Fixed confirmed findings before public exposure: HIGH: - upload filename path traversal → store.safe_name() strips to basename - login rate-limit XFF bypass → key on request.client.host + per-username bucket; auth.check_login() burns bcrypt time on unknown users (no enumeration) - cross-user read access → per-user isolation: guests see/use/download/delete only their own assets & jobs (owner sees all); WS job events scoped per-user MEDIUM: - unbounded upload read → bounded chunked streaming to the 1GB cap - asset member path check → Path.is_relative_to boundary + ownership gate - WS token-in-query-string leak → session-cookie-only WS auth LOW: - retry_job bypassed the per-user job cap → cap now checked on retry - wholesale API-key injection → env_for_operator injects a paid key only to operators that declare it (guest local jobs never receive fal/OpenRouter keys) - session revocation → users.session_epoch, bumped on password change - int() 500s → 400; net-lane defense-in-depth (guests blocked by requires_env AND resources==net, so a mis-tagged paid op is still blocked) + public /api/health for serve.sh & proxy; docs/VPS.md; mb MB_TOKEN bearer auth tests/smoke.sh: 34 checks passing incl. all new hardening. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
135 lines
5.2 KiB
Python
135 lines
5.2 KiB
Python
"""System snapshot for the dashboard — CPU/RAM/disk (psutil), Apple GPU (macmon,
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no sudo), queue/lane occupancy, recent jobs. Everything cached so refresh-spam is
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cheap; the slow bits (du of data/ and HF cache) refresh at most every 5 min."""
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import json
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import os
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import shutil
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import subprocess
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import time
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from pathlib import Path
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import psutil
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from . import db, store
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_cache: dict = {}
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def _cached(key: str, ttl: float, fn):
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now = time.time()
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hit = _cache.get(key)
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if hit and now - hit[0] < ttl:
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return hit[1]
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val = fn()
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_cache[key] = (now, val)
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return val
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def _macmon_gpu():
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def fetch():
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try:
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out = subprocess.run(["macmon", "pipe", "-s", "1"], capture_output=True,
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text=True, timeout=6).stdout.strip().splitlines()
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sample = json.loads(out[-1])
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gpu = sample.get("gpu_usage") or [0, 0.0]
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return {"util_percent": round(gpu[1] * 100, 1),
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"power_w": round(sample.get("gpu_power", 0.0), 1),
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"temp_c": round(sample.get("temp", {}).get("gpu_temp_avg", 0.0), 1),
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"source": "macmon"}
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except FileNotFoundError:
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return {"source": "unavailable", "hint": "brew install macmon for GPU stats"}
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except Exception as e:
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return {"source": "unavailable", "hint": str(e)[:80]}
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return _cached("gpu", 5.0, fetch)
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def _du_gb(path: Path):
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try:
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out = subprocess.run(["du", "-sk", str(path)], capture_output=True,
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text=True, timeout=60).stdout.split()
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return round(int(out[0]) / (1024 * 1024), 1)
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except Exception:
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return None
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def _lanes(con, runner):
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limits = getattr(runner, "LANE_LIMITS", None) or {"gpu": 1, "cpu": 3, "net": 6}
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lanes = {k: {"limit": v, "running": 0, "queued": 0} for k, v in limits.items()}
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rows = con.execute("SELECT operator, status FROM jobs WHERE status IN ('queued','running')").fetchall()
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for r in rows:
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lane = runner.lane_of(r["operator"])
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if lane not in lanes:
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lane = "cpu"
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lanes[lane]["running" if r["status"] == "running" else "queued"] += 1
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return lanes
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def _jobs_24h(con):
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cutoff = time.time() - 86400
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rows = con.execute(
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"SELECT operator, status FROM jobs WHERE finished_at >= ?", (cutoff,)).fetchall()
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out = {"done": 0, "error": 0, "cancelled": 0, "by_operator": {}}
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for r in rows:
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out[r["status"]] = out.get(r["status"], 0) + 1
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out["by_operator"][r["operator"]] = out["by_operator"].get(r["operator"], 0) + 1
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return out
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def snapshot(con, runner) -> dict:
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def stats():
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per_core = psutil.cpu_percent(interval=0.15, percpu=True)
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vm = psutil.virtual_memory()
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du = shutil.disk_usage(str(db.DATA))
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try:
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load1 = os.getloadavg()[0]
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except OSError:
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load1 = 0.0
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return {
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"cpu": {"percent": round(sum(per_core) / len(per_core), 1),
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"cores": len(per_core), "per_core": [round(c, 0) for c in per_core],
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"load1": round(load1, 2)},
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"ram": {"used_gb": round((vm.total - vm.available) / 1e9, 1),
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"total_gb": round(vm.total / 1e9, 1), "percent": vm.percent},
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"disk": {"free_gb": round(du.free / 1e9, 1), "total_gb": round(du.total / 1e9, 1)},
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"uptime_s": round(time.time() - psutil.boot_time()),
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}
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base = _cached("stats", 5.0, stats)
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hf = Path.home() / ".cache" / "huggingface"
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return {
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**base,
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"gpu": _macmon_gpu(),
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"lanes": _lanes(con, runner),
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"jobs_24h": _jobs_24h(con),
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"data_dir_gb": _cached("data_du", 300.0, lambda: _du_gb(db.DATA)),
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"hf_cache_gb": _cached("hf_du", 300.0, lambda: _du_gb(hf) if hf.exists() else None),
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"operators": len(runner.operators),
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}
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def recent_jobs(con, runner, limit: int = 20, user_id: str | None = None) -> list[dict]:
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cutoff = time.time() - 86400
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if user_id is None: # owner: all users
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rows = con.execute(
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"SELECT * FROM jobs WHERE status IN ('done','error','cancelled') "
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"AND finished_at >= ? ORDER BY finished_at DESC LIMIT ?", (cutoff, limit)).fetchall()
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else: # guest: only their own
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rows = con.execute(
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"SELECT * FROM jobs WHERE status IN ('done','error','cancelled') "
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"AND finished_at >= ? AND user_id = ? ORDER BY finished_at DESC LIMIT ?",
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(cutoff, user_id, limit)).fetchall()
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umap = {u_id: name for u_id, name in
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con.execute("SELECT id, username FROM users").fetchall()}
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out = []
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for r in rows:
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j = db.row_to_dict(r)
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outs = con.execute(
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"SELECT id, kind, name FROM assets WHERE parent_job = ?", (j["id"],)).fetchall()
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dur = (j["finished_at"] - j["started_at"]) if j.get("started_at") and j.get("finished_at") else None
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out.append({
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"id": j["id"], "operator": j["operator"], "status": j["status"],
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"username": umap.get(j.get("user_id")) or ("—" if j.get("user_id") else "owner"),
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"duration_s": round(dur, 1) if dur else None,
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"outputs": [{"id": o["id"], "kind": o["kind"], "name": o["name"]} for o in outs],
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})
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return out
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