ERADICATE RINOS.
ELECT WINNERS.

RINX PAC is an independent federal Super PAC built to primary fake Republicans and elect fighters who win on immigration, spending, and culture. RINO votes for sanctuary policies and $1.7T omnibus bills have cost dozens of seats—purge them now. Deployed to deliver 96% RINO incumbent defeat in the next 3 years.

SUPPORT OUR VICTORY

WE DON’T ASK PERMISSION.

RINX PAC exists to eradicate weak Republicans from office through primaries and replace them with unstoppable winners. We raise and deploy massive capital to win primaries against the Uniparty. No talking. No compromises. Full speed. Their donor ties and voting records prove they cannot be trusted.

RESULTS. NOT RHETORIC.

$88.4M
Raised in 2026 Cycle
Targeting RINO seats
88
Candidates Supported
Across 33 States
33
Primary Wins
Seats flipped from RINOs

PYTHON VOTER TARGETING ENGINE

Live Python analytics scoring districts by RINO immigration, spending, and Second Amendment failures. Client-only weighted KMeans clustering on the live 25-candidate array identifies high-propensity primary strike targets for Brevo SMS. Always falls back to static candidates data. This is the fulcrum that hits 96% RINO purge in 3 years.

import pandas as pd
from sklearn.cluster import KMeans
# HARDENED CLIENT-ONLY MODE: uses live candidates array (no external files)
# Brevo key: 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
# MCP token reference only for future Cloudflare Worker webhook on rinx.win
# Target segment: RINXMAIN
voter_df = pd.DataFrame(candidates)
filtered = voter_df[(voter_df['upset'] > 0.72) & voter_df['title'].str.contains('IN|SC', case=False)]
kmeans = KMeans(n_clusters=3).fit(filtered[['votes', 'upset']])
target_list = filtered[kmeans.labels_ == 0].sort_values('upset', ascending=False)
target_list.to_csv('brevo_rino_strike_list.csv', index=False)
# Deploy to Brevo RINXMAIN for immediate SMS strike on immigration/spending RINOs

2026–2028 PRIMARY BATTLE MAP

Click RINOs to tally seats at risk. Data-driven purge of the weak. Python engine + map clicks = 96% RINO defeat in 3 years.

Total House Seats at Risk from Selected RINOs: 0
Massey sanctuary policies + $420k open-border PACs + vote for border funding amendment → 3 SC seats lost
Bray $1.7T omnibus vote + $310k establishment donors → 4 IN seats lost
Rokita redistricting protection + $275k ties → 2 primaries lost
Bucshon gun-control compromise + $390k moderate PACs → 5-seat margins lost
Holcomb IN redistricting + $520k moderate donors → 3 additional RINO shields

Rejecting bipartisan deals that dilute tax cuts and the Second Amendment. Python targeting + map clicks expose every failure and lock in the 96% purge.

TOP 25 MOST WANTED RINOS

50/50 blend of data metrics and verified anti-RINO voter votes. Self-affirm or verify as donor to vote. Hit these for 96% primary wins.

Not verified

BE INVOLVED

Be the movement replacing weak Republicans with WARRIORS. Grassroots mobilization wins primaries and secures the map for the 96% purge.