Welcome back, aspiring DFIR investigators!

If you’re diving into digital forensics, memory analysis is one of the most exciting and useful skills you can pick up. Essentially, you take a snapshot of what’s happening inside a computer’s brain right at that moment and analyze it. Unlike checking files on a hard drive, which shows what was saved before, memory tells you about live actions. Things like running programs or hidden threats that might disappear when the machine shuts down. This makes it super helpful for solving cyber incidents, especially when bad guys try to cover their tracks.

In this guide, we’re starting with the basics of memory analysis using a tool called Volatility. We’ll cover why it’s so important, how to get started, and some key commands to make you feel confident. This is part one, where we focus on the foundations and give instructions. Stick around for part two, where we’ll keep exploring Volatility and dive into network details, registry keys, files, and scans like malfind and Yara rules. Plus, if you make it through part two, there are some bonuses waiting to help you extract even more insights quickly.

Memory Forensics

Memory analysis captures stuff that disk forensics might miss. For example, after a cyber attack, malware could delete its own files or run without saving anything to the disk at all. That leaves you with nothing to find on the hard drive. But in memory, you can spot remnants like active connections or secret codes. Even law enforcement grabs memory dumps from suspects’ computers before powering them off. Once it’s off, the RAM clears out, and booting back up might be tricky if the hacker sets traps. Hackers often use tricks like USB drives that trigger wipes of sensitive data on shutdown, cleaning everything in seconds so authorities find nothing. We’re not diving into those tricks here, but they show why memory comes first in many investigations.

Lucky for us, Volatility makes working with these memory captures straightforward. It started evolving, and in 2019, Volatility 3 arrived with better syntax and easier to remember commands. We’ll look at both Volatility 2 and 3, sharing commands to get you comfortable. These should cover what most analysts need.

Memory Gems

Below is some valuable data you can find in RAM for investigations:

1. Network connections

2. File handles and open files

3. Open registry keys

4. Running processes on the system

5. Loaded modules

6. Loaded device drivers

7. Command history and console sessions

8. Kernel data structures

9. User and credential information

10. Malware artifacts

11. System configuration

12. Process memory regions

Keep in mind, sometimes key data like encryption keys hides in memory. Memory forensics can pull this out, which might be a game-changer for a case.

Approach to Memory Forensics

In this section we will describe a structured method for conducting memory forensics, designed to support investigations of data in memory. It is based on the six-step process from SANS for analyzing memory.

Identifying and Checking Processes

Start by listing all processes that are currently running. Harmful programs can pretend to be normal ones, often using names that are very similar to trick people. To handle this:

1. List every active process.

2. Find out where each one comes from in the operating system.

3. Compare them to lists of known safe processes.

4. Note any differences or odd names that stand out.

Examining Process Details

After spotting processes that might be problematic, look closely at the related dynamic link libraries (DLLs) and resources they use. Bad software can hide by misusing DLLs. Key steps include:

1. Review the DLLs connected to the questionable process.

2. Look for any that are not approved or seem harmful.

3. Check for evidence of DLLs being inserted or taken over improperly.

Reviewing Network Connections

A lot of malware needs to connect to the internet, such as to contact control servers or send out stolen information. To find these activities:

1. Check the open and closed network links stored in memory.

2. Record any outside IP addresses and related web domains.

3. Figure out what the connection is for and why it’s happening.

4. Confirm if the process is genuine.

5. See if it usually needs network access.

6. Track it back to the process that started it.

7. Judge if its actions make sense.

Finding Code Injection

Skilled attackers may use methods like replacing a process’s code or working in hidden memory areas. To detect this:

1. Apply tools for memory analysis to spot unusual patterns or signs of these tactics.

2. Point out processes that use strange memory locations or act in unexpected ways.

Detecting Rootkits

Attackers often aim for long-term access and hiding. Rootkits bury themselves deep in the system, giving high-level control while staying out of sight. To address them:

1. Search for indicators of rootkit presence or major changes to the OS.

2. Spot any processes or drivers with extra privileges or hidden traits.

Isolating Suspicious Items

Once suspicious processes, drivers, or files are identified, pull them out for further study. This means:

1. Extract the questionable parts from memory.

2. Save them safely for detailed review with forensic software.

The Volatility Framework

A widely recommended option for memory forensics is Volatility. This is a prominent open-source framework used in the field. Its main component is a Python script called Volatility, which relies on various plugins to carefully analyze memory dumps. Since it is built on Python, it can run on any system that supports Python.

Volatility’s modules, also known as plugins, are additional features that expand the framework’s capabilities. They help pull out particular details or carry out targeted examinations on memory files.

Frequently Used Volatility Modules

Here are some modules that are often used:

pslist: Shows the active processes.

cmdline: Reveals the command-line parameters for processes.

netscan: Checks for network links and available ports.

malfind: Looks for possible harmful code added to processes.

handles: Examines open resources.

svcscan: Displays services in Windows.

dlllist: Lists the dynamic-link libraries loaded in a process.

hivelist: Identifies registry hives stored in memory.

You can find documentation on Volatility here:

Volatility v2: https://github.com/volatilityfoundation/volatility/wiki/Command-Reference

Volatility v3: https://volatility3.readthedocs.io/en/latest/index.html

Installation

Installing Volatility 3 is quite easy and will require a separate virtual environment to keep things organized. Create it first before proceeding with the rest:

bash$ > python3 -m venv ~/venvs/vol3

bash$ > source ~/venvs/vol3

Now you are ready to install it:

bash$ > pip install volatility3

Since we are going to cover Yara rules in Part 2, we will need to install some dependencies:

bash$ > sudo apt install -y build-essential pkg-config libtool automake libpcre3-dev libjansson-dev libssl-dev libyara-dev python3-dev

bash$ > pip install yara-python pycryptodome

Yara rules are important and they help you automate half the analysis. There are hundreds of these rules available on Github, so you can download and use them each time you analyze the dump. While these rules can find a lot of things, there is always a chance that malware can fly under the radar, as attackers change tactics and rewrite payloads. 

Now we are ready to work with Volatility 3.

Plugins

Volatility comes with multiple plugins. To list all the available plugins do this:

bash$ > vol -h

Each of these plugins has a separate help menu with a description of what it does.

Memory Analysis Cheat Sheet

Image Information

Imagine you’re an analyst investigating a hacked computer. You start with image information because it tells you basics like the OS version and architecture. This helps Volatility pick the right settings to read the memory dump correctly. Without it, your analysis could go wrong. For example, if a company got hit by ransomware, knowing the exact Windows version from the dump lets you spot if the malware targeted a specific weakness.

In Volatility 2, ‘imageinfo‘ scans for profiles, and ‘kdbgscan‘ digs deeper for kernel debug info if needed. Volatility 3’s ‘windows.info‘ combines this, showing 32/64-bit, OS versions, and kernel details all in one and it’s quicker.

bash$ > vol -f Windows.vmem windows.info

Here’s what the output looks like, showing key system details to guide your next steps.

Process Information

As a beginner analyst, you’d run process commands to list what’s running on the system, like spotting a fake “explorer.exe” that might be malware stealing data. Say you’re checking a bank employee’s machine after a phishing attack, these commands can tell you if suspicious programs are active, and help you trace the breach.

‘pslist‘ shows active processes via kernel structures. ‘psscan‘ scans memory for hidden ones (good for rootkits). ‘pstree‘ displays parent-child relationships like a family tree. ‘psxview‘ in Vol 2 compares lists to find hidden processes.

Note that Volatility 2 wants you to specify the profile. You can find out the profile while gathering the image info.

Volatility 2:

vol.py -f “/path/to/file” ‑‑profile <profile> pslist

vol.py -f “/path/to/file” ‑‑profile <profile> psscan

vol.py -f “/path/to/file” ‑‑profile <profile> pstree

vol.py -f “/path/to/file” ‑‑profile <profile> psxview

Volatility 3:

vol.py -f “/path/to/file” windows.pslist

vol.py -f “/path/to/file” windows.psscan

vol.py -f “/path/to/file” windows.pstree

Now let’s see what we get:

bash$ > vol -f Windows7.vmem windows.pslist

This output lists processes with PIDs, names, and start times. Great for spotting outliers.

bash$ > vol -f Windows.vmem windows.psscan

Here, you’ll see a broader scan that might catch processes trying to hide.

bash$ > vol -f Windows7.vmem windows.pstree

This tree view helps trace how processes relate, like if a browser spawned something shady.

Displaying the entire process tree will look messy, so we recommend a more targeted approach with –pid

Process Dump

You’d use process dump when you spot a suspicious process and want to extract its executable for closer inspection, like with antivirus tools. For instance, if you’re analyzing a system after a data leak, dumping a weird process could reveal it is spyware sending info to hackers.

Vol 2’s ‘procdump‘ pulls the exe for a PID. Vol 3’s ‘dumpfiles‘ grabs the exe plus related DLLs, giving more context.

Volatility 2:

vol.py -f “/path/to/file” ‑‑profile <profile> procdump -p <PID> ‑‑dump-dir=“/path/to/dir”

Volatility 3:

vol.py -f “/path/to/file” -o “/path/to/dir” windows.dumpfiles ‑‑pid <PID>

We already have a process we are interested in:

bash$ > vol -f Windows.vmem windows.dumpfiles --pid 504

After the dump, check the output and analyze it further.

Memdump

Memdump is key for pulling the full memory of a process, which might hold passwords or code snippets. Imagine investigating insider theft, dumping memory from an email app could show unsent drafts with stolen data.

Vol 2’s ‘memdump’ extracts raw memory for a PID. Vol 3’s ‘memmap’ with –dump maps and dumps regions, useful for detailed forensics.

Volatility 2:

vol.py -f “/path/to/file” ‑‑profile <profile> memdump -p <PID> ‑‑dump-dir=“/path/to/dir”

Volatility 3:

vol.py -f “/path/to/file” -o “/path/to/dir” windows.memmap ‑‑dump ‑‑pid <PID>

Let’s see the output for our process:

bash$ > vol -f Windows7.vmem windows.memmap --dump --pid 504

This shows the memory map and dumps files for deep dives.

DLLs

Listing DLLs helps spot injected code, like malware hiding in legit processes. Unusual DLLs might point to infection.

Both versions list loaded DLLs for a PID, but Vol 3 is profile-free and faster.

Volatility 2:

vol.py -f “/path/to/file” ‑‑profile <profile> dlllist -p <PID>

Volatility 3:

vol.py -f “/path/to/file” windows.dlllist ‑‑pid <PID>

Let’s see the DLLs loaded in our memory dump:

bash$ > vol -f Windows7.vmem windows.dlllist --pid 504

Here you see all loaded DLLs of this process. You already know how to dump processes with their DLLs for a more thorough analysis. 

Handles

Handles show what a process is accessing, like files or keys crucial for seeing if malware is tampering with system parts. In a ransomware case, handles might reveal encrypted files being held open or encryption keys used to encrypt data.

Both commands list handles for a PID. Similar outputs, but Vol 3 is streamlined.

Volatility 2:

vol.py -f “/path/to/file” ‑‑profile <profile> handles -p <PID>

Volatility 3:

vol.py -f “/path/to/file” windows.handles ‑‑pid <PID>

Let’s see the handles our process used:

bash$ > vol -f Windows.vmem windows.handles --pid 504

It gave us details, types and names for clues.

Services

Services scan lists background programs, helping find persistent malware disguised as services. If you’re probing a server breach, this could uncover a backdoor service.

Use | more to page through long lists. Outputs are similar, showing service names and states.

Volatility 2:

vol -f “/path/to/file” ‑‑profile <profile> svcscan | more

Volatility 3:

vol -f “/path/to/file”  windows.svcscan | more

Since this technique is often abused, a lot can be discovered here:

bash$ > vol -f Windows7.vmem windows.svcscan

Give it a closer look and spend enough time here. It’s good to familiarize yourself with native services and their locations

Summary

We’ve covered the essentials of memory analysis with Volatility, from why it’s vital to key commands for processes, dumps, DLLs, handles, and services. Apart from the commands, now you know how to approach memory forensics and what actions you should take. As we progress, more articles will be coming where we practice with different cases. We already have a memory dump of a machine that suffered a ransomware attack, which we analyzed with you recently. In part two, you will build on this knowledge by exploring network info, registry, files, and advanced scans like malfind and Yara rules. And for those who finish part two, some handy bonuses await to speed up your work even more. Stay tuned!

The post Digital Forensics: Volatility – Memory Analysis Guide, Part 1 first appeared on Hackers Arise.

Welcome back, my aspiring SCADA/ICS cyberwarriors!

SCADA (Supervisory Control and Data Acquisition) systems and the wider class of industrial control systems (ICS) run many parts of modern life, such as electricity, water, transport, factories. These systems were originally built to work in closed environments and not to be exposed to the public Internet. Over the last decade they have been connected more and more to corporate networks and remote services to improve efficiency and monitoring. That change has also made them reachable by the same attackers who target regular IT systems. When a SCADA system is hit by malware, sabotage, or human error, operators must restore service fast. At the same time investigators need trustworthy evidence to find out what happened and to support legal, regulatory, or insurance processes.

Forensics techniques from traditional IT are helpful, but they usually do not fit SCADA devices directly. Many field controllers run custom or minimal operating systems, lack detailed logs, and expose few of the standard interfaces that desktop forensics relies on. To address that gap, we are starting a focused, practical 3-day course on SCADA forensics. The course is designed to equip you with hands-on skills for collecting, preserving and analysing evidence from PLCs, RTUs, HMIs and engineering workstations.

Today we will explain how SCADA systems are built, what makes forensics in that space hard, and which practical approaches and tools investigators can use nowadays.

Background and SCADA Architecture

A SCADA environment usually has three main parts: the control center, the network that connects things, and the field devices.

The control center contains servers that run the supervisory applications, databases or historians that store measurement data, and operator screens (human-machine interfaces). These hosts look more like regular IT systems and are usually the easiest place to start a forensic investigation.

The network between control center and field devices is varied. It can include Ethernet, serial links, cellular radios, or specialized industrial buses. Protocols range from simple serial messages to industrial Ethernet and protocol stacks that are unique to vendors. That variety makes it harder to collect and interpret network traffic consistently.

Field devices sit at the edge. They include PLCs (programmable logic controllers), RTUs (remote terminal units), and other embedded controllers that handle sensors and actuators. Many of these devices run stripped-down or proprietary firmware, hold little storage, and are designed to operate continuously.

Understanding these layers helps set realistic expectations for what evidence is available and how to collect it without stopping critical operations.

Challenges in SCADA Forensics

SCADA forensics has specific challenges that change how an investigation is done.

First, some field devices are not built for forensics. They often lack detailed logs, have limited storage, and run proprietary software. That makes it hard to find recorded events or to run standard acquisition tools on the device.

Second, availability matters. Many SCADA devices must stay online to keep a plant, substation, or waterworks operating. Investigators cannot simply shut everything down to image drives. This requirement forces use of live-acquisition techniques that gather volatile data while systems keep running.

Third, timing and synchronization are difficult. Distributed devices often have different clocks and can drift. That makes correlating events across a wide system challenging unless timestamps are synchronized or corrected during analysis.

Finally, organizational and legal issues interfere. Companies often reluctant to share device details, firmware, or incident records because of safety, reputation, or legal concerns. That slows development of general-purpose tools and slows learning from real incidents.

All these challenges only increase the value of SCADA forensics specialists. Salary varies by location, experience, and roles, but can range from approximately $65,000 to over $120,000 per year.

Real-world attack chain

To understand why SCADA forensics matters, it helps to look at how real incidents unfold. The following examples show how a single compromise inside the corporate network can quickly spread into the operational side of a company. In both cases, the attack starts with the compromise of an HR employee’s workstation, which is a common low-privilege entry point. From there, the attacker begins basic domain reconnaissance, such as mapping users, groups, servers, and RDP access paths. 

Case 1

In the first path, the attacker discovers that the compromised account has the right to replicate directory data, similar to a DCSync privilege. That allows the extraction of domain administrator credentials. Once the attacker holds domain admin rights, they use Group Policy to push a task or service that creates a persistent connection to their command-and-control server. From that moment, they can access nearly every machine in the domain without resistance. With such reach, pivoting into the SCADA or engineering network becomes a matter of time. In one real scenario, this setup lasted only weeks before attackers gained full control and eventually destroyed the domain.

Case 2

The second path shows a different but equally dangerous route. After gathering domain information, the attacker finds that the HR account has RDP access to a BACKUP server, which stores local administrator hashes. They use these hashes to move laterally, discovering that most domain users also have RDP access through an RDG gateway that connects to multiple workstations. From there, they hop across endpoints, including those used by engineers. Once inside engineering workstations, the attacker maps out routes to the industrial control network and starts interacting with devices by changing configurations, altering setpoints, or pushing malicious logic into PLCs.

Both cases end with full access to SCADA and industrial equipment. The common causes are poor segmentation between IT and OT, excessive privileges, and weak monitoring.

Frameworks and Methodologies

A practical framework for SCADA forensics has to preserve evidence and keep the process safe. The basic idea is to capture the most fragile, meaningful data first and leave more invasive actions for later or for offline testing.

Start with clear roles and priorities. You need to know who can order device changes, who will gather evidence, and who is responsible for restoring service. Communication between operations and security must be planned ahead of incidents.

As previously said, capture volatile and remote evidence first, then persistent local data. This includes memory contents, current register values, and anything stored only in RAM. Remote evidence includes network traffic, historian streams, and operator session logs. Persistent local data includes configuration files, firmware images, and file system contents. Capturing network traffic and historian data early preserves context without touching the device.

A common operational pattern is to use lightweight preservation agents or passive sensors that record traffic and key events in real time. These components should avoid any action that changes device behavior. Heavy analysis and pattern matching happen later on copies of captured data in a safe environment.

When device interaction is required, prefer read-only APIs, documented diagnostic ports, or vendor-supported tools. If hardware-level extraction is necessary, use controlled methods (for example JTAG reads, serial console captures, or bus sniffers) with clear test plans and safety checks. Keep detailed logs of every command and action taken during live acquisition so the evidence chain is traceable.

Automation helps, but only if it is conservative. Two-stage approaches are useful, where stage one performs simple, safe preservation and stage two runs deeper analyses offline. Any automated agent must be tested to ensure it never interferes with real-time control logic.

SCADA Network Forensics

Network captures are often the richest, least disruptive source of evidence. Packet captures and flow data show commands sent to controllers, operator actions, and any external systems that are connected to the control network.

Start by placing passive capture points in places that see control traffic without being in the critical data path, such as network mirrors or dedicated taps. Capture both raw packets and derived session logs as well as timestamps with a reliable time source.

Protocol awareness is essential. We will cover some of them in the next article. A lot more will be covered during the course. Industrial protocols like Modbus, DNP3, and vendor-specific protocols carry operational commands. Parsing these messages into readable audit records makes it much easier to spot abnormal commands, unauthorized writes to registers, or suspicious sequence patterns. Deterministic models, for example, state machines that describe allowed sequences of messages, help identify anomalies. But expect normal operations to be noisy and variable. Any model must be trained or tuned to the site’s own behavior to reduce false positives.

Network forensics also supports containment. If an anomaly is detected in real time, defenders can ramp up capture fidelity in critical segments and preserve extra context for later analysis. Because many incidents move from corporate IT into OT networks, collecting correlated data from both domains gives a bigger picture of the attacker’s path

Endpoint and Device Forensics

Field devices are the hardest but the most important forensic targets. The path to useful evidence often follows a tiered strategy, where you use non-invasive sources first, then proceed to live acquisition, and finally to hardware-level extraction only when necessary.

Non-invasive collection means pulling data from historians, backups, documented export functions, and vendor tools that allow read-only access. These sources often include configuration snapshots, logged process values, and operator commands.

Live acquisition captures runtime state without stopping the device. Where possible, use the device’s read-only interfaces or diagnostic links to get memory snapshots, register values, and program state. If a device provides a console or API that returns internal variables, collect those values along with timestamps and any available context.

If read-only or diagnostic interfaces are not available or do not contain the needed data, hardware extraction methods come next. This includes connecting to serial consoles, listening on fieldbuses, using JTAG or SWD to read memory, or intercepting firmware during upload processes. These operations require specialized hardware and procedures. It must be planned carefully to avoid accidental writes, timing interruptions, or safety hazards.

Interpreting raw dumps is often the bottleneck. Memory and storage can contain mixed content, such as configuration data, program code, encrypted blobs, and timestamps. But there are techniques that can help, including differential analysis (comparing multiple dumps from similar devices), data carving for detectable structures, and machine-assisted methods that separate low-entropy (likely structured) regions from high-entropy (likely encrypted) ones. Comparing captured firmware to a known baseline is a reliable way to detect tampering.

Where possible, create an offline test environment that emulates the device and process so investigators can replay traffic, exercise suspected malicious inputs, and validate hypotheses without touching production hardware.

SCADA Forensics Tooling

Right now the toolset is mixed. Investigators use standard forensic suites for control-center hosts, packet-capture and IDS tools extended with industrial protocol parsers for networks, and bespoke hardware tools or vendor utilities for field devices. Many useful tools exist, but most are specific to a vendor, a protocol, or a device family.

A practical roadmap for better tooling includes three points. First, create and adopt standardized formats for logging control-protocol events and for preserving packet captures with synchronized timestamps. Second, build non-disruptive acquisition primitives that work across device classes, ways to read key memory regions, configuration, and program images without stopping operation. Third, develop shared anonymized incident datasets that let researchers validate tools against realistic behaviors and edge cases.

In the meantime, it’s important to combine several approaches, such as maintaining high-quality network capture, work with vendors to understand diagnostic interfaces, prepare hardware tools and safe extraction procedures, while documenting everything. Establish and test standard operating procedures in advance so that when an incident happens the team acts quickly and consistently.

Conclusion

Attacks on critical infrastructure are rising, and SCADA forensics still trails IT forensics because field devices are often proprietary, have limited logging, and cannot be taken offline. We showed those gaps and gave practical actions. You will need to preserve network and historian data early, prefer read-only device collection, enforce strict IT/OT segmentation, reduce privileges, and rehearse incident response to protect those systems. In the next article, we will look at different protocols to give you a better idea of how everything works.

To support hands-on learning, our 3-day SCADA Forensics course starts in November that uses realistic ICS network topologies, breach simulations, and labs to teach how to reconstruct attack chains, identify IOCs, and analyze artifacts on PLCs, RTUs, engineering workstations and HMIs. 

During the course you will use common forensic tools to complete exercises and focus on safe, non-disruptive procedures you can apply in production environments. 

Learn more: https://hackersarise.thinkific.com/courses/scada-forensics

The post SCADA (ICS) Hacking and Security: An Introduction to SCADA Forensics first appeared on Hackers Arise.