MANDIANT Heap Inspector: A Complete Introduction for Malware Analysts

Speed Up Malware Investigations with MANDIANT Heap InspectorMalware investigations increasingly rely on fast, accurate memory analysis. Attackers live in volatile memory, and process heaps often contain the richest, most immediate evidence: injected code, decrypted payloads, configuration data, and ephemeral artifacts that never touch disk. MANDIANT Heap Inspector (MHI) is a targeted tool designed to accelerate forensic triage and detailed analysis of process heaps. This article explains how to use MHI effectively, demonstrates workflows that save hours in incident response, and shares practical tips and heuristics for extracting high-impact artifacts quickly.

Why focus on heaps?

Heaps are where many modern malware families unpack or decrypt payloads at runtime. Unlike static files on disk, heap-resident data often contains the true, unobfuscated executable code or configuration—exactly what an analyst needs to understand capabilities and actor intent. Common high-value heap artifacts include:

• In-memory unpacked PE files and shellcode
• Command-and-control (C2) URLs, IPs, and encryption keys
• Staged payloads and script interpreters
• Strings and structured configuration blobs (JSON, protobuf, XML)
• Function pointers and vtables used by injection techniques

Because these artifacts can be transient, rapid capture and streamlined analysis are crucial. MANDIANT Heap Inspector streamlines the discovery and extraction of these items.

What is MANDIANT Heap Inspector?

MANDIANT Heap Inspector is a specialized memory forensics utility that inspects process heaps to locate and extract suspicious or interesting data structures. It leverages targeted scanning heuristics, pattern detection, and automated reconstruction routines geared toward malware investigation, minimizing manual searching through large memory dumps.

Key capabilities:

• Scanning of process heaps for PE headers, shellcode patterns, and known packer signatures
• Extraction and rebuilding of in-memory PE images
• Heuristics for locating obfuscated or fragmented strings and config blobs
• Integration-friendly outputs for downstream tools (YARA, IDA, Ghidra, Volatility/WinDbg)
• Fast scanning optimized for large memory captures and live processes

Typical investigation workflow using MHI

Below is an efficient, field-tested workflow you can adopt during incident response. It blends rapid triage with deeper follow-up investigation.

1. Preparation and capture

   • Acquire a full memory image (best) or targeted process dumps of suspected processes. If live access available, use tools that minimally disturb memory layout.
   • Collect process metadata (PID, parent PID, command line, loaded modules) for context.

2. Initial MHI scan (triage)

   • Run MHI against process heaps to detect obvious in-memory PEs, shellcode signatures, and plaintext configuration. This fast pass should return a prioritized list of candidate artifacts.
   • Focus on high-signal artifacts first: PE files and long URLs or keys.

3. Automated extraction and reconstruction

   • Use MHI’s reconstruction routines to rebuild PE images found in heap segments. Export reconstructed binaries for static analysis and YARA scanning.
   • Extract contiguous string regions and attempt simple deobfuscation (XOR/ROT) if supported.

4. Corroboration and linking

   • Cross-check extracted artifacts with process module list and disk-resident files. If a reconstructed PE matches a disk binary, note differences (patched code, unpacked sections).
   • Feed exported samples to sandboxing and threat intelligence. Look for C2 indicators, command sets, or unique function signatures.

5. Deep analysis

   • Load extracted binaries into IDA/Ghidra for disassembly. Use MHI’s metadata (offsets, heap addresses) to map in-memory addresses to the loaded file for accurate analysis.
   • For kernel-mode investigations, correlate heap artifacts with drivers and device interactions where relevant.

6. Reporting and action

   • Summarize critical findings: extracted payloads, C2 indicators, persistence mechanisms, injection methods.
   • Provide IOCs for containment (IPs, domains, mutexes, file hashes) and recommended remediation (process termination, host isolation, memory captures for other hosts).

Practical MHI techniques and heuristics

• Prioritize heaps of processes that interact with the network, have unusual parent/child relationships, or show signs of code injection (suspended threads, remote thread creation).
• Look for PE headers (MZ/PE) inside heaps; many unpackers store full DLL/EXE images before mapping them into memory.
• Scan for wide-character (UTF-16LE) and ASCII URLs—malware often stores configuration as readable strings.
• Use entropy measures to find encrypted or packed payloads. High entropy regions in heaps often indicate compressed/encrypted payloads; low-entropy plain strings nearby may be config or keys.
• When a PE lacks import tables (typical of shellcode or in-memory loaders), search for known loader patterns or reconstruct a minimal import table to allow static tools to analyze the code.
• For fragmented artifacts, use surrounding metadata (heap allocation headers, heap segment start/end, thread stack references) to reassemble pieces that belong together.
• Maintain a library of YARA signatures for known packers, loaders, and common C2 patterns; run these against MHI outputs automatically.

Case examples (brief)

1. Unpacked RAT discovered in heap

   • Scenario: Network anomalies traced to a user workstation. MHI detected an in-memory PE inside explorer.exe heap. Reconstruction produced a DLL that contained hardcoded C2 URIs and a custom RC4-like routine. Rapid extraction allowed containment and IOC creation within hours.

2. Fileless loader injecting shellcode

   • Scenario: A process with no suspicious disk files exhibited remote thread creation. MHI located shellcode patterns in heap fragments; after reassembly and export, reverse engineering revealed a staged downloader and a unique command protocol.

These examples illustrate how quick heap inspection eliminates guesswork and reveals the true runtime artifacts malware authors try to hide.

Integration with other tools

• Volatility/Volatility3: Use MHI outputs to guide plugin selection and to provide reconstructed binaries for deeper memory mapping.
• YARA: Automate YARA scans on MHI-extracted files and string pools to flag known families and behaviors.
• IDA/Ghidra: Export binaries and map in-memory addresses for accurate function/variable recovery.
• Sandboxes: Submit reconstructed samples for dynamic behavior analysis when safe to do so.

Performance and automation tips

• Parallelize scans across processes and hosts where possible. MHI is designed to output discrete artifacts per-process which makes distributed automation straightforward.
• Use sampling heuristics for very large captures: scan the most probable heaps first (processes with network handles, high write+execute permissions, or anomalous parent PIDs).
• Cache and index extracted artifacts; identical unpacked payloads across hosts speed up triage through deduplication.
• Integrate into incident response playbooks: automated memory capture → MHI triage → automated YARA/TI lookup → escalate to manual analysis if high confidence.

Limitations and mitigations

• Obfuscation and anti-forensics: Malware may deliberately fragment, encrypt, or self-modify to evade heap scanners. Mitigate by combining entropy and structural heuristics, increasing the signal-to-noise ratio.
• False positives: Not every PE-like blob is malicious; many legitimate applications use in-memory generated code. Use process context and corroborating behavior (network, persistence) before concluding maliciousness.
• Live-memory capture artifacts: Some captures alter process memory layout. Prefer minimally invasive capture tools and repeat captures if behavior changes.

Quick checklist for responders

• Capture: Full memory or targeted process dumps from suspicious hosts.
• Triage: Run MHI for fast discovery of PE images, shellcode, and config.
• Extract: Reconstruct and export artifacts; run YARA and hash checks.
• Correlate: Map to processes, disk files, and network activity.
• Analyze: Static/dynamic analysis on reconstructed binaries.
• Remediate: Isolate hosts, block IOCs, and patch entry vectors.

Conclusion

MANDIANT Heap Inspector brings focused, practical capabilities to memory forensics that directly reduce the time from detection to actionable intelligence. By prioritizing in-memory artifacts, using targeted heuristics, and integrating MHI outputs into automated triage pipelines, incident responders can reveal the runtime truth of modern malware—often hidden from file-centric tools. For teams handling frequent or high-stakes incidents, investing in heap-focused analysis workflows pays off in faster containment, clearer attribution, and fewer missed artifacts.