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analyzing-heap-spray-exploitation

analyzing-heap-spray-exploitation

github.com/mukul975Security35.2k373 installsUpdated 8w ago
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About analyzing-heap-spray-exploitation

A security analysis skill for examining heap-spray exploitation in memory dumps, intended for incident responders and analysts familiar with memory forensics. It uses Volatility3 to identify suspicious allocations, NOP sleds, and embedded shellcode, and produces a JSON report.

Key features

  1. 01扫描可疑进程的注入内存
  2. 02分析大型连续内存分配
  3. 03查找 NOP sled 特征
  4. 04提取并分析 shellcode
  5. 05生成 JSON 分析报告

Use cases

  1. 01调查内存转储中的堆喷射
  2. 02识别可疑可执行内存区域
  3. 03提取 shellcode 供后续分析

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-heap-spray-exploitation

After installing, type/analyzing-heap-spray-exploitationin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE
references/
api-reference.md
scripts/
agent.py

Details

From the project README

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.

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