NorviTech/armiger-swarm-survival

Armiger Plugin #1 — Swarm Survival & Honeypot Adapter (SwarmSurvivalNet v2)

48-tensor PyTorch content-gated residual adapter that predicts real-world torrent download completion (96.83% Warehouse AUROC / 92.42%–93.03% Public-Tracker AUROC) and blocks 100.0% of fake-seeder malware honeypots while guaranteeing 0% content-category flips.
Available standalone here and pre-bundled inside NorviTech/armiger-ultra.

Overview

Raw tracker seeder counts are an unreliable predictor of whether a torrent grab will actually complete (53.02% AUROC across multi-source warehouse swarms and 85.17% on single-source public trackers):

1. Fake-Seeder Malware Honeypots spoof 5,000+ seeders on day zero for unreleased movies or games while bundling .exe / .lnk / .scr / codec-pack payloads.
2. Stale Tracker Scrapes vs. DHT/PEX Survival: Niche anime, audiobooks, and remuxes often report 0 cached tracker seeders yet complete reliably via DHT/PEX, whereas poisoned swarms stall at 99.9%.

NorviTech/armiger-swarm-survival (swarm_adapter.pt + swarm_survival.py) loads all 48 neural tensors (swarm_mlp, cross_gate, content_proj, Way3SwarmAnomalyHead, and Way4ViabilityHead) into PyTorch nn.Module layers (SwarmResidualAdapter) and executes the learned neural forward pass (self.forward(...)) inside evaluate_swarm(...).

Measured Performance (Audited Holdout Splits)

Metric	Raw Tracker Seeders	Raw DHT Peers	Armiger (Way-4 Formula)	Armiger Ultra + swarm_adapter.pt (48-Tensor Neural)
Multi-Source Warehouse Holdout AUROC (N=10,278)	53.02%	51.84%	86.64%	96.83% (97.90% AUPRC)
Public-Tracker Benchmark AUROC (N=757)	85.17%	86.81%	86.64%	92.42% (+7.25 pp vs. seeders)
Public-Tracker Holdout AUROC (N=493)	85.17%	86.81%	86.64%	93.03%
Fake-Seeder Honeypot Trap Recall (@ <=0.5% FPR)	0.00%	0.00%	99.90%	100.00%
Content Category Flip Rate (seeders=0 vs seeders=10,000)	N/A	N/A	0.00%	0.00%

Quickstart

from swarm_survival import SwarmResidualAdapter

adapter = SwarmResidualAdapter.from_pretrained("swarm_adapter.pt")
result = adapter.evaluate_swarm(
    title="Tears.of.Steel.2012.2160p.UHD.BluRay.x265-OPEN",
    seeders=42,
    leechers=5,
    completed=310,
    total_size_bytes=28_500_000_000,
    files=[{"path": "Tears.of.Steel.2012.2160p.mkv", "size": 28_500_000_000}],
    sources=["bt1.archive.org"],
    category_pred="movie",
    p_junk_neural=0.002,
)
print(result)

Part of the Armiger Modular Plugin Suite

Plugin Repository	Bundled in Armiger Ultra?	Footprint	Core Capability & Measured Impact (Unmutated Ground-Truth Keys)
NorviTech/armiger-swarm-survival	Yes (swarm_adapter.pt, swarm_survival.py)	167 KB (132 KB .pt)	SwarmSurvivalNet v2 & Honeypot Residual Adapter: Executes full 48-tensor neural forward pass (SwarmResidualAdapter); 96.83% Multi-Source Warehouse AUROC (N=10,278, vs. 53.02% raw seeders), 92.42% / 93.03% Public-Tracker AUROC (N=757 / N=493, vs. 85.17% raw seeders), 100.0% fake-seeder malware trap recall, 0.00% content-category flip guarantee.
NorviTech/armiger-swarm-priors	Yes (swarm_priors.py)	29.3 KB	Empirical Bayes Swarm & Release-Group Priors: 4-pathway tracker scrape prior engine (86.64% formula AUROC), mandatory modality dropout (p=0.60), anomaly feature extraction, and public-tracker passkey safety filter.
NorviTech/armiger-zero-cue-catalog	Yes (zero_cue_plugin.py, validated_zero_cue_catalog.json)	26.0 MB (BLAKE2b-64)	Zero-Cue Catalog & Structural Disambiguator: Offline 929,400-entry BLAKE2b-64 cryptographically hashed catalog (472,017 (title, year), 257,016 anime stems, 200,367 long titles) + deterministic structural rules; lifts 5-split (N=10,262) weighted category accuracy from 94.00% (Standalone Neural) to 95.42% (Fair Blind Hybrid), beyond_confirmation (N=1,025) from 92.88% to 95.12%, and tc_truespec_2000 (N=2,000) from 87.40% to 91.50% (+4.10 pp).
NorviTech/armiger-audio-guard	Yes (audio_language_guard.py)	3.3 KB	Cross-Head Audio Language & Anime Dub Guard: Couples title_language (P(Foreign Title)) with lang head to disambiguate .en. prepositions, <Foreign>.ENG.Sub, regional dubs, and MULTi (FR EN) tags; lifts binary English-vs-Foreign audio accuracy on oct15_confirmation (N=545) from 96.88% (Standalone Neural) to 97.80% (92.75% 3-class N=772).
NorviTech/armiger-calibration-dht	Yes (calibration.json, calibration_and_dht.py, armiger_dht_rsi.py)	181 KB	Conformal Calibration, BEP-44 DHT Updater & Distributed RSI Engine: Per-head temperature scaling ($T_h$), Mondrian safety gates (100.00% junk accuracy on oct15_confirmation N=2,170 & fresh_confirmation N=1,291, 99.90% on beyond_confirmation N=977), Hybrid Ed25519+WOTS+-SHAKE256 signed BEP-44/BEP-46 DHT hot-reload, Hybrid X25519+ML-KEM-768+ChaCha20-Poly1305 AEAD, distinct-ASN quorum, and 500-canary regression gate (61/61 unit tests, 4/4 multi-instance transfer tests, 45/45 red-team exploit probes blocked).
NorviTech/armiger-dht-db-sync	Yes (csam_guard.py, armiger_dht_db_sync.py)	155 KB	Modular, CSAM-Protected, Encrypted BEP-44/BEP-46 DHT Database Sync: Multi-stage CSAM & abuse pre-ingest blocker, Hybrid PQ-signed blinded SHA-256 tombstone purge engine, 10-category $\times$ 14-language $\times$ 7-quality sharded subscriptions with strict default-off xxx isolation, X25519+ML-KEM-768+ChaCha20-Poly1305 AEAD, binary Merkle proofs, and $K$-of-$N$ distinct-ASN Sybil quorum (37/37 unit + 12-node localhost UDP Kademlia BEP-44/46 wire tests, 45/45 red-team exploit probes blocked).

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Intended Use & Legal Compliance

Armiger, Armiger Ultra, and all bundled plugins are open-source machine learning and cryptographic metadata-classification utilities designed strictly for lawful use cases, including:

• Organizing and indexing licensed, public-domain, Creative Commons, and open-source digital media, software distributions (e.g., Linux ISOs, open-source games), and educational archives (e.g., OpenCourseWare, LibriVox, Project Gutenberg).
• Automated cybersecurity screening, fake-seeder honeypot detection, and disguised executable/malware filtering (.mkv.exe, .scr, .vbs) in peer-to-peer and decentralized storage research.
• Child safety (CSAM/CSAE) pre-ingest blocking, cryptographic tombstone revocation, and adult/NSFW namespace isolation for self-hosted and decentralized indexers.

NorviTech does not condone, encourage, or support copyright infringement or the unauthorized distribution of copyrighted works. Users are solely responsible for ensuring that their use of these models and plugins complies with all applicable local, national, and international copyright and data-protection laws.

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Armiger Ultra · Armiger · Swarm Survival · Swarm Priors · Zero-Cue Catalog · Audio Guard · Calibration & DHT RSI · DHT DB Sync · norvitech.com