Strike and Mimikatz, alongside numerous enumeration and discovery techniques.
Commodity malware, such as the Qakbot banking trojan, was observed in multiple engagements this quarter. In one engagement, several compromised endpoints were seen communicating with IP addresses associated with Qakbot C2 traffic. This activity coincides with a general resurgence of Qakbot and its delivery of emerging ransomware families and offensive security frameworks that we have not previously observed Qakbot deploy. This comes at a time where competing email-based botnets like Emotet and Trickbot have suffered continued setbacks from law enforcement and tech companies.
Other threats this quarter include infostealers like Redline Stealer and Raccoon Stealer. Redline Stealer was observed across three engagements this quarter, two of which involved ransomware. The malware operators behind Raccoon introduced new functionality to the malware at the end of June, which likely contributed to its increased presence in engagements this quarter.
As infostealers have continued to rank highly in CTIR engagements, let’s explore them in a bit more detail.
Throughout the incidents discussed over the last few quarters, and CTIR engagements in general, information stealing plays a big part of the attackers’ TTPs.
From a high level, infostealers can be used to gain access a variety of sensitive information, such as contact information, financial details, and even intellectual property. The adversaries involved often proceed to exfiltrate this information and may then attempt to sell it in dark web forums, threaten to release it if a ransom isn’t paid, among other things.
While these instances can and do crop up in CTIR engagements, many of the infostealers seen in this space are used for accessing and collecting user credentials. Once an attacker has gained an initial foothold on a system, there are many places within an operating system that they can look for and collect credentials through the practice of credential dumping.
These stolen credentials may be offered up for sale on the dark web, alongside the stolen information mentioned above, but they can also prove to be a key weapon in an attacker’s arsenal. Their usefulness lies in one simple concept—why force your way into a system when you can just log in?
There are several advantages for bad actors that use this approach. Probably the most oblivious of these is that using pre-existing credentials is far more likely to go unnoticed than other more flagrant tactics an attacker can use. If part of the goal of an attack is to remain under the radar, activities carried out by “known users” are less likely to trigger security alerts when compared to tactics such as exploiting vulnerabilities or downloading malware binaries.
Adversaries tend to seek credentials with higher privileges, allowing them further control over the systems they compromise, with those including administrative access being the crown jewels.
User credentials can not only provide an attacker with means to elevate privileges and establish persistence on a system, but also to move laterally through a network. Some credentials, especially those with administrative privileges, can offer access to multiple systems throughout a network. By obtaining them, many more options become available to further an attack.
There are several threats involved in information stealing that appear repeatedly in CTIR engagements over the last few quarters.
Perhaps the most notorious is Mimikatz—a tool used to pull credentials from operating systems. Mimikatz is not malware per-se and can be useful for penetration testing and red team activities. But bad actors leverage it as well, and over the last few quarters CTIR has observed it being used in ransomware-as-a-service attacks, as well as pre-ransomware incidents.
CTIR has also observed Redline Stealer being utilized by adversaries in CTIR engagements across quarters. This infostealer has grown in popularity as a supplementary tool used alongside other malware. On more than one occasion, CTIR has identified stolen credentials on the dark web that claimed to have been obtained via Redline Stealer.
Other information stealers seen across the last few quarters include the Vidar information stealer, Raccoon Stealer, and SolarMaker, all of which have been used to further an adversary’s attacks.
Over the last several months, Talos has seen an increasing number of engagements involving insider threats. In one engagement this quarter, passwords were reset through a management console of a perimeter firewall that a disgruntled employee had access to.
The organization’s team changed all associated passwords but overlooked one administrative account. On the following day, someone logged in using that account, deleted all other accounts and firewall rules, and created one local account, likely to provide persistence.
You’ll hear Alexis Merritt, Incident Response Consultant for Cisco Talos, talk about this more in the ThreatWise TV episode.
To help protect against this threat when an individual leaves an organization, steps like disabling accounts and ensuring that connections to the enterprise remotely through VPN has been removed can be very valuable. Implementing a mechanism to wipe systems, especially for remote employees, is important as well.
For more on this topic, Cisco Secure recently put together a white paper on the Insider Threat Maturity FrameWork.
In several incidents over the last few quarters that involved information stealers, multi-factor authentication (MFA) was not properly implemented by the organizations impacted, providing adversaries an opportunity to infiltrate the networks. MFA tools like Cisco Secure Access by Duo can prevent attackers from successfully gaining access.
And finally, Cisco Advisory CISO Wolfgang Goerlich has created this storytelling video, to help people think about incident response in a new way:
Join the Cisco Talos Incident Response team for a live debrief of the Q3 report on 27th October.
We’d love to hear what you think. Ask a Question, Comment Below, and Stay Connected with Cisco Secure on social!
Cisco Secure Social Channels
ShoMon is a Shodan alert feeder for TheHive written in GoLang. With version 2.0, it is more powerful than ever!
Can be used as Webhook OR Stream listener
Utilizes shadowscatcher/shodan (fantastic work) for Shodan interaction.
Console logs are in JSON format and can be ingested by any other further log management tools
CI/CD via Github Actions ensures that a proper Release with changelogs, artifacts, images on ghcr and dockerhub will be provided
Provides a working docker-compose file file for TheHive, dependencies
Super fast and Super mini in size
Complete code refactoring in v2.0 resulted in more modular, maintainable code
Via conf file or environment variables alert specifics including tags, type, alert-template can be dynamically adjusted. See config file.
Full banner can be included in Alert with direct link to Shodan Finding.
IP is added to observables
Parameters should be provided via conf.yaml or environment variables. Please see config file and docker-compose file
After conf or environment variables are set simply issue command:
./shomon
FreshRSS 
go build . go build -ldflags="-s -w" . could be used to customize compilation and produce smaller binary.docker pull ghcr.io/kaansk/shomondocker pull kaansk/shomondocker build -t shomon .docker run -it shomondocker-compose run -d
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PersistenceSniper is a Powershell script that can be used by Blue Teams, Incident Responders and System Administrators to hunt persistences implanted in Windows machines. The script is also available on Powershell Gallery. |
Why writing such a tool, you might ask. Well, for starters, I tried looking around and I did not find a tool which suited my particular use case, which was looking for known persistence techniques, automatically, across multiple machines, while also being able to quickly and easily parse and compare results. Sure, Sysinternals' Autoruns is an amazing tool and it's definitely worth using, but, given it outputs results in non-standard formats and can't be run remotely unless you do some shenanigans with its command line equivalent, I did not find it a good fit for me. Plus, some of the techniques I implemented so far in PersistenceSniper have not been implemented into Autoruns yet, as far as I know. Anyway, if what you need is an easy to use, GUI based tool with lots of already implemented features, Autoruns is the way to go, otherwise let PersistenceSniper have a shot, it won't miss it :)
Using PersistenceSniper is as simple as:
PS C:\> git clone https://github.com/last-byte/PersistenceSniper
PS C:\> Import-Module .\PersistenceSniper\PersistenceSniper\PersistenceSniper.psd1
PS C:\> Find-AllPersistence
If you need a detailed explanation of how to use the tool or which parameters are available and how they work, PersistenceSniper's Find-AllPersistence supports Powershell's help features, so you can get detailed, updated help by using the following command after importing the module:
Get-Help -Name Find-AllPersistence -Full
PersistenceSniper's Find-AllPersistence returns an array of objects of type PSCustomObject with the following properties:
PS C:\> Find-AllPersistence | Where-Object "Access Gained" -EQ "System"
Of course, being PersistenceSniper a Powershell-based tool, some cool tricks can be performed, like passing its output to Out-GridView in order to have a GUI-based table to interact with.
As already introduced, Find-AllPersistence outputs an array of Powershell Custom Objects. Each object has the following properties, which can be used to filter, sort and better understand the different techniques the function looks for:
Find-AllPersistence without a -ComputerName parameter, PersistenceSniper will run only on the local machine. Otherwise it will run on the remote computer(s) you specify;Let's face it, hunting for persistence techniques also comes with having to deal with a lot of false positives. This happens because, while some techniques are almost never legimately used, many indeed are by legit software which needs to autorun on system boot or user login.
This poses a challenge, which in many environments can be tackled by creating a CSV file containing known false positives. If your organization deploys systems using something like a golden image, you can run PersistenceSniper on a system you just created, get a CSV of the results and use it to filter out results on other machines. This approach comes with the following benefits:
Find-AllPersistence comes with parameters allowing direct output of the findings to a CSV file, while also being able to take a CSV file as input and diffing the results.
PS C:\> Find-AllPersistence -DiffCSV false_positives.csv
One cool way to use PersistenceSniper my mate Riccardo suggested is to use it in an incremental way: you could setup a Scheduled Task which runs every X hours, takes in the output of the previous iteration through the -DiffCSV parameter and outputs the results to a new CSV. By keeping track of the incremental changes, you should be able to spot within a reasonably small time frame new persistences implanted on the machine you are monitoring.
The topic of persistence, especially on Windows machines, is one of those which see new discoveries basically every other week. Given the sheer amount of persistence techniques found so far by researchers, I am still in the process of implementing them. So far the following 31 techniques have been implemented successfully:
The techniques implemented in this script have already been published by skilled researchers around the globe, so it's right to give credit where credit's due. This project wouldn't be around if it weren't for:
I'd also like to give credits to my fellow mates at @APTortellini, in particular Riccardo Ancarani, for the flood of ideas that helped it grow from a puny text-oriented script to a full-fledged Powershell tool.
This project is under the CC0 1.0 Universal license. TL;DR: you can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.
