Borrowing it
Nothing to install: this file belongs to OLGTX303/find-evil-sift-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/OLGTX303/find-evil-sift-agent/master/CLAUDE.mdgit clone --depth 1 https://github.com/OLGTX303/find-evil-sift-agentWrote 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.
[](https://agentmods.dev/instructions/olgtx303/find-evil-sift-agent/claude-md)<a href="https://agentmods.dev/instructions/olgtx303/find-evil-sift-agent/claude-md"><img src="https://agentmods.dev/badge/instructions/olgtx303/find-evil-sift-agent/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/olgtx303/find-evil-sift-agent/claude-md"><img src="https://agentmods.dev/badge/instructions/olgtx303/find-evil-sift-agent/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01000 | $0.01000 |
| Opus 5 | $0.00500 | $0.00500 |
| Sonnet 5 | $0.00200 | $0.00200 |
| Haiku 4.5 | $0.00100 | $0.00100 |
Grade B, and why
find-evil-sift-agent CLAUDE.md scanned grade B with 1 finding 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 10d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
│ └── ssh_client.py ← asyncssh helper with sudo support How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FIND EVIL! — SIFT Forensic AI Agent
Project structure
sift-agent/
├── orchestrator.py ← Main autonomous IR agent (gpt-5.4-mini via OpenAI-compatible API)
├── setup_sift_vm.py ← One-time VM setup: start, share evidence, install deps
├── src/sift_mcp/
│ ├── server.py ← MCP server exposing SIFT tools
│ ├── tools.py ← 18 forensic tool implementations (SSH → SIFT VM)
│ └── ssh_client.py ← asyncssh helper with sudo support
└── findings/ ← Auto-created: agent_execution_log.jsonl + findings_report.json
Evidence (VANKO case)
find/VANKO/surface_physical.E01-E21— Microsoft Surface 3 disk image (119GB EWF)find/VANKO/vanko-c-drive.CYLR.7z— Cellebrite C-drive extractionfind/sift-2026-04-22.ova— SIFT Workstation VM
One-time setup
# 1. Import OVA (already done via ovftool)
# VMX at: F:\5Gcase\hackton\SIFT-VM\SIFT-2026\SIFT-2026.vmx
# 2. Install sift-agent
pip install -e .
# 3. Start and configure SIFT VM
python setup_sift_vm.py
# 4. Set environment
set OPENAI_API_KEY=your_key
set OPENAI_BASE_URL=https://api.456478.xyz/
set SIFT_HOST=<vm_ip>
set SIFT_PORT=22 # or 2222 if using NAT
set SIFT_USER=sansforensics
set SIFT_PASS=forensics
set EVIDENCE_DIR=/cases/VANKO
Running the investigation
python orchestrator.py --output-dir ./findings
The agent will autonomously:
- Mount the E01 image via ewfmount
- Enumerate users and system info
- Scan for suspicious executables
- Parse registry Run keys (persistence)
- Extract logon events from Security.evtx
- Run YARA malware detection
- Build a timeline with log2timeline
- Produce
findings/findings_report.json
MCP server (standalone)
# Register in Claude Code
claude mcp add sift-forensic -e SIFT_HOST=<ip> -e SIFT_PORT=22 -- sift-mcp
# Then ask Claude: "Mount the VANKO image and find evil"
Architecture
┌─────────────────────────────────────────────┐
│ Windows Host (Claude Code) │
│ orchestrator.py + gpt-5.4-mini (OpenAI-compat API) │
│ ┌─────────────────────────────────────┐ │
│ │ sift-forensic-mcp (stdio MCP) │ │
│ │ 18 forensic tool definitions │ │
│ └──────────────┬──────────────────────┘ │
└─────────────────┼───────────────────────────┘
│ asyncssh (port 22/2222)
┌─────────────────▼───────────────────────────┐
│ SIFT Workstation VM (VMware NAT) │
│ Ubuntu 22.04 + 200+ IR tools │
│ ┌───────────────────────────────────────┐ │
│ │ /cases/VANKO/surface_physical.E01 │ │
│ │ ewfmount → /mnt/ewf/ewf1 │ │
│ │ kpartx → /dev/mapper/loop0p3 │ │
│ │ /mnt/windows/ (NTFS mounted) │ │
│ └───────────────────────────────────────┘ │
└─────────────────────────────────────────────┘
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.
- 10d ago First seen · 103 lines · 1,000 tokens per session scan B 75196881f27b
find-evil-sift-agent CLAUDE.md is an instructions file published in the GitHub repository OLGTX303/find-evil-sift-agent (0 stars, last pushed 2mo ago), licensed MIT. It adds 1,000 tokens to every session, about $0.0050 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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