Cylera Devices

1. Detect credentials and parse arguments (run in parallel if arguments are known)

If $ARGUMENTS is provided, run both sub-steps simultaneously. Otherwise, run step 1a first, then ask.

1a) Detect credentials — single Bash call:

(which doppler 2>/dev/null && echo "doppler_found") || \
(which op 2>/dev/null && [ -n "$OP_ENVIRONMENT_ID" ] && echo "op_found") || \
([ -f .env ] && echo "dotenv_found") || \
echo "none"

• doppler_found → use doppler run -- as the command prefix
• op_found → use op run --environment "$OP_ENVIRONMENT_ID" -- as the command prefix
• dotenv_found → use no prefix
• none → offer to run cylera init. If the user agrees, run it and use no prefix. If they decline, stop.

1b) Parse arguments:

Extract filters from $ARGUMENTS:

• If a token matches class, type, vendor, or os (case-insensitive), treat the next token as its value
• A bare word that doesn't follow a keyword is treated as a class value (common shorthand, e.g. Medical)
• Unknown tokens: ignore

2. Run the fetch-and-export script

Substitute CLASS, TYPE, VENDOR, OS, and PREFIX before running. Use empty string for unused filters.

PREFIX="<prefix>" python3 - << 'PYEOF'
import subprocess, json, csv, sys, datetime, os
from pathlib import Path
from collections import Counter

device_class = "<class>"   # e.g. "Medical" or ""
device_type = "<type>"     # e.g. "X-Ray" or ""
vendor = "<vendor>"        # e.g. "Philips" or ""
device_os = "<os>"         # e.g. "Windows" or ""
prefix = os.environ.get("PREFIX", "").split() if os.environ.get("PREFIX") else []

date = datetime.date.today().isoformat()

parts = []
if device_class:
    parts.append(device_class.lower().replace(" ", "-"))
if device_type:
    parts.append(device_type.lower().replace(" ", "-"))
if vendor:
    parts.append(vendor.lower().replace(" ", "-"))
if device_os:
    parts.append(device_os.lower().replace(" ", "-"))
slug = "-".join(parts) if parts else "all"
filepath = Path.cwd() / f"cylera-devices-{slug}-{date}.csv"

columns = ["hostname", "ip_address", "mac_address", "serial_number",
           "type", "class", "os", "vendor", "model",
           "location", "risk", "vlan", "last_seen", "first_seen"]

cmd = prefix + ["cylera", "devices", "--page-size", "100"]
if device_class:
    cmd += ["--class", device_class]
if device_type:
    cmd += ["--type", device_type]
if vendor:
    cmd += ["--vendor", vendor]
if device_os:
    cmd += ["--os", device_os]

rows = []
page = 0

while True:
    result = subprocess.run(
        cmd + ["--page", str(page)],
        capture_output=True, text=True
    )
    if result.returncode != 0:
        print(json.dumps({"error": result.stderr}))
        sys.exit(1)
    data = json.loads(result.stdout)
    devices = data.get("devices", [])
    for d in devices:
        last_seen_ts = d.get("last_seen")
        first_seen_ts = d.get("first_seen")
        last_seen_str = datetime.datetime.fromtimestamp(last_seen_ts).strftime("%Y-%m-%d") if last_seen_ts else ""
        first_seen_str = datetime.datetime.fromtimestamp(first_seen_ts).strftime("%Y-%m-%d") if first_seen_ts else ""
        rows.append({
            "hostname": d.get("hostname", ""),
            "ip_address": d.get("ip_address", ""),
            "mac_address": d.get("mac_address", ""),
            "serial_number": d.get("serial_number", ""),
            "type": d.get("type", ""),
            "class": d.get("class", ""),
            "os": d.get("os", ""),
            "vendor": d.get("vendor", ""),
            "model": d.get("model", ""),
            "location": d.get("location", ""),
            "risk": d.get("risk", ""),
            "vlan": d.get("vlan", ""),
            "last_seen": last_seen_str,
            "first_seen": first_seen_str,
        })
    if len(devices) < 100:
        break
    page += 1

with open(filepath, "w", newline="") as f:
    writer = csv.DictWriter(f, fieldnames=columns)
    writer.writeheader()
    writer.writerows(rows)

class_counter = Counter(r["class"] for r in rows)
vendor_counter = Counter(r["vendor"] for r in rows)
type_counter = Counter(r["type"] for r in rows)

print(json.dumps({
    "total_devices": len(rows),
    "filepath": str(filepath),
    "pages_fetched": page + 1,
    "class_distribution": dict(class_counter),
    "top_vendors": vendor_counter.most_common(5),
    "top_types": type_counter.most_common(5),
}))
PYEOF

Parse the small JSON summary that the script prints.

3. Report

Tell the user:

• Total devices exported and active filters applied
• The full path to the CSV file
• Class, top vendor, and top device type breakdown
• Any notable observations (e.g., large number of unclassified devices, dominant vendor)

4. Offer to open the CSV

Ask the user if they would like to open the CSV file. If yes, run:

open "<filepath>"