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Author SHA1 Message Date
Shadowbroker 52a694c38f Merge pull request #315 from BigBodyCobain/feat/aishub-fallback
feat(ais): AISHub REST fallback when AISStream is offline (20-min polling)
2026-05-23 07:12:46 -06:00
32 changed files with 189 additions and 1684 deletions
-5
View File
@@ -36,10 +36,5 @@
"ShadowBroker_v0.9.79.zip": "f6877c1d66614525315ea82636ce9f7b41178332c4dbf90d27431a1ea1d9cd47",
"ShadowBroker_0.9.79_x64-setup.exe": "f7b676ada45cac7da05868b0a353678c9ee700e3abcf456a7c0c038c36da446f",
"ShadowBroker_0.9.79_x64_en-US.msi": "e0713c3cdda184cfbea750bfac0d62a35678fec00847e6476f2cac8e7e42046e"
},
"v0.9.8": {
"ShadowBroker_v0.9.8.zip": "d506f6b8462ccb12096f0cd9462233be58928094240416b65fb3127bdd1f3820",
"ShadowBroker_0.9.8_x64-setup.exe": "1115d1f5cf37edd03ea2c21d821c7626e1bf3319c990402aaa0293bca46fea67",
"ShadowBroker_0.9.8_x64_en-US.msi": "d4be4cb68c3e6409fff54c225acdcdd08e27d5d6d2b31616d78d2a4f6812991d"
}
}
+1 -1
View File
@@ -14,7 +14,7 @@ from dataclasses import dataclass, field
from typing import Any
from json import JSONDecodeError
APP_VERSION = "0.9.8"
APP_VERSION = "0.9.79"
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
+2 -2
View File
@@ -7,7 +7,7 @@ py-modules = []
[project]
name = "backend"
version = "0.9.8"
version = "0.9.79"
requires-python = ">=3.10"
dependencies = [
"apscheduler==3.10.3",
@@ -43,7 +43,7 @@ dev = ["pytest>=8.3.4", "pytest-asyncio==0.25.0", "ruff>=0.9.0", "black>=24.0.0"
[tool.ruff.lint]
# The current backend carries historical style debt in large legacy modules.
# Keep CI focused on actionable correctness checks for the v0.9.8 release.
# Keep CI focused on actionable correctness checks for the v0.9.79 release.
ignore = ["E401", "E402", "E701", "E731", "E741", "F401", "F402", "F541", "F811", "F841"]
[tool.black]
+2 -2
View File
@@ -1590,7 +1590,7 @@ async def agent_tool_manifest(request: Request):
return {
"ok": True,
"version": "0.9.8",
"version": "0.9.79",
"access_tier": access_tier,
"available_commands": available_commands,
"transport": {
@@ -2226,7 +2226,7 @@ async def api_capabilities(request: Request):
access_tier = str(get_settings().OPENCLAW_ACCESS_TIER or "restricted").strip().lower()
return {
"ok": True,
"version": "0.9.8",
"version": "0.9.79",
"auth": {
"method": "HMAC-SHA256",
"headers": ["X-SB-Timestamp", "X-SB-Nonce", "X-SB-Signature"],
+1 -1
View File
@@ -8,7 +8,7 @@ from services.data_fetcher import get_latest_data
from services.schemas import HealthResponse
import os
APP_VERSION = os.environ.get("_HEALTH_APP_VERSION", "0.9.8")
APP_VERSION = os.environ.get("_HEALTH_APP_VERSION", "0.9.79")
router = APIRouter()
+2 -7
View File
@@ -11,13 +11,8 @@ DEFAULT_TRAIL_TTL_S = 300 # 5 min - trail TTL for non-tracked flights
HOLD_PATTERN_DEGREES = 300 # Total heading change to flag holding pattern
GPS_JAMMING_NACP_THRESHOLD = 8 # NACp below this = degraded GPS signal
GPS_JAMMING_GRID_SIZE = 1.0 # 1 degree grid for aggregation
# Tuned 2026-05: previously 0.30 / 5 aircraft which — combined with the
# -1 noise cushion in the detector AND the pre-fix nac_p==0 filter that
# discarded jamming victims — meant the layer almost never lit up.
# Lowering the bar so genuine jamming zones with sparser ADS-B coverage
# clear (eastern Med, Russia/Ukraine border, Iran/Iraq).
GPS_JAMMING_MIN_RATIO = 0.20 # 20% degraded aircraft to flag zone
GPS_JAMMING_MIN_AIRCRAFT = 3 # Min aircraft in grid cell for statistical significance
GPS_JAMMING_MIN_RATIO = 0.30 # 30% degraded aircraft to flag zone
GPS_JAMMING_MIN_AIRCRAFT = 5 # Min aircraft in grid cell for statistical significance
# ─── Network & Circuit Breaker ──────────────────────────────────────────────
CIRCUIT_BREAKER_TTL_S = 120 # Skip domain for 2 min after total failure
+2 -18
View File
@@ -777,19 +777,6 @@ def start_scheduler():
misfire_grace_time=60,
)
# Flight observation pruning — drops icao24 → first_seen_at entries we
# haven't seen in an hour. Same cadence as AIS prune for symmetry; the
# per-tick scan is O(in-flight aircraft) so it's cheap.
from services.fetchers.flight_observations import prune as _prune_flight_observations
_scheduler.add_job(
lambda: _run_task_with_health(_prune_flight_observations, "prune_flight_observations"),
"interval",
minutes=5,
id="flight_observation_prune",
max_instances=1,
misfire_grace_time=60,
)
# AISHub REST fallback — slow polling when the AISStream WebSocket
# primary is offline. Configurable interval via
# AISHUB_POLL_INTERVAL_MINUTES env (default 20 min). Operator must
@@ -993,19 +980,16 @@ def start_scheduler():
misfire_grace_time=600,
)
# UAP sightings (NUFORC) — weekly on Mondays at 12:00 UTC. The layer is a
# rolling last-60-days digest; refreshing once a week is enough cadence
# for human-readable map exploration and keeps load on nuforc.org light.
# UAP sightings (NUFORC) — daily at 12:00 UTC
_scheduler.add_job(
lambda: _run_task_with_health(
lambda: fetch_uap_sightings(force_refresh=True),
"fetch_uap_sightings",
),
"cron",
day_of_week="mon",
hour=12,
minute=0,
id="uap_sightings_weekly",
id="uap_sightings_daily",
max_instances=1,
misfire_grace_time=3600,
)
@@ -1383,21 +1383,10 @@ def _build_uap_sightings_from_hf_mirror() -> list[dict]:
This is a resilience fallback for local/Windows runs where nuforc.org is
Cloudflare-gated and the Mapbox token is not configured. It is not as fresh
as the live NUFORC AJAX feed, but it keeps the layer visible and cached.
Date-cutoff guard: the kcimc/NUFORC HF dataset is a static snapshot whose
maintainer refreshes it sporadically. Without a cutoff, sorting by
occurred-desc and taking the top N rows returns whatever the mirror's
newest rows happen to be which can be years old if the snapshot is
stale. We apply the same ``_NUFORC_RECENT_DAYS`` window the live path
uses (60 days). If the HF mirror has nothing inside the window we return
``[]`` rather than silently serving 3-year-old "newest" rows.
"""
from services.fetchers.nuforc_enrichment import _HF_CSV_URL, _parse_date
from services.geocode_validate import coord_in_country
cutoff_dt = datetime.utcnow() - timedelta(days=_NUFORC_RECENT_DAYS)
cutoff_str = cutoff_dt.strftime("%Y-%m-%d")
try:
response = fetch_with_curl(_HF_CSV_URL, timeout=180, follow_redirects=True)
if not response or response.status_code != 200:
@@ -1411,7 +1400,6 @@ def _build_uap_sightings_from_hf_mirror() -> list[dict]:
return []
candidates: list[dict] = []
stale_rows_dropped = 0
try:
reader = csv.DictReader(io.StringIO(response.text))
for row in reader:
@@ -1422,9 +1410,6 @@ def _build_uap_sightings_from_hf_mirror() -> list[dict]:
)
if not occurred:
continue
if occurred < cutoff_str:
stale_rows_dropped += 1
continue
raw_location = _normalize_uap_location(
row.get("Location", "")
or row.get("City", "")
@@ -1459,19 +1444,6 @@ def _build_uap_sightings_from_hf_mirror() -> list[dict]:
logger.warning("UAP sightings: HF fallback parse failed: %s", e)
return []
if not candidates:
# HF mirror returned rows, but none inside the rolling window. This is
# the smoking gun for "the public HF dataset hasn't been refreshed in
# years" — log loudly so the operator sees it instead of guessing.
logger.error(
"UAP sightings: HF fallback yielded 0 rows within last %d days "
"(dropped %d stale rows). HF mirror is likely stale; the layer "
"will be empty until the live NUFORC path recovers.",
_NUFORC_RECENT_DAYS,
stale_rows_dropped,
)
return []
candidates.sort(key=lambda row: (row["occurred"], row["posted"], row["id"]), reverse=True)
candidates = candidates[:_NUFORC_HF_FALLBACK_LIMIT]
@@ -1543,29 +1515,13 @@ def fetch_uap_sightings(*, force_refresh: bool = False):
sightings = _load_nuforc_sightings_cache(force_refresh=force_refresh)
if sightings is None:
live_error: Exception | None = None
try:
sightings = _build_recent_uap_sightings()
except Exception as e:
live_error = e
logger.warning("UAP sightings: live NUFORC rebuild failed, using fallback: %s", e)
sightings = _build_uap_sightings_from_hf_mirror()
if sightings:
_save_nuforc_sightings_cache(sightings)
elif live_error is not None:
# Both paths failed: live raised AND HF fallback returned empty
# (either the HF mirror is stale beyond the cutoff or the network
# is gone entirely). The previous code silently set the layer to
# ``[]`` and kept marking it fresh; that masked the failure for
# days. Surface it via assert_canary so the health registry shows
# the layer as broken instead of "fresh and empty".
from services.slo import assert_canary
assert_canary("uap_sightings", 0)
logger.error(
"UAP sightings: both live NUFORC and HF fallback produced 0 "
"rows; layer is unavailable. Live error: %s",
live_error,
)
with _data_lock:
latest_data["uap_sightings"] = sightings or []
@@ -1,148 +0,0 @@
"""Per-aircraft observation tracking for cumulative fuel/CO2 estimates.
Background
----------
The pre-existing emissions enrichment attached a *rate* to each flight
(GPH and kg/hr) based on aircraft model. Users reasonably wanted the
running total: how much fuel HAS this plane burned since we started
seeing it? Multiplying the rate by elapsed observation time gets us
there, but it requires somewhere to remember "when did this icao24
first appear on our radar?"
Why this lives outside ``flight_trails``
----------------------------------------
``flight_trails`` is sized and pruned aggressively for map rendering
(5-minute TTL for untracked aircraft, 200 trail points max). That's
wrong for cumulative burn: if a plane has been airborne 2 hours but
its trail was pruned 30 min in, the "first trail point" timestamp is
30 min ago, not 2h ago. Worse, when the trail expires and re-creates,
the cumulative counter would reset mid-flight.
This module tracks observation lifecycle separately:
* When a hex is first observed: start a new flight session.
* While observed regularly (gap < ``REOPEN_GAP_S``): keep accumulating.
* When unseen for longer than ``REOPEN_GAP_S``: treat next sighting as
a new session (the plane landed and took off again, or it's a
different leg). Reset ``first_seen_at``.
* Stale sessions are pruned every ``PRUNE_INTERVAL_S`` so memory stays
bounded.
The user explicitly asked for this counting semantic: "as soon as a
plane appears there should be a counter that keeps a running count of
the fuel being burned... If there is no estimate take off time then it
can just be from the time the server starts to keep a log of whats in
the air."
"""
from __future__ import annotations
import threading
import time
# Gap between sightings that resets the session. ADS-B refreshes the
# whole aircraft list every minute or two, so anything over a few
# minutes means the plane left our coverage window (landed, transit
# through dead zone, etc). 15 minutes is conservative.
REOPEN_GAP_S = 15 * 60
# Don't accumulate runaway memory: drop entries unseen for an hour.
PRUNE_AFTER_S = 60 * 60
# Cap on accumulated airtime per session so a single bug elsewhere
# (e.g. ts clock skew) can't produce comically large numbers.
MAX_SESSION_SECONDS = 24 * 3600 # 24h — longest realistic civilian leg
_observations: dict[str, dict[str, float]] = {}
_lock = threading.Lock()
_last_prune_at = 0.0
def record_observation(icao_hex: str, *, now: float | None = None) -> int:
"""Record a sighting of ``icao_hex`` and return airtime so far (seconds).
Returns 0 for the first-ever sighting (no elapsed time yet) or when
``icao_hex`` is falsy. The caller can multiply the returned seconds
by ``rate_per_hour / 3600`` to get cumulative consumption.
"""
if not icao_hex:
return 0
key = str(icao_hex).strip().lower()
if not key:
return 0
current = float(now if now is not None else time.time())
with _lock:
entry = _observations.get(key)
if entry is None:
_observations[key] = {"first_seen_at": current, "last_seen_at": current}
return 0
# Use explicit ``is None`` checks instead of ``or`` short-circuit:
# ``0.0`` is a legitimate timestamp value (e.g. test fixtures
# seeding a far-past first_seen_at to exercise the clamp) but
# ``0.0 or fallback`` collapses to ``fallback`` because 0.0 is
# falsy. Bit me on my own test — leaving the safer form here.
last_raw = entry.get("last_seen_at")
last_seen = float(last_raw) if last_raw is not None else current
gap = current - last_seen
if gap > REOPEN_GAP_S:
# Treat as a new flight session — the plane landed/disappeared
# long enough that the prior cumulative count is no longer
# the same flight.
_observations[key] = {"first_seen_at": current, "last_seen_at": current}
return 0
first_raw = entry.get("first_seen_at")
first = float(first_raw) if first_raw is not None else current
# Clamp absurd values from clock skew or bad input.
elapsed = max(0, min(int(current - first), MAX_SESSION_SECONDS))
entry["last_seen_at"] = current
return elapsed
def prune(*, now: float | None = None) -> int:
"""Drop entries we haven't seen in ``PRUNE_AFTER_S`` seconds.
Returns number of entries dropped. Safe to call from a scheduler tick;
cheap (single dict scan) so cadence doesn't matter much.
"""
current = float(now if now is not None else time.time())
dropped = 0
with _lock:
stale_keys = []
for k, v in _observations.items():
last_raw = v.get("last_seen_at")
last = float(last_raw) if last_raw is not None else 0.0
if current - last > PRUNE_AFTER_S:
stale_keys.append(k)
for k in stale_keys:
del _observations[k]
dropped += 1
return dropped
def get_session_seconds(icao_hex: str, *, now: float | None = None) -> int:
"""Read-only accessor: airtime for a known icao without bumping last-seen.
Used by tests and external consumers (e.g. when rendering a snapshot
of all in-flight aircraft, you want the current value, not to update
last_seen_at as a side effect).
"""
if not icao_hex:
return 0
key = str(icao_hex).strip().lower()
with _lock:
entry = _observations.get(key)
if entry is None:
return 0
current = float(now if now is not None else time.time())
first_raw = entry.get("first_seen_at")
first = float(first_raw) if first_raw is not None else current
return max(0, min(int(current - first), MAX_SESSION_SECONDS))
def _reset_for_tests() -> None:
"""Drop all observations. Test helper only."""
with _lock:
_observations.clear()
+50 -123
View File
@@ -17,7 +17,6 @@ from services.network_utils import fetch_with_curl
from services.fetchers._store import latest_data, _data_lock, _mark_fresh
from services.fetchers.plane_alert import enrich_with_plane_alert, enrich_with_tracked_names
from services.fetchers.emissions import get_emissions_info
from services.fetchers.flight_observations import record_observation as _record_flight_observation
from services.fetchers.retry import with_retry
from services.fetchers.route_database import lookup_route
from services.fetchers.aircraft_database import lookup_aircraft_type
@@ -30,88 +29,6 @@ _RE_AIRLINE_CODE_1 = re.compile(r"^([A-Z]{3})\d")
_RE_AIRLINE_CODE_2 = re.compile(r"^([A-Z]{3})[A-Z\d]")
def detect_gps_jamming_zones(
raw_flights: list[dict],
*,
min_aircraft: int | None = None,
min_ratio: float | None = None,
nacp_threshold: int | None = None,
) -> list[dict]:
"""Detect GPS interference zones from a snapshot of raw ADS-B aircraft.
Methodology mirrors GPSJam.org / Flightradar24: bin aircraft into 1°x1°
grid cells, flag cells where the fraction of aircraft reporting degraded
NACp clears a threshold.
Inputs
------
raw_flights:
Iterable of dicts. Each item is expected to carry ``lat``, ``lng``
(or ``lon``), and ``nac_p``. Records missing position OR missing
``nac_p`` entirely (typical for OpenSky-sourced flights) are
skipped absence-of-data isn't evidence of anything.
nac_p == 0 IS counted as degraded. Pre-fix code skipped it on the theory
that "0 = old transponder, never computed accuracy." That's only half
right: modern Mode-S Enhanced Surveillance transponders also fall back
to nac_p=0 when they lose GPS lock entirely which is exactly the
jamming signature we're trying to detect. Filtering 0 out was discarding
the strongest evidence.
Denoising:
1. Require ``min_aircraft`` per grid cell for statistical validity.
2. Subtract 1 from degraded count per cell (GPSJam's technique) so
a single quirky transponder can't flag an entire zone.
3. Require ratio ``adjusted_degraded / total > min_ratio``.
All thresholds default to the module-level constants but can be
overridden for testing.
"""
min_aircraft = GPS_JAMMING_MIN_AIRCRAFT if min_aircraft is None else int(min_aircraft)
min_ratio = GPS_JAMMING_MIN_RATIO if min_ratio is None else float(min_ratio)
nacp_threshold = (
GPS_JAMMING_NACP_THRESHOLD if nacp_threshold is None else int(nacp_threshold)
)
jamming_grid: dict[str, dict[str, int]] = {}
for rf in raw_flights or []:
rlat = rf.get("lat")
rlng = rf.get("lng") if rf.get("lng") is not None else rf.get("lon")
if rlat is None or rlng is None:
continue
nacp = rf.get("nac_p")
if nacp is None:
continue
grid_key = f"{int(rlat)},{int(rlng)}"
cell = jamming_grid.setdefault(grid_key, {"degraded": 0, "total": 0})
cell["total"] += 1
if nacp < nacp_threshold:
cell["degraded"] += 1
jamming_zones: list[dict] = []
for gk, counts in jamming_grid.items():
if counts["total"] < min_aircraft:
continue
adjusted_degraded = max(counts["degraded"] - 1, 0)
if adjusted_degraded == 0:
continue
ratio = adjusted_degraded / counts["total"]
if ratio > min_ratio:
lat_i, lng_i = gk.split(",")
severity = "low" if ratio < 0.5 else "medium" if ratio < 0.75 else "high"
jamming_zones.append(
{
"lat": int(lat_i) + 0.5,
"lng": int(lng_i) + 0.5,
"severity": severity,
"ratio": round(ratio, 2),
"degraded": counts["degraded"],
"total": counts["total"],
}
)
return jamming_zones
# ---------------------------------------------------------------------------
# OpenSky Network API Client (OAuth2)
# ---------------------------------------------------------------------------
@@ -542,18 +459,6 @@ def _classify_and_publish(all_adsb_flights):
ac_category = "heli" if model_upper in _HELI_TYPES_BACKEND else "plane"
# Source attribution: prefer the explicit ``source`` tag stamped
# at fetch time (adsb.lol, OpenSky). If absent, fall back to the
# legacy ``supplemental_source`` (airplanes.live, adsb.fi) so
# supplementals are still attributed without changing their
# tagger. Final fallback "adsb.lol" preserves prior behavior for
# any caller that synthesizes records without going through one
# of our fetchers (e.g. tests).
source = (
f.get("source")
or f.get("supplemental_source")
or "adsb.lol"
)
flights.append(
{
"callsign": flight_str,
@@ -575,7 +480,6 @@ def _classify_and_publish(all_adsb_flights):
"airline_code": airline_code,
"aircraft_category": ac_category,
"nac_p": f.get("nac_p"),
"source": source,
}
)
except (ValueError, TypeError, KeyError, AttributeError) as loop_e:
@@ -602,22 +506,6 @@ def _classify_and_publish(all_adsb_flights):
if model:
emi = get_emissions_info(model)
if emi:
# Cumulative fuel/CO2: multiply the per-hour rate by how
# long we've been observing this airframe. Users want to
# see the *amount* burned, not just the rate. If we've
# never seen this hex before, observed_seconds is 0 and
# the cumulative values are 0 until the next refresh —
# the rate is still useful info on its own.
observed_seconds = _record_flight_observation(
f.get("icao24") or ""
)
elapsed_h = observed_seconds / 3600.0
emi = {
**emi,
"observed_seconds": observed_seconds,
"fuel_gallons_burned": round(emi["fuel_gph"] * elapsed_h, 1),
"co2_kg_emitted": round(emi["co2_kg_per_hour"] * elapsed_h, 1),
}
f["emissions"] = emi
callsign = f.get("callsign", "").strip().upper()
@@ -836,8 +724,56 @@ def _classify_and_publish(all_adsb_flights):
latest_data["military_flights"] = military_snapshot
# --- GPS Jamming Detection ---
# Uses NACp (Navigation Accuracy Category Position) from ADS-B to infer
# GPS interference zones, similar to GPSJam.org / Flightradar24.
# NACp < 8 = position accuracy worse than the FAA-mandated 0.05 NM.
#
# Denoising (to suppress false positives from old GA transponders):
# 1. Skip nac_p == 0 ("unknown accuracy") — old transponders that never
# computed accuracy, NOT evidence of jamming. Real jamming shows 1-7.
# 2. Require minimum aircraft per grid cell for statistical validity.
# 3. Subtract 1 from degraded count per cell (GPSJam's technique) so a
# single quirky transponder can't flag an entire zone.
# 4. Require the adjusted ratio to exceed the threshold.
try:
jamming_zones = detect_gps_jamming_zones(raw_flights_snapshot)
jamming_grid = {}
raw_flights = raw_flights_snapshot
for rf in raw_flights:
rlat = rf.get("lat")
rlng = rf.get("lng") or rf.get("lon")
if rlat is None or rlng is None:
continue
nacp = rf.get("nac_p")
if nacp is None or nacp == 0:
continue
grid_key = f"{int(rlat)},{int(rlng)}"
if grid_key not in jamming_grid:
jamming_grid[grid_key] = {"degraded": 0, "total": 0}
jamming_grid[grid_key]["total"] += 1
if nacp < GPS_JAMMING_NACP_THRESHOLD:
jamming_grid[grid_key]["degraded"] += 1
jamming_zones = []
for gk, counts in jamming_grid.items():
if counts["total"] < GPS_JAMMING_MIN_AIRCRAFT:
continue
adjusted_degraded = max(counts["degraded"] - 1, 0)
if adjusted_degraded == 0:
continue
ratio = adjusted_degraded / counts["total"]
if ratio > GPS_JAMMING_MIN_RATIO:
lat_i, lng_i = gk.split(",")
severity = "low" if ratio < 0.5 else "medium" if ratio < 0.75 else "high"
jamming_zones.append(
{
"lat": int(lat_i) + 0.5,
"lng": int(lng_i) + 0.5,
"severity": severity,
"ratio": round(ratio, 2),
"degraded": counts["degraded"],
"total": counts["total"],
}
)
with _data_lock:
latest_data["gps_jamming"] = jamming_zones
if jamming_zones:
@@ -913,15 +849,7 @@ def _fetch_adsb_lol_regions():
res = fetch_with_curl(url, timeout=10)
if res.status_code == 200:
data = res.json()
aircraft = data.get("ac", [])
# Stamp the source at the fetch site so attribution survives
# the OpenSky/supplemental dedupe-by-hex merge downstream.
# Previously adsb.lol records carried no marker while OpenSky
# records got ``is_opensky: True`` — which made flight tooltips
# look like everything came from OpenSky.
for a in aircraft:
a["source"] = "adsb.lol"
return aircraft
return data.get("ac", [])
except (
requests.RequestException,
ConnectionError,
@@ -1004,7 +932,6 @@ def _enrich_with_opensky_and_supplemental(adsb_flights):
"gs": (s[9] * 1.94384) if s[9] else 0,
"t": "Unknown",
"is_opensky": True,
"source": "OpenSky",
}
)
elif os_res.status_code == 429:
+1 -18
View File
@@ -7,7 +7,6 @@ import requests
from services.network_utils import fetch_with_curl
from services.fetchers._store import latest_data, _data_lock, _mark_fresh
from services.fetchers.emissions import get_emissions_info
from services.fetchers.flight_observations import record_observation as _record_flight_observation
from services.fetchers.plane_alert import enrich_with_plane_alert
logger = logging.getLogger("services.data_fetcher")
@@ -172,7 +171,6 @@ def fetch_military_flights():
h = a.get("hex", "").lower()
if h and h not in seen_hex:
seen_hex.add(h)
a["source"] = "adsb.lol"
all_mil_ac.append(a)
except Exception as e:
logger.warning(f"adsb.lol mil fetch failed: {e}")
@@ -184,7 +182,6 @@ def fetch_military_flights():
h = a.get("hex", "").lower()
if h and h not in seen_hex:
seen_hex.add(h)
a["source"] = "airplanes.live"
all_mil_ac.append(a)
logger.info(f"airplanes.live mil: +{len(resp2.json().get('ac', []))} raw, {len(all_mil_ac)} total unique")
except Exception as e:
@@ -237,7 +234,6 @@ def fetch_military_flights():
"registration": f.get("r", "N/A"),
"icao24": icao_hex,
"squawk": f.get("squawk", ""),
"source": f.get("source") or "adsb.lol",
})
continue
@@ -262,8 +258,7 @@ def fetch_military_flights():
"model": f.get("t", "Unknown"),
"icao24": icao_hex,
"speed_knots": speed_knots,
"squawk": f.get("squawk", ""),
"source": f.get("source") or "adsb.lol",
"squawk": f.get("squawk", "")
})
except Exception as loop_e:
logger.error(f"Mil flight interpolation error: {loop_e}")
@@ -301,18 +296,6 @@ def fetch_military_flights():
if model:
emissions = get_emissions_info(model)
if emissions:
# Cumulative fuel/CO2 since first observation — mirrors
# the civilian path in flights._classify_and_publish.
observed_seconds = _record_flight_observation(
mf.get("icao24") or ""
)
elapsed_h = observed_seconds / 3600.0
emissions = {
**emissions,
"observed_seconds": observed_seconds,
"fuel_gallons_burned": round(emissions["fuel_gph"] * elapsed_h, 1),
"co2_kg_emitted": round(emissions["co2_kg_per_hour"] * elapsed_h, 1),
}
mf["emissions"] = emissions
if mf.get("alert_category"):
mf["type"] = "tracked_flight"
-258
View File
@@ -1,258 +0,0 @@
"""Cumulative fuel/CO2 tracking via per-aircraft observation timestamps.
Background
----------
Users want the running total of fuel burned per aircraft not just the
rate. We track first-seen-at per icao24 and multiply elapsed observation
time by the model-based rate. This module's job is exclusively the
timestamp bookkeeping; multiplication happens in the flights/military
fetchers.
These tests pin:
* First sighting returns 0 (no airtime yet).
* Repeated sightings within ``REOPEN_GAP_S`` accumulate elapsed time.
* Gap longer than ``REOPEN_GAP_S`` resets the session (plane landed
and took off again different flight).
* ``MAX_SESSION_SECONDS`` clamp protects against clock skew bugs.
* ``prune()`` drops stale entries.
* ``get_session_seconds`` reads without bumping last_seen.
* Empty / None icao input is a defensive no-op.
"""
from __future__ import annotations
import pytest
@pytest.fixture(autouse=True)
def _reset_observations():
from services.fetchers import flight_observations as obs
obs._reset_for_tests()
yield
obs._reset_for_tests()
class TestRecordObservation:
def test_first_sighting_returns_zero(self):
from services.fetchers.flight_observations import record_observation
assert record_observation("a12345", now=1000.0) == 0
def test_repeated_sightings_accumulate(self):
"""ADS-B refreshes every ~minute in practice, so each observation
is within ``REOPEN_GAP_S`` (15 min) of the last and we keep
accumulating. Walking the timestamps in 5-minute steps so we
stay inside the reopen window the whole way."""
from services.fetchers.flight_observations import record_observation
record_observation("a12345", now=1000.0)
# 1 minute later (within REOPEN_GAP_S)
assert record_observation("a12345", now=1060.0) == 60
# Step through 5-minute spaced refreshes — first_seen_at stays
# at 1000.0 the whole time, and we approach a 1-hour airtime.
assert record_observation("a12345", now=1360.0) == 360
assert record_observation("a12345", now=1660.0) == 660
assert record_observation("a12345", now=1960.0) == 960
assert record_observation("a12345", now=2260.0) == 1260
assert record_observation("a12345", now=2560.0) == 1560
assert record_observation("a12345", now=2860.0) == 1860
assert record_observation("a12345", now=3160.0) == 2160
assert record_observation("a12345", now=3460.0) == 2460
assert record_observation("a12345", now=3760.0) == 2760
assert record_observation("a12345", now=4060.0) == 3060
assert record_observation("a12345", now=4360.0) == 3360
# 1 hour after first sighting — still inside the 15-min reopen
# window from the prior 4360 observation.
assert record_observation("a12345", now=4600.0) == 3600
def test_gap_longer_than_reopen_resets_session(self):
"""If a hex hasn't been seen in ``REOPEN_GAP_S`` (15 min default),
the next sighting is treated as a new flight first_seen_at resets."""
from services.fetchers.flight_observations import record_observation
record_observation("a12345", now=1000.0)
record_observation("a12345", now=1500.0) # 500s later — within gap
# Now 20 minutes of silence (1200s > 900s threshold) → session reset.
assert record_observation("a12345", now=2700.0) == 0
# And the next quick sighting starts accumulating from 2700 again.
assert record_observation("a12345", now=2760.0) == 60
def test_session_clamp(self):
"""Clock skew protection: when a hex has been continuously
observed for longer than ``MAX_SESSION_SECONDS``, clamp.
Synthesizes the state directly because driving 86,400+ seconds of
observations through the public API in a test would take 1000+
REOPEN_GAP_S-respecting steps.
"""
from services.fetchers import flight_observations as obs
from services.fetchers.flight_observations import _observations, _lock
# last_seen_at very recent so REOPEN_GAP_S branch does NOT fire,
# but first_seen_at way in the past so the elapsed math overflows
# MAX_SESSION_SECONDS. Clamp must kick in.
big_now = float(obs.MAX_SESSION_SECONDS + 1_000_000)
with _lock:
_observations["a12345"] = {
"first_seen_at": 0.0,
"last_seen_at": big_now - 60, # 60s ago — well inside gap window
}
elapsed = obs.record_observation("a12345", now=big_now)
assert elapsed == obs.MAX_SESSION_SECONDS, (
f"elapsed must be clamped to MAX_SESSION_SECONDS; got {elapsed}"
)
def test_empty_input_returns_zero(self):
from services.fetchers.flight_observations import record_observation
assert record_observation("") == 0
assert record_observation(None) == 0 # type: ignore[arg-type]
assert record_observation(" ") == 0
def test_case_insensitive_key(self):
"""ICAO24 hex codes are case-insensitive — adsb.lol lowercases
them, OpenSky may not. Normalize so both refer to the same airframe."""
from services.fetchers.flight_observations import record_observation
record_observation("A12345", now=1000.0)
# Different case must hit the same entry.
assert record_observation("a12345", now=1060.0) == 60
class TestGetSessionSeconds:
def test_read_only_does_not_bump(self):
from services.fetchers.flight_observations import (
record_observation,
get_session_seconds,
)
record_observation("a12345", now=1000.0)
record_observation("a12345", now=1060.0) # bumps last_seen
# Now read at t=2000. Without bumping, gap=2000-1060=940 > 900,
# so a recording call would reset. But the read should NOT reset.
seconds_at_2000 = get_session_seconds("a12345", now=2000.0)
assert seconds_at_2000 == 1000, (
f"read should return 2000-1000=1000s; got {seconds_at_2000}"
)
# Verify the next recording at t=2001 still resets (gap > 900s
# from the read above — proves the read didn't bump last_seen).
from services.fetchers.flight_observations import record_observation as rec
assert rec("a12345", now=2001.0) == 0 # session reset
def test_unknown_hex_returns_zero(self):
from services.fetchers.flight_observations import get_session_seconds
assert get_session_seconds("nonexistent") == 0
class TestPrune:
def test_drops_stale_entries(self):
from services.fetchers import flight_observations as obs
obs.record_observation("active", now=10_000.0)
obs.record_observation("stale", now=1.0)
dropped = obs.prune(now=10_000.0)
assert dropped == 1
# Active entry survives:
assert obs.get_session_seconds("active", now=10_001.0) == 1
# Stale entry was dropped — next obs starts fresh:
assert obs.record_observation("stale", now=10_002.0) == 0
def test_no_op_when_nothing_stale(self):
from services.fetchers import flight_observations as obs
obs.record_observation("hex1", now=1000.0)
obs.record_observation("hex2", now=1000.0)
dropped = obs.prune(now=1500.0)
assert dropped == 0
# ---------------------------------------------------------------------------
# Integration: emissions enrichment in _classify_and_publish honors the
# cumulative tracker.
# ---------------------------------------------------------------------------
class TestEmissionsCumulativeIntegration:
def _reset_store(self):
from services.fetchers._store import latest_data, _data_lock
with _data_lock:
for key in (
"flights", "commercial_flights", "private_flights",
"private_jets", "military_flights", "tracked_flights",
):
latest_data[key] = []
def test_first_publish_zero_cumulative(self, monkeypatch):
"""On the first observation, cumulative values are 0 — but the
rate fields and observed_seconds are still present in the dict."""
from services.fetchers import flights as flights_module
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
flights_module._classify_and_publish([
{
"hex": "test001",
"flight": "JBU711",
"r": "N1",
"t": "C172", # Cessna 172, 9 GPH
"lat": 40.0,
"lon": -100.0,
"alt_baro": 3000,
"gs": 100,
}
])
with _data_lock:
published = list(latest_data.get("flights", []))
assert len(published) == 1
emi = published[0].get("emissions")
assert emi is not None
assert emi["fuel_gph"] == 9
assert emi["observed_seconds"] == 0
assert emi["fuel_gallons_burned"] == 0.0
assert emi["co2_kg_emitted"] == 0.0
def test_second_publish_accumulates(self, monkeypatch):
"""Publishing the same hex a second time picks up real elapsed time
and produces non-zero cumulative values."""
import time as _time_real
from services.fetchers import flights as flights_module
from services.fetchers import flight_observations as obs
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
# Manually seed an observation 1 hour in the past so the next
# publish picks up ~3600s elapsed.
with obs._lock:
obs._observations["test002"] = {
"first_seen_at": _time_real.time() - 3600,
"last_seen_at": _time_real.time() - 60,
}
flights_module._classify_and_publish([
{
"hex": "test002",
"flight": "JBU711",
"r": "N1",
"t": "C172", # 9 GPH
"lat": 40.0,
"lon": -100.0,
"alt_baro": 3000,
"gs": 100,
}
])
with _data_lock:
published = list(latest_data.get("flights", []))
assert len(published) == 1
emi = published[0].get("emissions")
# Roughly 1 hour observed → 9 gal burned.
assert 3500 <= emi["observed_seconds"] <= 3700
assert 8.7 <= emi["fuel_gallons_burned"] <= 9.3
# CO2 = 9 gph * 9.57 kg/gal = 86.1 kg/hr.
assert 84 <= emi["co2_kg_emitted"] <= 88
@@ -1,354 +0,0 @@
"""Per-flight source attribution.
Background
----------
Pre-fix, adsb.lol records (the primary source for most flights) carried
no source marker. OpenSky records got ``is_opensky: True`` and
supplementals got ``supplemental_source``, so any UI that wanted to show
which provider a flight came from saw OpenSky/airplanes.live records as
explicitly tagged and adsb.lol records as "unlabeled" making it look
like adsb.lol wasn't even being used.
This caused user confusion ("only military planes have adsb.lol
telemetry") that was diagnostic noise, not a real bug. The actual fix:
stamp ``source`` at every fetch site so the downstream consumer can
attribute the provider with no guesswork.
These tests pin:
* adsb.lol regional records get ``source: "adsb.lol"`` at fetch time
(synthesized via the published flight dict).
* OpenSky records get ``source: "OpenSky"`` (alongside the existing
``is_opensky: True`` for backwards compat).
* Supplementals (airplanes.live, adsb.fi) flow through with their
``supplemental_source`` honored.
* The military fetcher tags ``source`` on military_flights and uavs.
* The published flight dict carries ``source`` so downstream code
can render attribution.
"""
from __future__ import annotations
import pytest
# ---------------------------------------------------------------------------
# _classify_and_publish — source field flows into published flight dict
# ---------------------------------------------------------------------------
class TestClassifyAndPublishSource:
def _reset_store(self):
"""Clear store before each test so we get deterministic state."""
from services.fetchers._store import latest_data, _data_lock
with _data_lock:
for key in (
"flights", "commercial_flights", "private_flights",
"private_jets", "military_flights", "tracked_flights",
):
latest_data[key] = []
return latest_data
def test_adsb_lol_record_tagged_in_published_flight(self, monkeypatch):
"""A raw adsb.lol record (carrying ``source: 'adsb.lol'`` from the
fetch site) flows through ``_classify_and_publish`` and the
published flight dict carries the same ``source`` field."""
from services.fetchers import flights as flights_module
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
# Patch route + type lookups so they don't try to hit the network.
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
flights_module._classify_and_publish(
[
{
"hex": "ad7701",
"flight": "JBU711",
"r": "N967JT",
"t": "A321",
"lat": 40.0,
"lon": -100.0,
"alt_baro": 36000,
"gs": 401.6,
"nac_p": 9,
"source": "adsb.lol", # stamped at fetch site
}
]
)
with _data_lock:
published = list(latest_data.get("flights", []))
assert len(published) == 1
assert published[0]["source"] == "adsb.lol"
# nac_p still flows through too — sanity check that adding source
# didn't break the existing GPS jamming signal.
assert published[0]["nac_p"] == 9
def test_opensky_record_tagged_in_published_flight(self, monkeypatch):
"""OpenSky-sourced records carry ``source: 'OpenSky'`` (plus the
existing ``is_opensky: True`` for back-compat)."""
from services.fetchers import flights as flights_module
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
flights_module._classify_and_publish(
[
{
"hex": "a12345",
"flight": "UAL100",
"r": "N100UA",
"t": "Unknown",
"lat": 41.0,
"lon": -87.0,
"alt_baro": 35000,
"gs": 450,
# No nac_p — OpenSky doesn't carry it.
"is_opensky": True,
"source": "OpenSky",
}
]
)
with _data_lock:
published = list(latest_data.get("flights", []))
assert len(published) == 1
assert published[0]["source"] == "OpenSky"
def test_supplemental_source_propagates(self, monkeypatch):
"""Supplemental records (airplanes.live, adsb.fi) have their
legacy ``supplemental_source`` field promoted to the unified
``source`` field in the published dict so consumers don't have
to inspect two different keys."""
from services.fetchers import flights as flights_module
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
flights_module._classify_and_publish(
[
{
"hex": "b22222",
"flight": "DAL200",
"r": "N200DL",
"t": "B738",
"lat": 42.0,
"lon": -90.0,
"alt_baro": 32000,
"gs": 420,
"supplemental_source": "airplanes.live",
# No explicit "source" — should fall through to
# supplemental_source.
}
]
)
with _data_lock:
published = list(latest_data.get("flights", []))
assert len(published) == 1
assert published[0]["source"] == "airplanes.live"
def test_explicit_source_wins_over_supplemental_source(self, monkeypatch):
"""If both fields are present, explicit ``source`` wins (it's the
newer canonical tag)."""
from services.fetchers import flights as flights_module
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
flights_module._classify_and_publish(
[
{
"hex": "c33333",
"flight": "AAL300",
"r": "N300AA",
"t": "A321",
"lat": 33.0,
"lon": -97.0,
"alt_baro": 34000,
"gs": 430,
"source": "adsb.lol",
"supplemental_source": "adsb.fi",
}
]
)
with _data_lock:
published = list(latest_data.get("flights", []))
assert published[0]["source"] == "adsb.lol"
def test_untagged_record_defaults_to_adsb_lol(self, monkeypatch):
"""A record with neither ``source`` nor ``supplemental_source``
(e.g. synthesized by a test, or a fetcher that hasn't been
migrated yet) defaults to ``"adsb.lol"`` since that's been the
primary source historically. Defensive default better than
empty string."""
from services.fetchers import flights as flights_module
from services.fetchers._store import latest_data, _data_lock
self._reset_store()
monkeypatch.setattr(flights_module, "lookup_route", lambda _: None)
monkeypatch.setattr(flights_module, "lookup_aircraft_type", lambda _: "")
flights_module._classify_and_publish(
[
{
"hex": "d44444",
"flight": "SWA400",
"r": "N400SW",
"t": "B737",
"lat": 32.0,
"lon": -110.0,
"alt_baro": 30000,
"gs": 410,
}
]
)
with _data_lock:
published = list(latest_data.get("flights", []))
assert published[0]["source"] == "adsb.lol"
# ---------------------------------------------------------------------------
# adsb.lol regional fetcher tags at fetch time
# ---------------------------------------------------------------------------
class TestAdsbLolRegionalTagging:
def test_fetch_region_stamps_source_on_each_aircraft(self, monkeypatch):
"""The wrapper around the adsb.lol regional endpoint stamps
``source: 'adsb.lol'`` on every record before returning, so the
downstream merge step sees attribution survive even when the
record gets reshuffled (e.g. dedupe-by-hex during OpenSky merge)."""
from services.fetchers import flights as flights_module
# Fake response — 3 aircraft, none have a source field originally.
class FakeResp:
status_code = 200
def json(self):
return {
"ac": [
{"hex": "a1", "lat": 40.0, "lon": -100.0, "nac_p": 8},
{"hex": "a2", "lat": 40.1, "lon": -100.1, "nac_p": 9},
{"hex": "a3", "lat": 40.2, "lon": -100.2, "nac_p": 10},
]
}
monkeypatch.setattr(
flights_module, "fetch_with_curl", lambda *a, **kw: FakeResp()
)
results = flights_module._fetch_adsb_lol_regions()
assert len(results) >= 3
# Every aircraft we got back must be tagged.
sources = {a.get("source") for a in results}
assert sources == {"adsb.lol"}, (
f"adsb.lol regional fetcher must stamp source on every record; "
f"got: {sources}"
)
def test_fetch_region_failure_returns_empty_without_crashing(self, monkeypatch):
"""If adsb.lol returns non-200, the fetcher returns [] gracefully —
downstream code already handles this. Sanity check that the source
tagging doesn't introduce a new failure mode."""
from services.fetchers import flights as flights_module
class FakeResp:
status_code = 500
def json(self): return {}
monkeypatch.setattr(
flights_module, "fetch_with_curl", lambda *a, **kw: FakeResp()
)
results = flights_module._fetch_adsb_lol_regions()
assert results == []
# ---------------------------------------------------------------------------
# Military fetcher tags source on output dicts
# ---------------------------------------------------------------------------
class TestMilitarySourceTagging:
def test_military_output_carries_source_field(self, monkeypatch):
"""Each entry in ``military_flights`` should carry a ``source``
field. Pre-fix the only military attribution was inferring from
which endpoint we hit; now it's explicit."""
from services.fetchers import military as mil_module
from services.fetchers._store import latest_data, _data_lock
# Reset relevant store state.
with _data_lock:
latest_data["military_flights"] = []
latest_data["uavs"] = []
latest_data["tracked_flights"] = []
# Stub _store.is_any_active so the fetch doesn't early-return.
# The military module imports the function inline at call time,
# so we have to patch it on the _store module itself rather than
# on the military module.
from services.fetchers import _store as store_module
monkeypatch.setattr(store_module, "is_any_active", lambda *_: True)
# Stub fetch_with_curl to return one synthetic military aircraft
# from adsb.lol, none from airplanes.live.
class _RespMil:
status_code = 200
def json(self):
return {
"ac": [
{
"hex": "ae6c1d",
"flight": "CRUSH52",
"r": "170281",
"t": "C30J",
"lat": 47.594,
"lon": -124.879,
"alt_baro": 9025,
"gs": 162.8,
"track": 334.5,
"nac_p": 10,
}
]
}
class _RespEmpty:
status_code = 200
def json(self):
return {"ac": []}
def _fake_fetch(url, *a, **kw):
if "adsb.lol" in url:
return _RespMil()
return _RespEmpty()
monkeypatch.setattr(mil_module, "fetch_with_curl", _fake_fetch)
# Stubs for downstream enrichments that try to hit external state.
monkeypatch.setattr(mil_module, "enrich_with_plane_alert", lambda mf: None)
monkeypatch.setattr(mil_module, "_enrich_country", lambda hex_, flag: ("US", "USAF"))
monkeypatch.setattr(mil_module, "_classify_military_type", lambda t: "transport")
monkeypatch.setattr(mil_module, "_classify_uav", lambda m, c: (False, "", ""))
monkeypatch.setattr(mil_module, "get_emissions_info", lambda model: None)
monkeypatch.setattr(mil_module, "_mark_fresh", lambda *keys: None)
mil_module.fetch_military_flights()
with _data_lock:
mil_published = list(latest_data.get("military_flights", []))
assert len(mil_published) == 1
assert mil_published[0]["source"] == "adsb.lol"
-333
View File
@@ -1,333 +0,0 @@
"""GPS jamming detection — nac_p=0 counted, lowered thresholds.
Background
----------
Pre-fix, the detector had three stacked filters that together meant the
``gps_jamming`` layer almost never lit up:
1. ``nac_p == 0`` aircraft were dropped on the theory that "0 = old
transponder." But modern Mode-S Enhanced Surveillance transponders
also fall back to ``nac_p == 0`` when they lose GPS lock entirely
which is *exactly* the jamming signature we want to catch.
2. ``GPS_JAMMING_MIN_AIRCRAFT = 5`` per 1°x1° cell.
3. ``GPS_JAMMING_MIN_RATIO = 0.30`` adjusted ratio.
Combined with the existing ``-1`` noise cushion (``adjusted = degraded - 1``)
the bar to clear required dense, busy airspace but jamming hotspots
(eastern Med, eastern Ukraine, Iran/Iraq) tend to have sparser traffic
precisely because pilots avoid them.
These tests pin the new behavior:
* ``nac_p == 0`` is now counted as degraded.
* ``nac_p == None`` (no field typical for OpenSky records) is still
skipped absence isn't evidence.
* Thresholds lowered to 3 aircraft / 0.20 ratio.
* Public function signature accepts overrides so callers / future
operators can re-tune without code edits.
"""
from __future__ import annotations
import pytest
# ---------------------------------------------------------------------------
# nac_p == 0 inclusion (the headline fix)
# ---------------------------------------------------------------------------
class TestNacpZeroCounted:
def test_cell_dominated_by_nacp_zero_now_fires(self):
"""Three aircraft all reporting nac_p=0 in one cell, plus two
with valid GPS. Pre-fix the three nac_p=0 records were skipped
entirely (cell would have total=2, degraded=0, no zone). Post-fix
they count as degraded this IS the jamming signature."""
from services.fetchers.flights import detect_gps_jamming_zones
# All in 1°x1° cell at int(lat)=40, int(lng)=-100
feed = [
{"hex": "a1", "lat": 40.1, "lng": -100.1, "nac_p": 0},
{"hex": "a2", "lat": 40.5, "lng": -100.5, "nac_p": 0},
{"hex": "a3", "lat": 40.9, "lng": -100.9, "nac_p": 0},
{"hex": "b1", "lat": 40.2, "lng": -100.3, "nac_p": 9},
{"hex": "b2", "lat": 40.7, "lng": -100.7, "nac_p": 11},
]
zones = detect_gps_jamming_zones(feed)
# total=5, degraded=3, adjusted=2, ratio=0.40 > 0.20 → zone fires.
assert len(zones) == 1
assert zones[0]["degraded"] == 3
assert zones[0]["total"] == 5
assert zones[0]["ratio"] == 0.40
# Grid-cell center coords.
assert zones[0]["lat"] == 40.5
assert zones[0]["lng"] == -99.5
def test_nacp_zero_alone_clears_min_aircraft(self):
"""A cell with exactly 3 aircraft all reporting nac_p=0 must
fire under the new MIN_AIRCRAFT=3 + MIN_RATIO=0.20 regime."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "a1", "lat": 50.1, "lng": 30.1, "nac_p": 0},
{"hex": "a2", "lat": 50.5, "lng": 30.5, "nac_p": 0},
{"hex": "a3", "lat": 50.9, "lng": 30.9, "nac_p": 0},
]
zones = detect_gps_jamming_zones(feed)
# total=3, degraded=3, adjusted=2, ratio=0.667 > 0.20 → fires.
# severity is "medium" because 0.5 ≤ ratio < 0.75.
assert len(zones) == 1
assert zones[0]["severity"] == "medium"
# ---------------------------------------------------------------------------
# nac_p == None is still skipped (preserve OpenSky behavior)
# ---------------------------------------------------------------------------
class TestNoneStillSkipped:
def test_none_records_dont_add_to_grid(self):
"""OpenSky's /states/all doesn't include nac_p, so its records
arrive with the field absent (``rf.get("nac_p") is None``). These
records must NOT count toward total absence-of-data isn't
evidence of either jamming OR working GPS."""
from services.fetchers.flights import detect_gps_jamming_zones
# 3 jammed + 4 OpenSky-style (no nac_p). Pre-fix and post-fix
# behavior should be identical here: None always skipped.
feed = [
{"hex": "a1", "lat": 40.1, "lng": -100.1, "nac_p": 0},
{"hex": "a2", "lat": 40.2, "lng": -100.2, "nac_p": 0},
{"hex": "a3", "lat": 40.3, "lng": -100.3, "nac_p": 0},
# OpenSky-style: no nac_p at all
{"hex": "o1", "lat": 40.4, "lng": -100.4},
{"hex": "o2", "lat": 40.5, "lng": -100.5},
{"hex": "o3", "lat": 40.6, "lng": -100.6},
{"hex": "o4", "lat": 40.7, "lng": -100.7},
]
zones = detect_gps_jamming_zones(feed)
# Only the 3 nac_p=0 records hit the grid. total=3, not 7.
assert len(zones) == 1
assert zones[0]["total"] == 3
assert zones[0]["degraded"] == 3
def test_explicit_none_skipped(self):
"""Same behavior when ``nac_p`` is present but set to None
(defensive adsb.lol shouldn't do this, but downstream
normalizers might)."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "a1", "lat": 0.1, "lng": 0.1, "nac_p": None},
{"hex": "a2", "lat": 0.2, "lng": 0.2, "nac_p": None},
{"hex": "a3", "lat": 0.3, "lng": 0.3, "nac_p": None},
]
zones = detect_gps_jamming_zones(feed)
# No records counted → no zones.
assert zones == []
# ---------------------------------------------------------------------------
# Lowered MIN_AIRCRAFT (5 → 3)
# ---------------------------------------------------------------------------
class TestMinAircraftLowered:
def test_three_aircraft_cell_now_qualifies(self):
"""Pre-fix MIN_AIRCRAFT=5 blocked sparse cells entirely. Post-fix
the bar is 3 aircraft per cell, which is realistic for the actual
jamming hotspots where traffic is thinner."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "a1", "lat": 33.1, "lng": 44.1, "nac_p": 3},
{"hex": "a2", "lat": 33.2, "lng": 44.2, "nac_p": 5},
{"hex": "a3", "lat": 33.3, "lng": 44.3, "nac_p": 7},
]
zones = detect_gps_jamming_zones(feed)
# total=3, degraded=3, adjusted=2, ratio=0.667 — fires under new
# rules, would have been blocked by MIN_AIRCRAFT=5 pre-fix.
assert len(zones) == 1
def test_two_aircraft_cell_still_blocked(self):
"""We didn't lower the bar to 2 — that would create too much
single-transponder noise. Two aircraft per cell still doesn't
qualify."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "a1", "lat": 33.1, "lng": 44.1, "nac_p": 3},
{"hex": "a2", "lat": 33.2, "lng": 44.2, "nac_p": 3},
]
zones = detect_gps_jamming_zones(feed)
assert zones == []
# ---------------------------------------------------------------------------
# Lowered MIN_RATIO (0.30 → 0.20)
# ---------------------------------------------------------------------------
class TestMinRatioLowered:
def test_ratio_between_old_and_new_threshold_fires(self):
"""Construct a cell whose ratio sits in the (0.20, 0.30) window:
fires under the new bar, would have been blocked pre-fix."""
from services.fetchers.flights import detect_gps_jamming_zones
# 10 aircraft, 4 degraded → adjusted=3, ratio=3/10=0.30.
# Pre-fix threshold was > 0.30 strict — would NOT fire.
# Post-fix threshold is > 0.20 — fires.
feed = (
[{"hex": f"d{i}", "lat": 40.1, "lng": -100.1, "nac_p": 3} for i in range(4)]
+ [{"hex": f"c{i}", "lat": 40.5, "lng": -100.5, "nac_p": 9} for i in range(6)]
)
zones = detect_gps_jamming_zones(feed)
assert len(zones) == 1
assert zones[0]["degraded"] == 4
assert zones[0]["total"] == 10
assert zones[0]["ratio"] == 0.30
def test_ratio_at_or_below_new_threshold_does_not_fire(self):
"""Ratio of exactly 0.20 must NOT fire (strict ``>`` comparison)."""
from services.fetchers.flights import detect_gps_jamming_zones
# 15 aircraft, 4 degraded → adjusted=3, ratio=3/15=0.20. Strictly
# not greater than 0.20, so doesn't qualify.
feed = (
[{"hex": f"d{i}", "lat": 40.1, "lng": -100.1, "nac_p": 3} for i in range(4)]
+ [{"hex": f"c{i}", "lat": 40.5, "lng": -100.5, "nac_p": 9} for i in range(11)]
)
zones = detect_gps_jamming_zones(feed)
assert zones == []
# ---------------------------------------------------------------------------
# Pre-existing noise cushion (-1) preserved
# ---------------------------------------------------------------------------
class TestNoiseCushionPreserved:
def test_single_quirky_transponder_doesnt_fire(self):
"""One degraded aircraft in a healthy cell shouldn't fire even
under the relaxed thresholds. The ``-1`` adjustment in the
detector exists for this reason."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = (
[{"hex": "d1", "lat": 40.1, "lng": -100.1, "nac_p": 3}]
+ [{"hex": f"c{i}", "lat": 40.5, "lng": -100.5, "nac_p": 9} for i in range(10)]
)
zones = detect_gps_jamming_zones(feed)
# total=11, degraded=1, adjusted=0 → cell short-circuits.
assert zones == []
# ---------------------------------------------------------------------------
# Constants pinned (catches accidental rollback)
# ---------------------------------------------------------------------------
class TestConstantsPinned:
def test_min_aircraft_is_three(self):
from services.constants import GPS_JAMMING_MIN_AIRCRAFT
assert GPS_JAMMING_MIN_AIRCRAFT == 3, (
"MIN_AIRCRAFT must be 3; raising it back to 5 brings back the "
"'jamming never shows' bug."
)
def test_min_ratio_is_0_20(self):
from services.constants import GPS_JAMMING_MIN_RATIO
assert GPS_JAMMING_MIN_RATIO == 0.20, (
"MIN_RATIO must be 0.20; raising it back to 0.30 brings back "
"the 'jamming never shows' bug."
)
# ---------------------------------------------------------------------------
# Overrides honored
# ---------------------------------------------------------------------------
class TestOverridesHonored:
def test_overrides_supersede_constants(self):
"""The public signature accepts overrides so an operator can
re-tune at the call site (e.g. for a more aggressive setup in
an active conflict zone) without editing the module constants."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "a1", "lat": 40.1, "lng": -100.1, "nac_p": 3},
{"hex": "a2", "lat": 40.2, "lng": -100.2, "nac_p": 3},
]
# With defaults (min_aircraft=3) this is blocked. With override=2 it fires.
assert detect_gps_jamming_zones(feed) == []
zones = detect_gps_jamming_zones(feed, min_aircraft=2)
assert len(zones) == 1
# ---------------------------------------------------------------------------
# lon vs lng compatibility
# ---------------------------------------------------------------------------
class TestLonLngCompat:
def test_lon_key_accepted(self):
"""adsb.lol records arrive with ``lon`` (no g). The OpenSky merge
normalizes to ``lng`` but raw records flowing into the detector
may use either. Make sure both work."""
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "a1", "lat": 40.1, "lon": -100.1, "nac_p": 0},
{"hex": "a2", "lat": 40.2, "lon": -100.2, "nac_p": 0},
{"hex": "a3", "lat": 40.3, "lon": -100.3, "nac_p": 0},
]
zones = detect_gps_jamming_zones(feed)
assert len(zones) == 1
# ---------------------------------------------------------------------------
# Empty / malformed inputs don't crash
# ---------------------------------------------------------------------------
class TestRobustness:
def test_empty_feed(self):
from services.fetchers.flights import detect_gps_jamming_zones
assert detect_gps_jamming_zones([]) == []
def test_none_feed(self):
"""The wrapper at the call site passes ``raw_flights_snapshot``
which could in principle be None on a startup race. Handle it."""
from services.fetchers.flights import detect_gps_jamming_zones
assert detect_gps_jamming_zones(None) == []
def test_records_missing_position_skipped(self):
from services.fetchers.flights import detect_gps_jamming_zones
feed = [
{"hex": "noloc", "nac_p": 0},
{"hex": "nolat", "lng": -100.0, "nac_p": 0},
{"hex": "nolng", "lat": 40.0, "nac_p": 0},
]
assert detect_gps_jamming_zones(feed) == []
@@ -238,8 +238,6 @@ class TestNoMonsterUserAgentRemains:
"ShadowBroker-FeedIngester/1.0",
"ShadowBroker/0.9.79 local Shodan connector",
"ShadowBroker/0.9.79 Finnhub connector",
"ShadowBroker/0.9.8 local Shodan connector",
"ShadowBroker/0.9.8 Finnhub connector",
"Mozilla/5.0 (compatible; ShadowBroker CCTV proxy)",
)
@@ -1,252 +0,0 @@
"""HF NUFORC fallback honors the rolling cutoff window.
Background
----------
The UAP sightings layer is sourced primarily from a live scrape of
nuforc.org. When that fails (Cloudflare 403, curl disabled on Windows,
wdtNonce regex stale, etc.) the code falls back to a static CSV mirror
hosted on Hugging Face at ``kcimc/NUFORC/nuforc_str.csv``.
The HF mirror is maintained by a third party and refreshed sporadically.
Pre-fix, the fallback parsed every row, sorted by ``occurred`` descending,
and took the top 250 **with no date cutoff**. When the HF mirror is
stale (its "newest" rows are ~2-3 years old), users saw a map full of
2022-2023 sightings labeled as the "last 60 days" layer.
These tests pin the new behavior:
* Rows older than ``_NUFORC_RECENT_DAYS`` are dropped before the take-top-N.
* If the HF mirror has nothing in the window, the fallback returns ``[]``
and logs ERROR (don't silently serve stale data).
* ``fetch_uap_sightings`` records the failure when BOTH paths fail, so
the layer shows as broken in the health registry instead of "fresh".
"""
from __future__ import annotations
import logging
from datetime import datetime as real_datetime
class _FixedDateTime(real_datetime):
"""A datetime whose utcnow() returns a pinned value, for deterministic
cutoff math. Subclasses real datetime so existing operations still work."""
@classmethod
def utcnow(cls):
return cls(2026, 5, 1, 12, 0, 0)
class _StubResponse:
status_code = 200
def __init__(self, text: str):
self.text = text
def _stub_geocode_cache(*_args, **_kwargs):
"""Pre-populated location cache so the fallback doesn't try to hit
Photon during the test."""
return {
"Denver, CO, USA": [39.7392, -104.9903],
"Seattle, WA, USA": [47.6062, -122.3321],
"Phoenix, AZ, USA": [33.4484, -112.0740],
}
def test_hf_fallback_drops_rows_older_than_60_days(monkeypatch):
"""Pre-fix: a row from 2023 would make it into the layer if it was
among the newest 250 in the HF mirror. Post-fix: it's filtered out
before we even count to 250."""
from services.fetchers import earth_observation as eo
# 2026-05-01 - 60 days = 2026-03-02. So 2026-03-01 is one day too old.
csv_text = (
"Sighting,Occurred,Location,Shape,Duration,Posted,Summary\n"
'1,2026-04-15 21:00:00 Local,"Denver, CO, USA",Triangle,5 minutes,2026-04-16,"In-window sighting"\n'
'2,2023-06-01 21:00:00 Local,"Seattle, WA, USA",Light,30 seconds,2023-06-02,"Three years old"\n'
'3,2022-01-15 20:00:00 Local,"Phoenix, AZ, USA",Disk,2 minutes,2022-01-16,"Even older"\n'
)
monkeypatch.setattr(eo, "datetime", _FixedDateTime)
monkeypatch.setattr(eo, "fetch_with_curl", lambda *a, **kw: _StubResponse(csv_text))
monkeypatch.setattr(eo, "_load_nuforc_location_cache", _stub_geocode_cache)
monkeypatch.setattr(eo, "_save_nuforc_location_cache", lambda cache: None)
# If the cutoff is missing, the geocoder may still get called for the
# 2022/2023 rows. We assert geocoder is NEVER invoked for stale rows.
geocode_calls: list[str] = []
def _geocode_spy(location, city, state, country=""):
geocode_calls.append(location)
return None # already in cache, shouldn't be hit anyway
monkeypatch.setattr(eo, "_geocode_uap_location", _geocode_spy)
sightings = eo._build_uap_sightings_from_hf_mirror()
ids = [s["id"] for s in sightings]
assert ids == ["NUFORC-1"], f"only the 2026 row should survive: got {ids}"
# Stale rows must not have been geocoded — they should be dropped
# before the geocoding loop is reached.
assert geocode_calls == []
def test_hf_fallback_returns_empty_when_mirror_is_fully_stale(monkeypatch, caplog):
"""The smoking-gun case: the HF mirror is so stale that NO rows are
within the rolling window. Pre-fix returned 250 ancient rows. Post-fix
returns ``[]`` and logs ERROR so the operator knows the layer is dead."""
from services.fetchers import earth_observation as eo
csv_text = (
"Sighting,Occurred,Location,Shape,Duration,Posted,Summary\n"
'1,2023-04-15 21:00:00 Local,"Denver, CO, USA",Triangle,5 minutes,2023-04-16,"Old"\n'
'2,2022-06-01 21:00:00 Local,"Seattle, WA, USA",Light,30 seconds,2022-06-02,"Older"\n'
'3,2021-01-15 20:00:00 Local,"Phoenix, AZ, USA",Disk,2 minutes,2021-01-16,"Ancient"\n'
)
monkeypatch.setattr(eo, "datetime", _FixedDateTime)
monkeypatch.setattr(eo, "fetch_with_curl", lambda *a, **kw: _StubResponse(csv_text))
monkeypatch.setattr(eo, "_load_nuforc_location_cache", _stub_geocode_cache)
monkeypatch.setattr(eo, "_save_nuforc_location_cache", lambda cache: None)
monkeypatch.setattr(eo, "_geocode_uap_location", lambda *a, **kw: None)
with caplog.at_level(logging.ERROR, logger="services.fetchers.earth_observation"):
sightings = eo._build_uap_sightings_from_hf_mirror()
assert sightings == []
# The error log should mention how many stale rows were dropped so the
# operator can tell the mirror is the problem (not "we got 0 rows" which
# could also mean the download failed).
relevant = [r for r in caplog.records if "HF fallback yielded 0 rows" in r.getMessage()]
assert relevant, "expected loud ERROR when HF mirror is fully stale"
# The message should report the count of dropped stale rows.
assert any("dropped 3" in r.getMessage() for r in relevant)
def test_hf_fallback_still_returns_data_when_some_rows_are_in_window(monkeypatch):
"""Mixed-age mirror: some rows in the window, some not. The fallback
should return only the in-window rows and not log the doomsday ERROR."""
from services.fetchers import earth_observation as eo
csv_text = (
"Sighting,Occurred,Location,Shape,Duration,Posted,Summary\n"
'1,2026-04-15 21:00:00 Local,"Denver, CO, USA",Triangle,5 minutes,2026-04-16,"Fresh"\n'
'2,2026-04-10 21:00:00 Local,"Seattle, WA, USA",Light,30 seconds,2026-04-10,"Also fresh"\n'
'3,2020-01-15 20:00:00 Local,"Phoenix, AZ, USA",Disk,2 minutes,2020-01-16,"Ancient"\n'
)
monkeypatch.setattr(eo, "datetime", _FixedDateTime)
monkeypatch.setattr(eo, "fetch_with_curl", lambda *a, **kw: _StubResponse(csv_text))
monkeypatch.setattr(eo, "_load_nuforc_location_cache", _stub_geocode_cache)
monkeypatch.setattr(eo, "_save_nuforc_location_cache", lambda cache: None)
monkeypatch.setattr(eo, "_geocode_uap_location", lambda *a, **kw: None)
sightings = eo._build_uap_sightings_from_hf_mirror()
ids = sorted(s["id"] for s in sightings)
assert ids == ["NUFORC-1", "NUFORC-2"], f"only in-window rows should appear: got {ids}"
def test_fetch_uap_sightings_marks_failure_when_both_paths_empty(monkeypatch, caplog):
"""When the live path raises AND the HF fallback returns empty,
``fetch_uap_sightings`` must:
* NOT mark the layer fresh (pre-fix bug: it did, so the layer
showed as healthy-but-empty for days)
* call ``assert_canary("uap_sightings", 0)`` so the health
registry surfaces the broken layer
* log an ERROR with the live-path exception for debugging
"""
from services.fetchers import earth_observation as eo
from services.fetchers import _store
monkeypatch.setattr(_store, "is_any_active", lambda layer: True)
monkeypatch.setattr(eo, "_load_nuforc_sightings_cache", lambda force_refresh=False: None)
def _boom():
raise RuntimeError("NUFORC live: zero rows pulled across 3 months")
monkeypatch.setattr(eo, "_build_recent_uap_sightings", _boom)
monkeypatch.setattr(eo, "_build_uap_sightings_from_hf_mirror", lambda: [])
marked: list[str] = []
monkeypatch.setattr(eo, "_mark_fresh", lambda *keys: marked.extend(keys))
canary_calls: list[tuple[str, int]] = []
import services.slo as slo
monkeypatch.setattr(
slo, "assert_canary", lambda key, value: canary_calls.append((key, int(value)))
)
with caplog.at_level(logging.ERROR, logger="services.fetchers.earth_observation"):
eo.fetch_uap_sightings()
assert marked == [], "broken layer must NOT be marked fresh"
assert canary_calls == [("uap_sightings", 0)], (
f"expected canary trip when both paths fail; got {canary_calls}"
)
# The live error message should propagate into the error log so the
# operator can tell live failed AND fallback was empty (not the other
# way around).
assert any(
"both live NUFORC and HF fallback" in r.getMessage()
for r in caplog.records
)
def test_fetch_uap_sightings_succeeds_when_fallback_returns_data(monkeypatch):
"""Positive path: live fails, fallback returns rows. The layer is
populated and marked fresh; assert_canary is NOT tripped (we only
trip the canary when the layer has zero data)."""
from services.fetchers import earth_observation as eo
from services.fetchers import _store
monkeypatch.setattr(_store, "is_any_active", lambda layer: True)
monkeypatch.setattr(eo, "_load_nuforc_sightings_cache", lambda force_refresh=False: None)
monkeypatch.setattr(
eo, "_build_recent_uap_sightings", lambda: (_ for _ in ()).throw(RuntimeError("live down"))
)
fallback_rows = [{"id": "NUFORC-fb-1", "date_time": "2026-04-20", "lat": 0.0, "lng": 0.0}]
monkeypatch.setattr(eo, "_build_uap_sightings_from_hf_mirror", lambda: fallback_rows)
monkeypatch.setattr(eo, "_save_nuforc_sightings_cache", lambda s: None)
marked: list[str] = []
monkeypatch.setattr(eo, "_mark_fresh", lambda *keys: marked.extend(keys))
canary_calls: list[tuple[str, int]] = []
import services.slo as slo
monkeypatch.setattr(
slo, "assert_canary", lambda key, value: canary_calls.append((key, int(value)))
)
eo.fetch_uap_sightings()
assert marked == ["uap_sightings"]
assert canary_calls == [], "canary should not trip when fallback supplies data"
def test_uap_scheduler_runs_weekly_not_daily():
"""The cron job for the UAP layer must be configured for Mondays at
12:00 UTC, not daily. Daily was the pre-fix default; weekly matches
the layer's stated cadence (a rolling 60-day digest) and keeps load
on nuforc.org light."""
from services import data_fetcher
src = data_fetcher.__file__
with open(src, "r", encoding="utf-8") as f:
text = f.read()
# Anchor on the scheduler block by id, then assert the cron triggers.
assert "uap_sightings_weekly" in text, (
"scheduler id should be uap_sightings_weekly (was uap_sightings_daily pre-fix)"
)
# The day_of_week directive is the difference between daily and weekly.
# If somebody flips it back to daily, this fires.
weekly_block = text.split("uap_sightings_weekly", 1)[0]
# Walk backwards for the matching add_job call.
add_job_idx = weekly_block.rfind("add_job(")
assert add_job_idx >= 0, "could not locate add_job block for UAP scheduler"
job_block = text[add_job_idx : text.find(")", text.index("uap_sightings_weekly")) + 1]
assert 'day_of_week="mon"' in job_block, (
f"expected day_of_week='mon' in UAP scheduler block:\n{job_block}"
)
+2 -2
View File
@@ -1,12 +1,12 @@
{
"name": "@shadowbroker/desktop-shell",
"version": "0.9.8",
"version": "0.9.79",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@shadowbroker/desktop-shell",
"version": "0.9.8",
"version": "0.9.79",
"devDependencies": {
"typescript": "^5.6.0"
}
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@shadowbroker/desktop-shell",
"version": "0.9.8",
"version": "0.9.79",
"private": true,
"description": "ShadowBroker desktop shell packaging, runtime bridge, and release tooling",
"scripts": {
@@ -46,18 +46,12 @@ function prepareBuildTree() {
const stagedLayoutPath = path.join(buildFrontendDir, 'src', 'app', 'layout.tsx');
if (fs.existsSync(stagedLayoutPath)) {
const layoutSource = fs.readFileSync(stagedLayoutPath, 'utf8');
// CRLF compatibility: on Windows checkouts without ``core.autocrlf=input``
// (the default) layout.tsx has CRLF line endings, but the original regexes
// only matched LF. The strip silently no-op'd, ``force-dynamic`` stayed,
// and Next's static-export refused to render ``/_not-found`` ("Page with
// `dynamic = \"force-dynamic\"` couldn't be exported"). Use ``\r?\n`` so
// the strip works regardless of line-ending normalization.
fs.writeFileSync(
stagedLayoutPath,
layoutSource
.replace(/\r?\n\/\/ The dashboard is a live local runtime[\s\S]*?client polling ever hydrates\.\r?\n/g, '\n')
.replace(/\r?\nexport const dynamic = ['"]force-dynamic['"];\r?\n/g, '\n')
.replace(/\r?\nexport const revalidate = 0;\r?\n/g, '\n'),
.replace(/\n\/\/ The dashboard is a live local runtime[\s\S]*?client polling ever hydrates\.\n/g, '\n')
.replace(/\nexport const dynamic = ['"]force-dynamic['"];\n/g, '\n')
.replace(/\nexport const revalidate = 0;\n/g, '\n'),
);
}
+1 -1
View File
@@ -4201,7 +4201,7 @@ dependencies = [
[[package]]
name = "shadowbroker-tauri-shell"
version = "0.9.8"
version = "0.9.79"
dependencies = [
"axum",
"base64 0.22.1",
@@ -1,6 +1,6 @@
[package]
name = "shadowbroker-tauri-shell"
version = "0.9.8"
version = "0.9.79"
edition = "2021"
[build-dependencies]
@@ -1,7 +1,7 @@
{
"$schema": "https://schema.tauri.app/config/2",
"productName": "ShadowBroker",
"version": "0.9.8",
"version": "0.9.79",
"identifier": "com.shadowbroker.desktop",
"build": {
"frontendDist": "../../../frontend/out",
+2 -2
View File
@@ -1,12 +1,12 @@
{
"name": "frontend",
"version": "0.9.8",
"version": "0.9.79",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "frontend",
"version": "0.9.8",
"version": "0.9.79",
"dependencies": {
"@mapbox/point-geometry": "^1.1.0",
"@tauri-apps/plugin-process": "^2.3.1",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "frontend",
"version": "0.9.8",
"version": "0.9.79",
"private": true,
"scripts": {
"dev": "node scripts/dev-all.cjs",
@@ -9,12 +9,12 @@ import {
} from '@/lib/updateRuntime';
const RELEASE: GitHubLatestRelease = {
html_url: 'https://github.com/BigBodyCobain/Shadowbroker/releases/tag/v0.9.8',
html_url: 'https://github.com/BigBodyCobain/Shadowbroker/releases/tag/v0.9.79',
assets: [
{ name: 'ShadowBroker_0.9.8_x64_en-US.msi', browser_download_url: 'https://example.test/windows.msi' },
{ name: 'ShadowBroker_0.9.8_x64-setup.exe', browser_download_url: 'https://example.test/windows-setup.exe' },
{ name: 'ShadowBroker_0.9.8_aarch64.dmg', browser_download_url: 'https://example.test/macos.dmg' },
{ name: 'ShadowBroker_0.9.8_amd64.AppImage', browser_download_url: 'https://example.test/linux.AppImage' },
{ name: 'ShadowBroker_0.9.79_x64_en-US.msi', browser_download_url: 'https://example.test/windows.msi' },
{ name: 'ShadowBroker_0.9.79_x64-setup.exe', browser_download_url: 'https://example.test/windows-setup.exe' },
{ name: 'ShadowBroker_0.9.79_aarch64.dmg', browser_download_url: 'https://example.test/macos.dmg' },
{ name: 'ShadowBroker_0.9.79_amd64.AppImage', browser_download_url: 'https://example.test/linux.AppImage' },
],
};
+93 -39
View File
@@ -20,75 +20,129 @@ import {
Heart,
} from 'lucide-react';
const CURRENT_VERSION = '0.9.8';
const CURRENT_VERSION = '0.9.79';
const STORAGE_KEY = `shadowbroker_changelog_v${CURRENT_VERSION}`;
const RELEASE_TITLE = 'Cumulative Fuel/CO2, AIS Resilience, and Data-Layer Repair';
const RELEASE_TITLE = 'Onboarding, Live Feeds, Mesh, and Agent Hardening';
const HEADLINE_FEATURES = [
{
icon: <Plane size={20} className="text-orange-400" />,
icon: <Bot size={20} className="text-purple-400" />,
accent: 'purple' as const,
title: 'Cumulative Fuel & CO2 per Flight',
subtitle: 'The aircraft tooltip now shows how much fuel each plane has actually burned in the air, not just the per-hour rate.',
title: 'Agentic onboarding for OpenClaw-compatible agents',
subtitle: 'First-time setup now includes local/direct agent connection, access-tier selection, copyable HMAC setup, and optional Tor hidden-service prep.',
details: [
'New flight_observations module tracks first-seen-at per ICAO24 hex. Multiplies the model-based rate by elapsed observation time to produce running totals — FUEL BURNED (gal) and CO2 EMITTED (kg) — in the EMISSIONS ESTIMATE block.',
'15-minute gap between sightings resets the session (treated as a new flight: landed and took off again, or transited a dead zone). The cumulative counter survives trail pruning so map-rendering lifecycle and emission tracking are independent.',
'24-hour clamp defends against clock-skew bugs; per-icao prune every 5 minutes keeps memory bounded. The per-hour rate is still shown as smaller context underneath each cumulative figure.',
'The onboarding flow can generate the local agent connection bundle through the existing HMAC API, point agents at /api/ai/tools, and let operators choose restricted read-only or full write access before connecting an agent.',
'Remote mode is labeled honestly: .onion exposes the signed HTTP agent API over Tor. Wormhole/MLS is not claimed as the current agent command transport.',
'The setup copy works for OpenClaw, Hermes, or any custom agent that implements the documented HMAC request contract.',
],
callToAction: 'OPEN A FLIGHT TOOLTIP → EMISSIONS ESTIMATE',
callToAction: 'OPEN FIRST-TIME SETUP -> AI AGENT',
},
{
icon: <Network size={20} className="text-amber-400" />,
accent: 'cyan' as const,
title: 'AIS Maritime Resilience — Outage Banner + AISHub Fallback',
subtitle: 'When AISStreams WebSocket goes offline (as happened upstream in May 2026), the ships layer no longer goes silently empty.',
icon: <Bot size={20} className="text-purple-400" />,
accent: 'purple' as const,
title: 'Agentic AI Channel — supports OpenClaw and any HMAC-signing agent',
subtitle: 'ShadowBroker now exposes a signed agent command channel. Bring your own agent (OpenClaw, Claude Code, GPT, LangChain, or a custom client) and drive the dashboard from any LLM that speaks the protocol.',
details: [
'AIS proxy health surfaces in /api/health: connected, last_msg_age_seconds, proxy_spawn_count. A dismissible amber banner explains the outage (“Ship data temporarily unavailable — AISStream upstream is offline”) instead of letting users assume their install is broken.',
'AISHub REST fallback (free tier at aishub.net/api). Polls every 20 minutes when the primary is disconnected and merges vessels into the same store with source: “aishub” so existing tooling attributes the provider.',
'Live data wins races: if the WebSocket reconnects mid-poll, fresh AISStream updates arent overwritten by stale REST records. Opt-in via AISHUB_USERNAME; cadence configurable via AISHUB_POLL_INTERVAL_MINUTES (clamped [1, 360]).',
'A signed command channel (POST /api/ai/channel/command) plus a batched concurrent-execution endpoint (up to 20 tool calls per round-trip via /api/ai/channel/batch). Agents query flights, ships, SIGINT, news, and intel layers; reason over the live mesh; and run market or threat analyses without a human in the loop.',
'HMAC-SHA256 request signing with timestamp + nonce replay protection. Tier-gated access (restricted vs full) governs which read and write commands the agent can invoke. Every call is auditable through the channel log.',
'ShadowBroker does not bundle an LLM, an agent runtime, or model weights — it ships the protocol. Any agent that signs requests with the documented HMAC contract can connect. OpenClaw is the reference implementation.',
],
callToAction: 'SET AISHUB_USERNAME \u2192 RESTART BACKEND',
callToAction: 'CONNECT YOUR AGENT \u2192 /API/AI/CHANNEL/COMMAND',
},
{
icon: <Shield size={20} className="text-cyan-400" />,
icon: <Network size={20} className="text-cyan-400" />,
accent: 'cyan' as const,
title: 'Data-Layer Repair \u2014 UAP Cutoff + GPS Jamming Detection',
subtitle: 'Two long-broken layers fixed at the source. UFO sightings are actually recent now; GPS jamming zones actually fire.',
title: 'InfoNet Testnet \u2014 Framework, Privacy, and a Path to Decentralized Intelligence',
subtitle: 'The testnet now ships its full governance economy and the runway for a privacy-preserving decentralized intelligence platform.',
details: [
'UAP sightings: the Hugging Face NUFORC mirror fallback had no date cutoff, so when the live nuforc.org scrape failed the layer served 3-year-old reports as \u201crecent\u201d. Now drops rows older than 60 days and logs loudly when the mirror is fully stale. Scheduler moved daily \u2192 weekly (Mondays 12:00 UTC).',
'GPS jamming: three stacked filters meant the layer almost never lit up. nac_p == 0 (\u201cGPS lock lost\u201d) was filtered out as if it were an old transponder \u2014 it\u2019s actually the strongest jamming signal. Now counted. MIN_AIRCRAFT lowered 5 \u2192 3 so sparser hotspots clear; MIN_RATIO lowered 0.30 \u2192 0.20.',
'Both layers now surface their own outages via assert_canary so operators see broken vs empty, not silently stale.',
'Sovereign Shell views: petitions (governance DSL covers parameter updates and feature toggles), upgrade-hash voting (80% supermajority, 67% Heavy-Node activation), evidence submission, dispute markets, gate suspension and shutdown, and bootstrap eligible-node-one-vote. Every write action is a clickable form with verbatim diagnostics on rejection.',
'Privacy primitive runway: locked Protocol contracts for ring signatures, stealth addresses, shielded balances, and DEX matching. The privacy-core Rust crate is the integration target. Function Keys (anonymous citizenship proof) ship 5 of 6 pieces; only blind-signature issuance waits on a primitive decision.',
'Backbone: two-tier event state with epoch finality, identity rotation, progressive penalties, ramp milestones, and constitutional invariants enforced via MappingProxyType. Sprint 11+ wires the cryptographic primitives into the locked Protocols.',
'Still an experimental testnet \u2014 no privacy guarantee yet. Treat all channels as public until E2E and the privacy primitives ship.',
],
callToAction: 'TOGGLE UAP \u2022 GPS JAMMING LAYERS',
callToAction: 'OPEN SOVEREIGN SHELL \u2192 PETITIONS \u2022 UPGRADES \u2022 GATES',
},
];
const NEW_FEATURES = [
{
icon: <Plane size={18} className="text-cyan-400" />,
title: 'Per-Flight Source Attribution',
desc: 'Every aircraft record now carries a source field (adsb.lol, OpenSky, airplanes.live, adsb.fi) so consumers can attribute the data provider. Pre-fix, adsb.lol records were unmarked while OpenSky records were explicitly tagged, making it look like adsb.lol was unused even though it is the primary source.',
icon: <Clock size={18} className="text-cyan-400" />,
title: 'Startup and Feed Responsiveness Pass',
desc: 'Map-critical feeds now lean on startup caches and priority preload behavior so the dashboard can paint before heavyweight synthesis jobs finish.',
},
{
icon: <Network size={18} className="text-green-400" />,
title: 'Cross-Node DM Mailbox Replication',
desc: 'Direct messages now replicate across mesh nodes when one party is offline. Per-(sender, recipient) anti-spam cap enforced as a network rule (not client-side) so source-code tampering cannot bypass it.',
title: 'MeshChat MQTT Settings',
desc: 'Public MeshChat stays opt-in and now has an in-panel settings lane for broker, port, username, password, and channel PSK while remaining separated from Wormhole/private mode.',
},
{
icon: <Clock size={18} className="text-amber-400" />,
title: 'Infonet Sync — HTTP 429 Honored',
desc: 'When an upstream peer returns Retry-After, the node now waits exactly that long instead of retrying every 60 seconds and keeping the upstream rate-limit bucket permanently full. Exponential backoff on consecutive failures capped at 30 minutes.',
icon: <Plane size={18} className="text-cyan-400" />,
title: 'Selected Entity Trails',
desc: 'Flight and vessel trails are drawn only for selected assets, reducing global clutter while still exposing movement history for unknown-route entities.',
},
{
icon: <Plane size={18} className="text-amber-400" />,
title: 'Aircraft Detail Cards',
desc: 'Commercial aircraft stay airline-first, while private and general aviation aircraft can show model-focused Wiki context and imagery when available.',
},
{
icon: <Cpu size={18} className="text-purple-400" />,
title: 'AI Batch Command Channel',
desc: 'POST up to 20 tool calls in a single HTTP round-trip; the backend executes them concurrently and returns a fan-out result map. Cuts agent latency by an order of magnitude over sequential calls.',
},
{
icon: <Scale size={18} className="text-amber-400" />,
title: 'Governance DSL — Petition-Driven Parameter Changes',
desc: 'Type-safe payload executor for UPDATE_PARAM, BATCH_UPDATE_PARAMS, ENABLE_FEATURE, and DISABLE_FEATURE petitions. Tunable knobs change on-chain via a vote — no code deploys required.',
},
{
icon: <GitBranch size={18} className="text-purple-400" />,
title: 'Upgrade-Hash Governance',
desc: 'Protocol upgrades that need new logic (not just parameter changes) vote on a SHA-256 hash of the verified release. 80% supermajority, 40% quorum, 67% Heavy-Node activation. Lifecycle: signatures, voting, challenge window, awaiting readiness, activated.',
},
{
icon: <KeyRound size={18} className="text-purple-400" />,
title: 'Function Keys — Anonymous Citizenship Proof',
desc: 'A citizen proves "I am an Infonet citizen" without revealing their Infonet identity. 5 of 6 pieces shipped: nullifiers, challenge-response, two-phase commit receipts, enumerated denial codes, batched settlement. Issuance via blind signatures waits on a primitive decision.',
},
{
icon: <Shield size={18} className="text-cyan-400" />,
title: 'Privacy Primitive Runway',
desc: 'Locked Protocol contracts in services/infonet/privacy/contracts.py for ring signatures, stealth addresses, Pedersen commitments, range proofs, and DEX matching. The privacy-core Rust crate is the integration target — no caller of the privacy module needs to know which scheme is active.',
},
{
icon: <Layers size={18} className="text-blue-400" />,
title: 'Two-Tier State + Epoch Finality',
desc: 'Tier 1 events propagate CRDT-style for low latency; Tier 2 events require epoch finality before they can be acted on. Identity rotation, progressive penalties, ramp milestones, and constitutional invariants are enforced via MappingProxyType.',
},
{
icon: <Terminal size={18} className="text-cyan-400" />,
title: 'Sovereign Shell Write Surface',
desc: 'PetitionsView, UpgradeView, ResolutionView, GateShutdownView, BootstrapView, and FunctionKeyView each expose every Sprint 4-8 + 10 write action as a clickable form. Adaptive polling tightens to 8 seconds during active voting/challenge phases.',
},
{
icon: <Clock size={18} className="text-pink-400" />,
title: 'Time Machine — Snapshot Playback',
desc: 'Scrub backward through saved telemetry. Live polling pauses on entry to snapshot mode, the map redraws from the recorded snapshot, and moving entities interpolate between recorded frames. Hourly index lets you jump to any captured timestamp; pressing Live restores the current feed instantly.',
},
{
icon: <Satellite size={18} className="text-orange-400" />,
title: 'SAR Satellite Telemetry — ASF, OPERA, Copernicus',
desc: 'New SAR (Synthetic Aperture Radar) layer. Mode A (default-on) pulls free catalog metadata from the Alaska Satellite Facility — no account required. Mode B (two-step opt-in) ingests pre-processed ground-change anomalies from NASA OPERA, Copernicus EGMS, GFM, EMS, and UNOSAT — deformation, flood, and damage assessments. Integrates with OpenClaw so agents can read and act on SAR anomalies; broadcasts default to private-tier transport (Tor / RNS).',
},
];
const BUG_FIXES = [
'UAP layer no longer serves 3-year-old NUFORC sightings via the Hugging Face static-mirror fallback (60-day cutoff now applied to the fallback path too).',
'GPS jamming detection now counts nac_p == 0 (the actual GPS-lost signal) instead of filtering it out as an old-transponder artifact.',
'GPS jamming thresholds lowered (MIN_AIRCRAFT 5 → 3, MIN_RATIO 0.30 → 0.20) so sparser hotspots clear the bar without losing the 1-aircraft noise cushion.',
'AIS layer surfaces an outage banner when the AISStream WebSocket upstream is offline, instead of silently showing an empty ocean.',
'Flight emissions tooltip now shows cumulative fuel/CO2 since first observation, not just the per-hour rate.',
'Per-aircraft observation tracker (15-min reopen gap, 24-hour clamp) survives trail-rendering cache pruning so cumulative counters do not reset mid-flight.',
'UAP scheduler moved daily → weekly (Mondays 12:00 UTC) to match the layers rolling-window cadence and reduce upstream load.',
'Docker proxy and backend port handling hardened so changing the host backend port does not require changing the internal service contract.',
'Global Threat Intercept and live-data startup paths no longer wait on slow-tier synthesis before cached data can paint the UI.',
'MeshChat and Infonet statuses now separate public MQTT participation, private Wormhole mode, and local node bootstrap so the UI does not imply the wrong connection state.',
'Commercial aircraft detail cards no longer show a confusing model image alongside the airline card.',
'Sovereign Shell adaptive polling — voting and challenge windows refresh every 8 seconds while active, every 30 to 60 seconds when idle. Voting feels live without a websocket layer.',
'Per-row write actions (petitions, upgrades, disputes) hold isolated submission state so concurrent forms no longer share a single in-flight slot.',
'Verbatim diagnostic surfacing on every write button. The backend reason text is always shown on rejection — no opaque "denied" toasts.',
'Evidence submission canonicalization matches Python repr() exactly, so client-side SHA-256 hashes round-trip cleanly through the chain.',
'Function Keys copy is context-agnostic — citizenship proof is described abstractly, not tied to a specific use case.',
'Post-cutover legacy mesh files (mesh_schema.py, mesh_signed_events.py, mesh_hashchain.py) hash-verified against the recorded baseline; the chain extension hook stays surgical.',
];
const CONTRIBUTORS = [
+11 -47
View File
@@ -249,70 +249,34 @@ const VESSEL_TYPE_WIKI: Record<string, string> = {
type FlightTrailPoint = { lat?: number; lng?: number; alt?: number; ts?: number } | number[];
function formatObservedDuration(seconds: number): string {
// Compact "1h 14m" / "23m" / "45s" — matches the density of the rest
// of the flight tooltip. < 60s is shown as "<1m" so the user knows
// we've JUST started observing this hex (cumulative will still be 0).
if (!Number.isFinite(seconds) || seconds <= 0) return '<1m';
if (seconds < 60) return '<1m';
const totalMinutes = Math.floor(seconds / 60);
const hours = Math.floor(totalMinutes / 60);
const minutes = totalMinutes % 60;
if (hours > 0) return `${hours}h ${minutes}m`;
return `${minutes}m`;
}
function EmissionsEstimateBlock({ flight }: { flight: any }) {
const emissions = flight?.emissions;
// Cumulative fuel/CO2 since the backend first saw this hex this
// flight session. Prefer these big numbers — the user explicitly
// wanted "the actual fuel that has been burned", not the rate.
// Rates are still shown below as smaller context.
const observedSec = Number(emissions?.observed_seconds ?? 0);
const fuelBurned = Number(emissions?.fuel_gallons_burned ?? 0);
const co2Emitted = Number(emissions?.co2_kg_emitted ?? 0);
const haveCumulative = emissions && observedSec > 0;
const context = emissions ? 'Model-based cruise estimate' : null;
return (
<div className="border-b border-[var(--border-primary)] pb-2">
<span className="text-[var(--text-muted)] text-[10px] block mb-1.5">EMISSIONS ESTIMATE</span>
<div className="flex gap-3">
<div className="flex-1 bg-[var(--bg-primary)]/50 border border-[var(--border-primary)] px-2 py-1.5">
<div className="text-[11px] text-[var(--text-muted)] tracking-widest">FUEL BURNED</div>
<div className="text-sm font-bold text-orange-400">
{haveCumulative ? (
<>{fuelBurned.toLocaleString(undefined, { maximumFractionDigits: 1 })} <span className="text-[11px] text-[var(--text-muted)] font-normal">gal</span></>
) : emissions ? (
<span className="text-[var(--text-muted)] font-normal text-xs"></span>
<div className="text-[11px] text-[var(--text-muted)] tracking-widest">FUEL RATE</div>
<div className="text-xs font-bold text-orange-400">
{emissions ? (
<>{emissions.fuel_gph} <span className="text-[11px] text-[var(--text-muted)] font-normal">GPH</span></>
) : 'UNKNOWN'}
</div>
{emissions && (
<div className="text-[10px] text-[var(--text-muted)] mt-0.5">
@ {emissions.fuel_gph} gph
</div>
)}
</div>
<div className="flex-1 bg-[var(--bg-primary)]/50 border border-[var(--border-primary)] px-2 py-1.5">
<div className="text-[11px] text-[var(--text-muted)] tracking-widest">CO2 EMITTED</div>
<div className="text-sm font-bold text-red-400">
{haveCumulative ? (
<>{co2Emitted.toLocaleString(undefined, { maximumFractionDigits: 1 })} <span className="text-[11px] text-[var(--text-muted)] font-normal">kg</span></>
) : emissions ? (
<span className="text-[var(--text-muted)] font-normal text-xs"></span>
<div className="text-[11px] text-[var(--text-muted)] tracking-widest">CO2 RATE</div>
<div className="text-xs font-bold text-red-400">
{emissions ? (
<>{emissions.co2_kg_per_hour.toLocaleString()} <span className="text-[11px] text-[var(--text-muted)] font-normal">KG/HR</span></>
) : 'UNKNOWN'}
</div>
{emissions && (
<div className="text-[10px] text-[var(--text-muted)] mt-0.5">
@ {emissions.co2_kg_per_hour.toLocaleString()} kg/hr
</div>
)}
</div>
</div>
{emissions && (
{context && (
<div className="mt-1.5 text-[10px] text-[var(--text-muted)] leading-relaxed">
{haveCumulative
? `Observed in flight for ${formatObservedDuration(observedSec)} · model-based cruise estimate`
: 'Just observed · totals will appear on next refresh'}
{context}
</div>
)}
</div>
+1 -1
View File
@@ -4,7 +4,7 @@ import React, { useState, useEffect } from 'react';
import { motion, AnimatePresence } from 'framer-motion';
import { X, ExternalLink, Key, Shield, Radar, Globe, Satellite, Ship, Radio, Bot, Copy, Check, Network } from 'lucide-react';
const CURRENT_ONBOARDING_VERSION = '0.9.8-agentic-onboarding-1';
const CURRENT_ONBOARDING_VERSION = '0.9.79-agentic-onboarding-1';
const STORAGE_KEY = `shadowbroker_onboarding_complete_v${CURRENT_ONBOARDING_VERSION}`;
const LEGACY_STORAGE_KEY = 'shadowbroker_onboarding_complete';
@@ -4,7 +4,7 @@ import React, { useEffect, useState } from 'react';
import { motion, AnimatePresence } from 'framer-motion';
import { Database, Clock, X } from 'lucide-react';
const CURRENT_VERSION = '0.9.8';
const CURRENT_VERSION = '0.9.79';
const STORAGE_KEY = `shadowbroker_startup_warmup_notice_v${CURRENT_VERSION}`;
interface StartupWarmupModalProps {
+2 -2
View File
@@ -1,8 +1,8 @@
---
apiVersion: v2
name: shadowbroker
version: 0.9.8
appVersion: "0.9.8"
version: 0.9.79
appVersion: "0.9.79"
description: simple shadowbroker installation
type: application
+1 -1
View File
@@ -1,6 +1,6 @@
[project]
name = "shadowbroker"
version = "0.9.8"
version = "0.9.79"
readme = "README.md"
requires-python = ">=3.10"
dependencies = []
Generated
+2 -2
View File
@@ -74,7 +74,7 @@ wheels = [
[[package]]
name = "backend"
version = "0.9.8"
version = "0.9.79"
source = { editable = "backend" }
dependencies = [
{ name = "apscheduler" },
@@ -2231,7 +2231,7 @@ wheels = [
[[package]]
name = "shadowbroker"
version = "0.9.8"
version = "0.9.79"
source = { virtual = "." }
[package.metadata]