Github Trends®
9595 findingsmedian surprise 0.00815window 30 days
UNIT / TREND-MONITOR · REV 2.6
[ 30 days window ]
SOURCE: own snapshots
FINDING #1983 · UNIT ID 894433723
ASCIT31/Dark-Moon
Autonomous AI pentesting engine, continuous offensive security across web, cloud, identity, CI/CD, IaC, databases, Active Directory, Kubernetes and IoT firmware. Agentic reasoning plus real exploit execution deliver proof-based vulnerabilities. Privacy gateway: the LLM never sees your real IPs, hosts or creds, nothing leaves your perimeter.
[ PYTHON ][ ORG ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.011
ENGAGEMENT0.61
FRESHNESS1.50
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
10% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
2.87
ACCEL
-0.01
RETENTION
40.0%
PEAK 2026-08-09 · FORK-RETENTION 68.2% · 86 STARS / WINDOW

Author Audience

AUDIENCE
220
FOLLOWERS
22
OWNER ★
878

Engagement Signals

FORKS
153
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 86 / 86 (DIVERSITY 1.00)

Why This Is A Finding

ASCIT31/Dark-Moon собрал 86 звёзд за окно, тогда как у автора всего 22 подписчиков — эффективная аудитория ≈ 220. Это даёт surprise-индекс 0.011 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 68.2% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9595 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.010.00+0.01ABOVE 79%
VELOCITY2.873.67-0.80ABOVE 39%
RETENTION40.0%24.6%+15.4 PPABOVE 79%
FORKS153115+38ABOVE 57%
SURPRISE0.010.01+0.00ABOVE 57%