Analyzing heap spray exploitation

Skill 26zl/cybersec-toolkit/.claude/skills/analyzing-heap-spray-exploitation

Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.From its SKILL.md

Install

npx -y skills add 26zl/cybersec-toolkit --skill analyzing-heap-spray-exploitation

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SKILL.md

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Analyzing Heap Spray Exploitation

Overview

Heap spraying is an exploitation technique that fills large regions of a process's heap with attacker-controlled data (typically NOP sleds followed by shellcode) to increase the reliability of code execution exploits. This skill covers detecting heap spray artifacts in memory dumps using Volatility3's malfind, vadinfo, and memmap plugins, identifying suspicious contiguous memory allocations, scanning for NOP sled patterns (0x90, 0x0c0c0c0c), and extracting embedded shellcode for analysis.

When to Use

When investigating security incidents that require analyzing heap spray exploitation
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques

Prerequisites

Python 3.9+ with volatility3 framework installed
Memory dump file (.raw, .vmem, .dmp format)
Understanding of virtual memory layout and VAD (Virtual Address Descriptor) trees
Familiarity with common shellcode patterns and NOP sled encodings

Steps

Step 1: Identify Suspicious Processes

Use Volatility3 windows.malfind to scan for processes with executable injected memory regions.

Step 2: Analyze VAD Entries

Examine VAD tree entries using windows.vadinfo for large contiguous allocations with RWX permissions.

Step 3: Scan for NOP Sled Patterns

Search suspicious memory regions for NOP sled signatures (0x90 sequences, 0x0c0c0c0c patterns).

Step 4: Extract and Analyze Shellcode

Dump suspicious memory regions and identify shellcode using byte pattern analysis.

Expected Output

JSON report with suspicious processes, heap spray indicators, NOP sled locations, memory region sizes, and extracted shellcode hashes.