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Analyzing Heap Spray Exploitation

  • 303 installs
  • 27.3k repo stars
  • Updated August 2, 2026
  • mukul975/anthropic-cybersecurity-skills

Run structured heap spray, gadget-chain, and heap-metadata analysis when reviewing native implants, C2-linked binaries, or memory-corruption exploits.

About

Analyzing Heap Spray Exploitation is an agent skill for solo builders and small security-focused teams who need repeatable procedures for studying heap spray and related memory-corruption tactics in offensive-security contexts. It walks through gadget chain automation, spray size prediction, cross-platform heap metadata forensics, and optional Frida instrumentation, with Python examples tied to tooling such as Ghidra, ROPgadget, Volatility, and GDB. Use it when a binary or implant reference mentions heap spray, Cobalt Strike–style staging, or large controlled allocations and you need analysis artifacts rather than ad-hoc notes. The skill is advanced and native-focused; it complements broader AppSec checklists by going deep on allocator behavior and ROP/JOP preparation. Outputs are analytical summaries and scripted findings you can fold into threat models, incident notes, or hardening tasks before or after ship.

  • Orchestrates HeapSprayAnalyzer-style workflows for implant and C2 heap spray patterns with Windows and Linux paths
  • Automates gadget chain discovery using Ghidra scripting, py-gadget-search, and ROPgadget with x64 and syscall filtering
  • Predicts heap spray allocation sizing from base parameters and multipliers for exploit surface estimation
  • Documents Windows heap metadata forensics via Volatility and Linux libc heap inspection via GDB
  • Ships Frida JavaScript hook templates for runtime allocation and spray-related API monitoring

Analyzing Heap Spray Exploitation by the numbers

  • 303 all-time installs (skills.sh)
  • +18 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #633 of 2,203 Security skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-heap-spray-exploitation

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Listed on Skillselion
Installs303
repo stars27.3k
Security audit3 / 3 scanners passed
Last updatedAugust 2, 2026
Repositorymukul975/anthropic-cybersecurity-skills

What it does

Run structured heap spray, gadget-chain, and heap-metadata analysis when reviewing native implants, C2-linked binaries, or memory-corruption exploits.

Files

SKILL.mdMarkdownGitHub ↗

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.

Related skills

FAQ

Is Analyzing Heap Spray Exploitation safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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