菜单
Malware analysis techniques — static triaging, dynamic sandboxing, PE/.NET analysis, C2 protocol identification. Use when analyzing a suspicious binary, script, document, or network capture from a potentially compromised system.
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基于 SOC 职业分类
| name | malware-analysis |
| description | Malware analysis techniques — static triaging, dynamic sandboxing, PE/.NET analysis, C2 protocol identification. Use when analyzing a suspicious binary, script, document, or network capture from a potentially compromised system. |
| license | MIT |
| compatibility | Requires filesystem-based agent with bash, Python 3, YARA, and analysis tools (pefile, oletools, Cuckoo/CAPE). |
| allowed-tools | Bash Read Write Edit Glob Grep WebSearch |
| metadata | {"user-invocable":"true","argument-hint":"<sample-path>"} |
| Task | Document |
|---|---|
| PE structure, YARA rules, shellcode disassembly, script deobfuscation | Static Triaging |
| Sandbox setup, strace/ltrace, process injection detection, sandbox evasion | Dynamic Sandboxing |
| PE analysis, .NET decompilation, malware config extraction, packer identification | PE / .NET Analysis |
| Beacon detection, DGA identification, Cobalt Strike decoding, protocol analysis | C2 Protocols |
file sample
strings sample | grep -iE '(http|https|\.exe|cmd|powershell|key|config|password)'
xxd sample | head -20
md5sum sample && sha256sum sample
rule Suspicious_Indicators {
strings:
$p1 = "cmd.exe" nocase
$p2 = "powershell -enc" nocase
$p3 = "CreateRemoteThread" nocase
$p4 = "VirtualAllocEx" nocase
$mz = {4D 5A}
condition:
$mz and 2 of ($p*)
}
import pefile
pe = pefile.PE("sample.exe")
print(f"Sections: {len(pe.sections)}")
for s in pe.sections:
print(f" {s.Name.decode().strip(chr(0))}: raw={s.SizeOfRawData} virt={s.Misc_VirtualSize} entropy={s.get_entropy():.2f}")
print(f"Imports: {[d.dll.decode() for d in pe.DIRECTORY_ENTRY_IMPORT]}")
print(f"Entry: 0x{pe.OPTIONAL_HEADER.AddressOfEntryPoint:x}")
Security research methodology — 5-phase workflow (intake → recon → enum → hunt → report). Routes to specialized technique modules. Use when the user asks to audit, penetration test, bug bounty, find vulnerabilities, exploit a target, or perform any security assessment.
AI/ML attack techniques — prompt injection, indirect/RAG poisoning, tool-calling manipulation, adversarial examples, model extraction, membership inference, training data extraction. Use when the target involves LLM agents, chatbots, ML model APIs, image classifiers, or federated learning systems.
Binary exploitation techniques — buffer overflow, format string, heap exploitation, ROP, kernel exploitation, sandbox escape, shellcode. Use when the target is a native binary (ELF/PE), remote service with memory corruption, or kernel module. Requires pwntools, GDB, and binary analysis tools.
Cryptography attack techniques — RSA, ECC, symmetric ciphers, hash collisions, PRNG attacks, lattice/LWE. Use when the challenge involves encryption, decryption, key recovery, nonce reuse, padding oracles, or cryptanalysis of custom schemes.
Forensic analysis techniques — disk, memory, network, steganography, side-channel analysis. Use when given a disk image (.dd, .E01, .raw), memory dump (.vmem, .raw), packet capture (.pcap, .pcapng), image/audio file with hidden data, or side-channel trace.
Open Source Intelligence techniques — social media investigation, geolocation from images, DNS/web reconnaissance. Use when gathering intelligence from publicly available sources, identifying a person/location/organization, or performing passive reconnaissance.