Extract DPAPI-protected secrets such as credentials and browser data offline and online.
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andycungkrinx91/konoha102026년 10월 21일 업데이트
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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.
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설치 방법 보기포함된 파일(3)
- SKILL.md2.3 KB
- references/api-reference.md2.2 KB
- scripts/agent.py8.1 KB
SKILL.md(원문)
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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
volatility3framework 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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