Malware Analysis Processes

I Extracted an Encryption Key from RAM during Dynamic Analysis. It’s 3:05am. I’ve been working on a ransomware case that recently hit several endpoints. The sample came in obfuscated, unlabelled, and exhibiting non-standard post-encryption behavior but it slipped. Here’s my live analysis, entirely on Linux, without static disassemblers or Windows-based sandboxing: 1. Initial Behavioral Profiling: The sample revealed ransomware-like behavior within the first minute of execution: • The payload spawned predictable file I/O syscalls against the infected document set. • After-encryption, it initiated outbound network traffic to a hardcoded IP on TCP port. I didn’t decompile or unpack. I went straight to runtime behavioral analysis. 2. Live Dynamic Tracing of System Calls and CryptoAPI I monitored: • File descriptors (open, read, write) tied to .enc output files. • Heap memory allocations via mmap and brk. • OpenSSL CryptoAPI activity. These exact APIs have been abused by some ransomware families before, especially those that rely on ephemeral AES keys without wiping memory. 3. With the encryption key likely existing only in memory, I attached GDB to the live process: On hitting the CryptoAPI call, the AES-256-CBC key was exposed in plain memory a classic opsec oversight. To preserve forensic integrity, I also dumped the memory. This validated that no memory clearing was implemented, and sensitive material was retained post-encryption. 4. Network Telemetry Inspection (C2): I observed traffic from the sample to a loopback of C2. A listener on port 4444 confirmed that the malware transmits a beacon after file encryption, matching tactics seen in lateral movement tools. 5. Summary of Findings (In Progress) • The ransomware uses OpenSSL’s EVP interface insecurely. • Keys remain in memory and are trivially extractable. • Syscall tracing exposes every stage of the attack lifecycle without needing source or symbols. • The malware does not clean buffers or invoke memory zeroing post-encryption. • Outbound beaconing was observed post-encryption, possibly for key exchange or reporting success. Why This Analysis Matters: As malware analysts we can rely on native Linux analysis and behavioral monitoring alone, to extract critical observables, rebuild attack timelines, and potentially reverse damage without reverse engineering the binary statically. Takeaways for Analysts and Threat Hunters: • Monitor EVP_* CryptoAPI calls during runtime. • Capture syscalls early because encryption happens fast. • Memory is rarely sanitized properly. • The stack and heap betray ransomware more often than the binary itself. • Behavioral parity can tell you everything, even when strings and symbols are gone. Threat actors reuse bad crypto patterns. Now I can go to bed, and Happy Birthday to myself 😊 #MalwareAnalysis #DynamicAnalysis #MemoryForensics #ReverseEngineering #LinuxForensics #DigitalForensics #RedTeaming #ThreatHunting

One key area we focused on was how malware interacts with DLLs (Dynamic Link Libraries). DLLs are shared libraries that contain functions used by multiple programs. Instead of rewriting code, Windows programs (including malware) simply call DLLs to perform common tasks like network connections, file access, or UI rendering. 🔍 Why does this matter in malware analysis? Malware often imports functions from DLLs like kernel32.dll, user32.dll, or ws2_32.dll. By analyzing which DLLs are imported, we can predict behavior before executing the file. Tools like Dependency Walker help us explore these imports in detail. As SOC analysts, we also watch for malicious DLL behaviors like: *DLL sideloading, where attackers drop a fake DLL next to a legitimate program *Export manipulation, where malware mimics the expected functions of trusted DLLs *Suspicious load paths, like DLLs running from Temporary file paths instead of places where legitimate programs typically store DLLs. Every unexpected or unusual DLL import is a clue. Learning to trace those patterns helps us catch threats early, often before any real damage is done. Here are some important DLLs and their functions:

Integrating Wazuh, MISP Project (@misp@misp-community.org ), and Cuckoo Sandbox for validating file hashes is a powerful strategy to enhance threat detection and response. This workflow combines Wazuh's logging and alerting, MISP's threat intelligence, and Cuckoo Sandbox's malware analysis capabilities. Here's a basic guide to set up this integration: ### Integration Steps 1. **Wazuh Configuration:** - Ensure Wazuh is properly configured and operational. - Set up rules in Wazuh to detect suspicious files and extract their hashes for further analysis. 2. **Wazuh and MISP Integration:** - Configure a connector between Wazuh and MISP so that alerts from Wazuh can be sent as events to MISP. - In MISP, enrich these alerts with threat intelligence. 3. **Cuckoo Sandbox Configuration:** - Install and configure Cuckoo Sandbox in an isolated environment. - Ensure Cuckoo is ready to analyze samples submitted by other systems. 4. **Hash Validation Workflow:** - When a suspicious hash is identified in Wazuh, check MISP for any known threat associations. - If there is not enough information in MISP, submit the file related to the hash to Cuckoo Sandbox for analysis. - Use the Cuckoo API to automate submission and retrieval of results. - Update MISP with results from the Cuckoo analysis, enhancing your threat intelligence database. 5. **Automation and Alerts:** - Use Wazuh's alert management capabilities to notify responsible teams when new analysis results become available. - Set up scripts to automate processes within this workflow, leveraging the available APIs from Wazuh, MISP, and Cuckoo. ### Tips: - **Security:** Ensure all communications between Wazuh, MISP, and Cuckoo are secure, using HTTPS or VPNs. - **Performance:** Monitor the performance of each component to ensure the integration doesn't cause unnecessary delays. - **Logs and Audit:** Maintain detailed logs of all automated actions and analyses, which aids in audit and process improvement. This integration not only improves response time to threats but also generates a valuable cycle of threat intelligence that can greatly enhance your network's security. If you need more details on any of the steps, feel free to ask! #cyberdefense #cyberawareness #cybersecurity #cyberattacks #wazuh #sandbox #misp

Sometimes, to find the truth, you have to let the system run - Why Boot a Suspect System? Because Sometimes, Static Analysis Isn’t Enough. In digital forensics, we often deal with forensic disk images—raw snapshots of digital devices captured during investigations. We carve files, examine logs, and reconstruct timelines. But occasionally, you hit a wall. What if the evidence is hidden in an encrypted app that only runs in the user’s environment? What if credentials are stored in volatile memory and protected behind a PIN? What if you need to observe how malware behaves when the system runs? That’s when we shift from static analysis to live examination. 💡 As a researcher, I built a guide for converting E01 forensic disk images into bootable Windows virtual machines. And honestly, this method has become one of the most practical tools in my investigative workflow. Whether in legal cases, insider threat investigations, or corporate security breaches, I’ve used this approach to: a. Crack login PINs and access protected user accounts b. Simulate and observe real-time malware behavior in sandboxed VMs c. Extract evidence hidden in applications that won’t run outside their native environments d. Interactively explore session data and user behavior e. Validate and reproduce findings before reporting ⚙️ The guide walks you through: Converting E01 images to raw .dd format using FTK Imager Turning the .dd into a VirtualBox .vmdk disk with VBoxManage Booting it as a fully functional Windows VM Troubleshooting EFI and boot errors 🧠 Why it matters: This method transforms how we understand and interact with evidence. It empowers forensic analysts, students, and investigators to go beyond static snapshots—into live, immersive evidence environments. I’ve used this not just as an academic exercise, but in real-world casework at Prudential Associates, where complex investigations demand interactive analysis. 🔗 I’ve also created a full GitHub README and guide with all steps documented—happy to share it with anyone in the forensics, cybersecurity, or legal communities. Sometimes, to find the truth, you have to let the system run. #DigitalForensics #DFIR #CyberForensics #MalwareAnalysis #ForensicVirtualization #E01 #GraduateResearch #UniversityOfBaltimore #PrudentialAssociates #LiveForensics #Cybersecurity #VirtualMachines #IncidentResponse

Part 2: Dynamic Malware Analysis Dynamic Malware Analysis is the process of running potentially malicious software in an isolated environment to monitor and analyze its actions and effects on the system. Key Aspects to Monitor: • File System Activity: Creation, modification, or deletion of files. • Process Activity: New processes spawned, process injection, or unusual process behavior. • Registry Changes: Modifications to registry keys and values. • Network Traffic: Outgoing connections, data exfiltration, or communication with suspicious IP addresses or domains. • Memory Activity: Unusual memory usage or memory injection techniques. • Persistence Mechanisms: Attempts to achieve persistence through startup entries, scheduled tasks, or services. • API Calls: Suspicious or uncommon API calls that might indicate malicious intent. • System Changes: Changes to system settings, configurations, or security policies. • Behavioral Anomalies: Any behavior that deviates from the norm, such as unexpected encryption or obfuscation. Tools for Dynamic Malware Analysis: Sandbox Environments Cuckoo Sandbox, FireEye , Joe Sandbox, Hybrid Analysis, Any.Run, VxStream Sandbox Process and System Monitoring: Process Monitor, Process Hacker, Autoruns, Noriben, Sysinternals Suite Network Analysis: Fiddler, Wireshark, TCPView, ApateDNS Static and Hybrid Analysis: VirusTotal, ReversingLabs TitaniumCloud, Intezer Analyze, Ghidra Registry and System Change Detection: Regshot Debugging and Code Analysis: OllyDbg, x64dbg, PE-sieve, Windbg, Radare2 Visual Analysis and Correlation: ProcDot Specialized Linux Toolkit: REMnux Other Tools: SysInternal Tools, CFF Explorer, PEView, BinText, PEiD, Regshot, HashMyFiles Detailed Focus Areas: Process Activities: Detect processes, focus on new child processes, DLL imports, and user context. Tools like Process Hacker help visualize these processes Network Activities: Analyze connections using Wireshark and Fiddler to understand and report the malware’s network activities Registry Activities: Monitor key registry locations HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\RunOnce HKEY_LOCAL_MACHINE\Software\Microsoft\Windows\CurrentVersion\Run HKEY_LOCAL_MACHINE\Software\Microsoft\Windows\CurrentVersion\RunOnce Tools like Regshot can compare registry states before and after malware execution to identify changes made by the malware. File Activities: Monitor directories like "Temp" and "Startup" for suspicious activities. '%TEMP%' for temporary files 'shell:startup' and 'shell:common startup' for startup directories Step-by-Step Guide for Dynamic Malware Analysis: 1. Prepare the Analysis Environment 2. Install Analysis Tools 3. Configure Monitoring Tools 4. Execute the Malware Sample 5. Monitor and Record Behavior 6. Analyze Collected Data 7. Restore the Environment BlackPerl DFIR #CyberSecurity #MalwareAnalysis #CyberDefense #Hacking

Malware Analysis Exercises #5 - Analyzing a simple process injection Process Injection occurs when code is injected into the memory space of another running process. This allows the injected code to execute within the selected process. Figure 1: It is loading some libraries such as vcruntime140d.dll, ucrtbase.dll, kernelbase.dll, kernel32.dll, and ntdll.dll, and you can notice some interesting functions. Figure 2: You can see some interesting functions being used. GetCurrentProcess, which returns a pseudohandle of the current process, and TerminateProcess, used to terminate a process. GetProcAddress, commonly used in code injections to locate the addresses of functions exported from DLL libraries. GetCurrentProcessId and GetSystemTimeAsFileTime retrieve the process ID and the system time in file format. Figure 3: There are several byte addition instructions (with ADD BYTE PTR), register manipulation, and memory access ([rdi], [rbp], [rsi], etc.), which suggest write and read operations, which are quite common in code injection routines or modification of a process's structures. Additionally, you can notice the presence of a conditional code (jb instructions), which may indicate flow control based on a condition or comparison, and you can also see the reference to "notepad.exe", which could be the target where the code will be injected. Figure 4: The call to OpenProcess is crucial in some injection techniques, as it opens the process where the code will be injected. The presence of the instruction test eax, eax after the call to OpenProcess serves to check if the function was successfully executed, indicating that the process was opened without errors and memory allocation, data writing, and execution could proceed. Figure 5: call qword ptr ds:[<&VirtualAllocEx>] makes a call to the VirtualAllocEx function, which allocates memory in the notepad process. This can be noted, as there are a series of data movement instructions in the registers (mov). call qword ptr ds:[<&WriteProcessMemory>] after allocating the memory in the notepad process, this instruction calls the WriteProcessMemory function, which is responsible for writing the payload into the memory allocated in the process. call qword ptr ds:[<&CreateRemoteThread>] calls the CreateRemoteThread function, which creates a new thread inside the notepad process to execute the injected code. And you can see other instructions that are moving data and manipulating information in memory. More details about Process Injection by Usman Sikander: https://lnkd.in/e6XRSaS4 Others Malware Analysis Exercises: https://lnkd.in/dyn2dWcf Dissecting Wndows Malware Series - Process Injection by 8kSec https://lnkd.in/ePXg24MB Source Code: https://lnkd.in/eaJe9MDS #malwareanalysis #redteam #cybersecurity #malwareanalysisexercises #blueteam

🔍 Unraveling the Shadows: Navigating the World of Malicious Operations (MalOps) 🔍 Diving deep into the intriguing and often elusive realm of Malicious Operations (MalOps). 👇🏼 a technical breakdown: 👉🏼 Triage and Analysis Precision: MalOps demands a surgical approach to triage and analysis. Identifying and dissecting malicious operations require a keen understanding of attacker tactics, techniques, and procedures (TTPs). 🕵️♂️💼 👉🏼 Indicators of Compromise (IoCs): MalOps investigators meticulously trace IoCs like digital breadcrumbs, connecting the dots to unravel the adversary's path. IoCs serve as the compass guiding the response. 🔍🔗 👉🏼 Behavioral Analysis Mastery: Understanding the behavior of malicious entities is key. MalOps professionals excel in behavioral analysis, discerning anomalies that might evade traditional detection mechanisms. 🔄📊 👉🏼Malware Reverse Engineering: The anatomy of malware is laid bare through reverse engineering. MalOps experts dissect malicious code, uncovering its functionalities and enabling the creation of robust defenses. 🦠💻 👉🏼Threat Intelligence Integration: The battle against MalOps is fueled by timely and relevant threat intelligence. Integrating threat feeds into defenses provides the edge needed to thwart emerging threats. 🌐🛡️ 👉🏼 🔐🔍 Digital Forensics Vigilance: MalOps investigations often lead to the forensics frontier. Digital forensics skills are paramount in reconstructing the sequence of events and understanding the impact of malicious activities. ✍🏽Hamza ZARKI #MalOps #CyberSecurity #ThreatAnalysis #incidentresponse #cyberdefenders #maliciousbehavior #cyberinvestigation #threatintelligence #cybereason #edr #xdr