How to Use a PE Analyzer for Malware Analysis and Reverse Engineering

How to Use a PE Analyzer for Malware Analysis and Reverse EngineeringUnderstanding Portable Executable (PE) files is essential for malware analysts and reverse engineers working on Windows-based binaries. A PE analyzer streamlines inspection of headers, sections, imports/exports, resources, and embedded data, enabling both quick triage and deep static analysis. This article walks through a practical workflow for using a PE analyzer, covering setup, key concepts, hands-on steps, common techniques for discovering malicious behavior, and tips for integrating PE analysis with dynamic and automated methods.

What is a PE Analyzer?

A PE analyzer is a tool that parses the Portable Executable (PE) file format used by Windows executables, DLLs, and other binary objects. It extracts structured metadata (DOS header, PE header, optional header, section table), shows import/export tables, resource trees, certificates, overlay data, and often provides features like entropy calculation, signature verification, and virtual address mapping. Examples range from GUI tools (like PE-bear, CFF Explorer, PEStudio) to command-line libraries and frameworks (like pefile for Python, LIEF, or custom parsers).

Why PE Analysis Matters in Malware Investigation

• Quick triage: identify suspicious packers, obfuscation, or uncommon sections.
• Hunt IOCs: find known malicious imports, strings, or hard-coded domains/IPs.
• Understand execution: map imports and entry points to probable runtime behavior.
• Support reverse engineering: prepare binaries for disassembly by locating code sections, overlays, and unpackers.
• Attribution and persistence: extract certificates, resources, and version info for contextual clues.

Setup: Tools and Environment

• Static tools: PEStudio, CFF Explorer, DIE (Detect It Easy), PE-bear, Exeinfo, rizin/cutter, Ghidra (PE loader).
• Libraries: pefile (Python), LIEF (C++/Python), pyelftools (not PE), radare2, r2pipe.
• Complementary tools: strings, sigcheck (Sysinternals), VirusTotal, YARA, binwalk.
• Safe environment: analyze in an isolated VM or dedicated analysis machine; no network access unless using controlled monitoring for dynamic tests.

Key PE Concepts to Know

• DOS Header and DOS Stub: legacy MS-DOS header; non-critical but can contain messages.
• PE Header and Optional Header: machine type, number of sections, entry point, image base, subsystem, and characteristics.
• Section Table: .text, .rdata, .data, .rsrc, .reloc, plus custom sections. Their characteristics (executable, readable, writable) matter.
• Import Address Table (IAT) and Export Table: functions the binary uses and exposes.
• TLS callbacks and entry point: code executed before main().
• Overlay: appended data after sections — often used by packers.
• Certificates and Authenticode: signer info that can indicate legitimacy or false signing.
• Resources: dialogs, icons, embedded files that may contain payloads or configuration.

Practical Workflow

1. Initial triage

   • Check file type and basic metadata (size, PE magic, machine).
   • Calculate entropy for sections — high entropy often indicates packing/compression/encryption.
   • Scan for packer signatures and known packers (UPX, Themida, etc.).
   • Identify suspicious imports (e.g., VirtualAlloc, CreateRemoteThread, LoadLibrary, GetProcAddress, URLDownloadToFile, InternetOpen/Connect).

2. Extract static indicators

   • Export/import table analysis: list API calls and map to likely behaviors (network, persistence, injection).
   • Strings extraction: search for URLs, IPs, commands, mutex names, registry keys, file paths.
   • Resource inspection: extract embedded files, configuration blobs, images containing steganographic data.

3. Section and overlay inspection

   • Check section names and permissions. Unusual names or RWX sections may indicate injected code.
   • Dump overlays and analyze as separate artifacts; overlays can be encrypted payloads or appended scripts.

4. Signature and certificate checks

   • Verify digital signatures; examine certificate chain and unusual signers.
   • Check for tampering indicators: valid signature but modified sections.

5. Unpacking and unpacker detection

   • If packed, attempt known unpackers (e.g., UPX -d). If custom-packed, use dynamic unpacking:
     • Run in instrumented VM, set breakpoints on entry point, map memory, dump process image after unpacking.
     • Use memory dumper tools (ProcDump, Scylla) to extract in-memory original PE.

6. Prepare for disassembly

   • Rebase and correct image base if needed.
   • Fix IAT or reconstruct if import addresses are resolved at runtime.
   • Load the cleaned/dumped binary into IDA/Ghidra/rizin/Cutter for automated analysis and function recovery.

7. Automation and enrichment

   • Create YARA rules from unique strings/byte patterns.
   • Automate static extraction with pefile/LIEF scripts to harvest IOCs and metadata for sharing.
   • Cross-check with threat intelligence sources and VirusTotal for context.

Common Techniques to Spot Malicious Behavior

• Suspicious API combos: e.g., VirtualAlloc + WriteProcessMemory + CreateRemoteThread suggests process injection.
• Network-related imports combined with string patterns for command-and-control (C2) addresses.
• Use of reflection, LoadLibrary/GetProcAddress with obfuscated strings for evasive dynamic resolution.
• Exception handlers or TLS callbacks used for stealthy initialization.
• Packed/obfuscated sections with high entropy and little readable strings.
• Self-modifying code sections or anomalous section permissions (executable + writable).

Example: Quick PE Analyzer Checklist

• PE magic valid?
• EntryPoint within executable section?
• Any RWX sections?
• High-entropy sections?
• Known packer signature?
• Notable imports: networking, process, registry, virtualization checks?
• Embedded strings: domains, file paths, commands?
• Digital signature present and valid?

Tips and Pitfalls

• Don’t trust strings alone — many malware authors include decoys.
• Packers often mask imports; focus on behavior observed in-memory after execution.
• Automated tools can miss obfuscation; manual inspection of headers and sections is still valuable.
• Keep a catalog of common API patterns for quick mapping to behaviors.
• Use multiple tools: one tool may parse a malformed PE differently than another.

Integrating with Dynamic Analysis

Static PE analysis is fast and low-risk but limited. Combine with controlled dynamic analysis:

• Run sample in VM with snapshoting; monitor network, files, registry, and processes.
• Use API monitors (API Monitor, Frida) to capture runtime API calls.
• Dump process memory after a period to extract unpacked code for deeper static analysis.

Sample Python Snippet: Extract Imports with pefile

import pefile, sys pe = pefile.PE(sys.argv[1]) for entry in getattr(pe, 'DIRECTORY_ENTRY_IMPORT', []):     print(entry.dll.decode())     for imp in entry.imports:         print(f"  {hex(imp.address) if imp.address else ''} {imp.name}") 

Conclusion

A PE analyzer is a foundational tool in malware analysis and reverse engineering. Use it for rapid triage, extracting IOCs, detecting packers, and preparing binaries for deeper reverse-engineering work. Combining static PE analysis with dynamic monitoring and automated tooling yields the most reliable insights into malicious Windows binaries.