analyzing-heap-spray-exploitation

analyzing-heap-spray-exploitation is a skill for Claude Code from oyi77/1ai-skills. It costs 61 tokens per session (1,174 once invoked), scanned A, original, MIT.

A memory-forensics guide for finding heap-spray attacks in process memory dumps. Heap spraying is an exploit technique that fills many memory areas with attacker-controlled data so malicious code is more likely to run.

In plain words
What is it for?
Use it with Volatility3 to inspect memory dumps, identify suspicious allocations and shellcode, and investigate exploitation attempts.
Why use it?
The relevant evidence may be buried in large memory allocations and virtual-address regions rather than in ordinary files or logs. Scanning for repeated patterns and embedded shellcode helps locate it.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the 1ai-skills plugin — 209 skills, 4 commands shipped together

Good fit Use it with Volatility3 to inspect memory dumps, identify suspicious allocations and shellcode, and investigate exploitation attempts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oyi77/1ai-skills/analyzing-heap-spray-exploitation
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add oyi77/1ai-skills --skill analyzing-heap-spray-exploitation
Clone the repo
git clone --depth 1 https://github.com/oyi77/1ai-skills

Made for: Claude Code.

Or install 1ai-skills, the plugin that ships this one along with the rest of its 209 skills, 4 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for analyzing-heap-spray-exploitation

README.md
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Your own site
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Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,174 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.01174
Opus 5 $0.00030 $0.00587
Sonnet 5 $0.00012 $0.00235
Haiku 4.5 $0.00006 $0.00117

Measured 8d ago against content hash 2b07a81405fc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

analyzing-heap-spray-exploitation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

cybersecurity/analyzing-heap-spray-exploitation/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Trigger phrases:

  • "analyzing heap spray exploitation"

  • "Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins "

  • 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

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
  1. Scope and authorize — confirm written authorization and define target boundaries
  2. Reconnaissance — enumerate targets, services, and potential attack surfaces
  3. Exploitation — attempt exploitation of identified vulnerabilities within scope
  4. Post-exploitation — document access level, lateral movement, and data exposure
  5. Report and remediate — compile findings with reproduction steps and fix recommendations

Read the full file on GitHub · 126 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 126 lines · 61 tokens per session scan A 2b07a81405fc

Subscribe to this mod's changes

analyzing-heap-spray-exploitation is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 1,174 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

Related

Other skills, from other repositories

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.

mukul975/Anthropic-Cybersecurity-Skills · 46 tokens

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.

26zl/cybersec-toolkit · 46 tokens

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.

pinkpixel-dev/skills-collection-1 · 46 tokens

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.

Mikaru0Mystic/sectinel · 46 tokens

analyzing-linux-kernel-rootkits

Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (checksyscall, lsmod, hiddenmodules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.

xalgorix/xalgorix · 65 tokens

analyzing-heap-spray-exploitation

A security-analysis skill for finding possible heap-spray attacks in a computer’s memory dump. A heap-spray attack fills large memory areas with repeated data to increase the chance that harmful code runs through a software vulnerability.

killvxk/cybersecurity-skills-zh · 59 tokens