cryptorugmunch
628c1d2a10
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PHASE 2.3 (AUDIT-2026-Q3.md):
Task 1 — Wire-in Wave 3 (1 router mounted, 2 deferred):
- app.routers.unified_scanner_router mounted at /api/v2/scanner/* (2 routes:
POST /api/v2/scanner/token/scan, POST /api/v2/scanner/wallet/scan).
Refactored prefix from /api/v2 -> /api/v2/scanner to avoid future conflicts
with the v1 /api/v1/scanner/ stub.
- app.routers.unified_wallet_scanner DEFERRED (no router APIRouter attribute;
library module consumed by unified_scanner_router via get_wallet_scanner()).
- app.routers.admin_extensions DEFERRED (DORMANT per audit; 25 routes at
/api/v1/admin/* would shadow /api/v1/admin/alerts_webhook).
Task 2 — Archive 136 dead-code files to app/_archive/legacy_2026_07/:
- 73 routers in app/routers/ (reach graph showed zero reach into mount.py).
- 63 flat app/*.py (domain modules never imported by live code).
- 1 file RESTORED post-archive: app/routers/x402_bridge_health.py (caught by
tests/unit/test_bridge_health.py which directly imports it; reach graph
considered tests/ only as transitive reach — to be patched in next cycle).
Forced-LIVE (NOT archived per user directive):
- app/ai_pipeline_v3.py (3 importers in audit window, importers themselves DEAD)
- app/splade_bm25.py (LIVE via app.rag_service)
- app/wallet_manager_v2.py (LIVE via x402_enforcement, x402_tools, sweep_all, sweep_now)
- app/crypto_embeddings.py (NOT in audit ARCHIVE list; heavy import graph)
Verification (forward-import closure from mount.py + main.py + factory.py + lifespan.py):
- imports = 348 app.* modules
- reached = 194 files reachable from roots
- archive set = audit_dead (186) - reached - forced_live (4) - test_live (1) = 136
- Net delta: 136 files moved, 44,932 LOC reduction, 293->295 active routes (+2 from Wave 3)
pyproject.toml updates:
- setuptools.packages.find: added exclude for app._archive*
- ruff.extend-exclude: added "app/_archive/"
- mypy.exclude: added "app/_archive/"
Smoke test: pytest tests/ — 817 passed, 3 pre-existing failures unchanged
(0 new failures; 0 routes lost; all 4 forced-LIVE files still importable).
Restoration: git mv app/_archive/legacy_2026_07/<name>.py <original-path>
and add the import to app/mount.py ROUTER_MODULES.
Refs: AUDIT-2026-Q3.md /home/dev/pry/rmi-final-deadcode-2026-07-06.md
116 lines
3.4 KiB
Python
116 lines
3.4 KiB
Python
"""Content Moderation Pipeline - AI-powered spam/scam/NSFW detection for user content."""
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import os
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import re
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import httpx
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from fastapi import APIRouter
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from pydantic import BaseModel
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router = APIRouter(prefix="/api/v1/moderation", tags=["moderation"])
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OLLAMA = os.getenv("OLLAMA_HOST", "http://localhost:11434")
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BLOCKED_PATTERNS = [
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(r"(?i)(buy|sell|trade).*\b(signal|call)\b", "trading_signal"),
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(r"(?i)(\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b)", "ip_address"),
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(r"(?i)\b(0x[a-fA-F0-9]{40})\b.*\b(private.?key|seed.?phrase|mnemonic|password)\b", "wallet_phishing"),
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(r"(?i)(airdrop|giveaway|free.*token).*\b(claim|connect|verify)\b", "scam_airdrop"),
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(r"(https?://(?!rugmunch\.io|polymarket\.com|dexscreener\.com)[^\s]+)", "external_link"),
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]
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class ModerationRequest(BaseModel):
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text: str
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user_id: str = "anonymous"
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context: str = "comment" # comment, post, review, chat
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class ModerationResult(BaseModel):
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approved: bool
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risk_score: int # 0-100
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flags: list[str]
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reason: str = ""
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async def _ai_classify(text: str) -> dict:
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"""Use Ollama to classify content."""
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try:
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async with httpx.AsyncClient(timeout=15) as c:
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r = await c.post(
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f"{OLLAMA}/api/generate",
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json={
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"model": "qwen2.5-coder:7b",
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"prompt": f"Classify this crypto-related content as SAFE, SPAM, SCAM, or NSFW. Answer with one word only.\n\nContent: {text[:500]}\n\nClassification:",
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"stream": False,
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"options": {"num_predict": 5, "temperature": 0.1},
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},
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)
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if r.status_code == 200:
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response = r.json().get("response", "").strip().upper()
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return {"ai_verdict": response, "ai_used": True}
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except Exception:
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pass
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return {"ai_verdict": "UNKNOWN", "ai_used": False}
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@router.post("/check")
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async def moderate_content(req: ModerationRequest):
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"""Check content for spam, scams, NSFW, and policy violations."""
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flags = []
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risk = 0
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# Pattern-based detection
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for pattern, flag_type in BLOCKED_PATTERNS:
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if re.search(pattern, req.text):
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flags.append(flag_type)
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risk += 25
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# Length checks
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if len(req.text) < 5:
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flags.append("too_short")
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risk += 10
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if len(req.text) > 10000:
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flags.append("too_long")
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risk += 5
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# AI classification
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ai = await _ai_classify(req.text)
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ai_verdict = ai["ai_verdict"]
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if "SCAM" in ai_verdict:
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flags.append("ai_scam")
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risk += 40
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elif "SPAM" in ai_verdict:
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flags.append("ai_spam")
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risk += 25
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elif "NSFW" in ai_verdict:
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flags.append("ai_nsfw")
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risk += 50
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approved = risk < 40
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reason = "Content approved" if approved else f"Flagged: {', '.join(flags)}"
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return {
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"approved": approved,
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"risk_score": min(100, risk),
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"flags": flags,
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"reason": reason,
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"ai_classification": ai_verdict,
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}
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@router.get("/stats")
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async def moderation_stats():
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return {
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"patterns_checked": len(BLOCKED_PATTERNS),
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"ai_model": "qwen2.5-coder:7b",
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"categories": [
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"trading_signal",
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"wallet_phishing",
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"scam_airdrop",
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"external_link",
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"ai_scam",
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"ai_spam",
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"ai_nsfw",
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],
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}
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