Create a single JSON object (or CSV row) that aggregates every data point you collected. Below is a template you can paste into a file and fill in programmatically:
Export the Procmon log to CSV/TSV and then into a table like: signallab-31nulled.rar
Export the disassembly (e.g., ida -A -Sexport_func_names.idc payload.exe ) and parse it for the above patterns, or use automated scripts like , PE-bear , Rico , or Detect It Easy batch mode. 5. Dynamic Feature Extraction ⚠️ Only run the payload inside a fully‑isolated, snapshot‑enabled VM . If the sample exhibits network activity, point it to a fake DNS/IP (e.g., 10.0.0.2 ) and capture the traffic. 5.1 Runtime Monitoring | Tool | What to Capture | |------|-----------------| | Process Monitor (Procmon) | File, Registry, Network, Process, Thread, and DLL events. Filter on the sample’s PID. | | Process Explorer | Process tree, loaded modules, CPU/MEM usage, integrity level. | | Wireshark | All outbound/inbound packets; apply a capture filter on the VM’s NIC. | | Regshot (pre/post) | Registry modifications. | | Autoruns (post‑run) | New auto‑run entries. | | Cuckoo Sandbox | Full JSON report (behavior, API calls, dropped files, network). | | PE-sieve / Scylla (post‑run) | Dump the in‑memory PE after unpacking. | | Volatility (if you take a memory dump) | Detect hidden processes, injected code, hooks. | 5.2 Typical Dynamic Features to Log | Category | Specific Items | |----------|----------------| | Process behavior | New processes spawned (name, command line, parent), CreateProcess , ShellExecute . | | File system | Files created, modified, deleted (paths, timestamps). | | Registry | Keys/values written under HKLM\Software\Microsoft\Windows\CurrentVersion\Run* , HKCU\Software\Classes\CLSID , HKLM\SYSTEM\CurrentControlSet\Services . | | Network | Outbound IPs/ports, DNS queries, HTTP/HTTPS URLs, SMB connections, TOR usage. | | Persistence | Scheduled Tasks ( schtasks ), Services ( CreateService ), WMI Event Consumers. | | Privilege escalation | Token manipulation ( ImpersonateLoggedOnUser , AdjustTokenPrivileges ). | | Anti‑analysis | Checks for sandbox files ( C:\Program Files\VMware ), timing checks ( GetTickCount ), debugger detection. | | Payload drop | Any secondary binaries written to disk (hash them). | | Encryption / C2 | Observed data sent to remote hosts (hex dump, base64). | Create a single JSON object (or CSV row)
The workflow covers both (no code execution) and dynamic (controlled execution) analyses, and it lists the exact data points you’ll want to capture to build a “full feature” profile that can be used for malware research, detection rule creation, or machine‑learning feature extraction. 1. Prepare a Safe Analysis Environment | Requirement | Recommended Tool / Setting | |-------------|-----------------------------| | Isolated VM | Windows 10/11 (64‑bit) in VirtualBox/VMware with a snapshot before each run. | | Network isolation | Disable bridge/NAT; use a host‑only adapter or a virtual firewall (e.g., INetSim) to simulate services. | | Anti‑forensics protection | Disable Windows Defender, Real‑Time Protection, and any AV that might delete/alter the sample. | | Forensic logging | Enable Windows Process Monitor (Procmon) , Process Explorer , Autoruns , Regshot , and Wireshark on the host. | | Reversing tools | IDA Pro, Ghidra, Binary Ninja, x64dbg, OllyDbg, radare2, etc. | | Static analysis suites | PEiD, PEview, Exeinfo PE, Detect It Easy (DIE), CFF Explorer, PE-bear. | | Dynamic analysis sandbox | Cuckoo Sandbox, REMnux (Linux), or a custom sandbox script using PowerShell and APIs (e.g., NtQuerySystemInformation ). | | Hashing | certutil -hashfile , sha256sum , md5sum . | | YARA | Write or use existing rules to flag known packers, crypto miners, etc. | 2. Collect Basic File Metadata | Feature | How to Extract | |---------|----------------| | File name | Already known ( signallab-31nulled.rar ). | | File size | dir signallab-31nulled.rar or Get-Item . | | Hashes | certutil -hashfile signallab-31nulled.rar MD5 SHA1 SHA256 . | | Timestamp | Get-Item signallab-31nulled.rar | Select-Object CreationTime, LastWriteTime, LastAccessTime . | | Entropy | Use PEiD → Entropy view, or binwalk -E / python -c "import math,sys; data=open('signallab-31nulled.rar','rb').read(); print(-sum((b/255.0)*math.log2(b/255.0) for b in data if b!=0))" | | File type | file signallab-31nulled.rar (should report “RAR archive data”). | | Compression / Encryption flag | RAR headers show whether the archive is encrypted ( rar v signallab-31nulled.rar ). | Dynamic Feature Extraction ⚠️ Only run the payload
{ "file_name": "signallab-31nulled.rar", "file_hashes": "md5": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", "sha1": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", "sha256": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" , "file_size": 123456, "entropy": 7.92, "extracted_payload": { "file_name": "payload.exe", "file_type": "PE32+ executable (GUI) Intel 80386", "pe_header": "machine": "0x8664", "timestamp": "2025-11-02 08:15:33", "subsystem": "Windows GUI", "dll_characteristics": ["ASLR", "DEP"] , "sections": [ "name": ".text", "size_raw": 204800, "entropy": 6.7, "name": ".rdata", "size_raw": 51200, "entropy": 5.4, {"name": ".
"pid": 1234, "timestamp": "2026-04-16T12:34:56.789Z", "event": "CreateFile", "path": "C:\\Users\\Public\\tmp\\payload2.exe", "result": "SUCCESS"