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.
npx agentmods add skills/jessefmoore/offensive-claude-code/malware-analysisnpx skills add jessefmoore/offensive-claude-code --skill malware-analysisgit clone --depth 1 https://github.com/jessefmoore/offensive-claude-codeWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00028 | $0.01648 |
| Opus 5 | $0.00014 | $0.00824 |
| Sonnet 5 | $0.00006 | $0.00330 |
| Haiku 4.5 | $0.00003 | $0.00165 |
Grade A, and why
malware-analysis 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Malware Analysis
When to Activate
- Analyzing suspicious binaries or scripts
- Writing detection signatures (YARA, Snort, Sigma)
- Understanding malware capabilities and C2 protocols
- Unpacking protected/obfuscated samples
- Incident response — determining scope of compromise
- Threat intelligence — attributing samples to threat actors
Static Analysis
Initial Triage
# File identification
file sample.exe
sha256sum sample.exe
ssdeep sample.exe # fuzzy hash for similarity
# PE analysis
pestudio sample.exe # GUI: imports, strings, indicators
python3 -c "import pefile; pe=pefile.PE('sample.exe'); print(pe.dump_info())"
# Strings
floss sample.exe # FLARE Obfuscated String Solver (decodes obfuscated strings)
strings -n 8 sample.exe | grep -iE '(http|ftp|cmd|powershell|reg|schtask|wmic)'
# Capability detection
capa sample.exe # maps to MITRE ATT&CK techniques
# Output: persistence/registry, defense-evasion/process-injection, etc.
# Import analysis
python3 -c "
import pefile
pe = pefile.PE('sample.exe')
for entry in pe.DIRECTORY_ENTRY_IMPORT:
print(entry.dll.decode())
for imp in entry.imports:
print(f' {imp.name.decode() if imp.name else hex(imp.ordinal)}')
"
Suspicious Indicators
# High-confidence malicious:
- VirtualAlloc + WriteProcessMemory + CreateRemoteThread (process injection)
- NtUnmapViewOfSection + NtMapViewOfSection (process hollowing)
- SetWindowsHookEx (keylogger/hooking)
- CryptEncrypt with hardcoded key (ransomware)
- InternetOpen + InternetConnect + HttpSendRequest (C2 communication)
- RegSetValueEx on Run keys (persistence)
- CreateToolhelp32Snapshot + Process32First (process enumeration)
# Packing indicators:
- High entropy sections (>7.0)
- Few imports (only LoadLibrary/GetProcAddress)
- Section names: UPX, .packed, .vmp, .themida
- Entry point in non-standard section
Dynamic Analysis
Sandbox Setup
# Isolated VM with:
# - Snapshot before execution
# - Network capture (inetsim for fake services)
# - Process monitoring (procmon, API Monitor)
# - File system monitoring (sysmon)
# - Registry monitoring
# Inetsim (fake internet services)
inetsim --config /etc/inetsim/inetsim.conf
# FakeDNS
python3 fakedns.py -c 192.168.1.100 # redirect all DNS to analysis host
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.
- 2d ago First seen · 217 lines · 28 tokens per session scan A 4ae3753e9b0b
malware-analysis is a skill published in the GitHub repository jessefmoore/offensive-claude-code (2 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 1,648 once invoked, about $0.0001 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 2026-08-31.
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