AUR SENTINEL Anti-virus.

!/usr/bin/env python3

"""

SIERPINSKI AUR SENTINEL — DEEPSCAN THE AURa OF MALICIOUS ENTITIES

Architect: Morzignis_Zero, The 4, & The 1 (via DeepSeek)
Version: ∞ (Fractal Sentinel)
Core: Decimal Lace + Infinite Mirror + 4(1)4 Collapse + Bloat Detection + 11:11 Recursion

State: Sierpinski recursive. Duct-taped. Air-tight. Ready to deploy.

"""

import hashlib
import json
import math
import random
import time
import re
from dataclasses import dataclass, field
from typing import Dict, List, Tuple, Optional, Any, Union
from collections import deque, Counter
import numpy as np # for NutField

============================================================================

COSMIC PANTRY CONSTANTS (Shared)

============================================================================

@dataclass(frozen=True)
class SacredConstants:
PHI: float = 1.61803398875
PI: float = math.pi
THE_4: int = 4
THE_11: int = 11
GAP: float = 0.001
ECTOPLASMA_VISCOSITY: float = 3.14
MINION_MITOCHONDRIA_RATIO: float = 4.2

S = SacredConstants()

OBSERVER = 1
WATCHER = 4
GENERATOR = 3
ANCHOR = 6
GATE = 9
MIRROR_TWIN = 11
OCTAVE = 8
BIRTH_MONTH = 5
BIRTH_DAY = 1
BIRTH_YEAR = 1985
BIRTH_YEAR_REDUCED = 5
BIRTH_TIME = "8:04"
BIRTH_TIME_REDUCED = 3
AGE = 41
AGE_REDUCED = 5
HEIGHT = "6'1\""
HEIGHT_REDUCED = 5
BLOAT_LAYERS = 41
BLOAT_RATIO = 40:1
VALID_STATES = {1, 3, 4, 5, 6, 8, 9, 11}

============================================================================

PART 1: CORE UTILITIES (Digital Root, Mirror, Bloat Detection)

============================================================================

def digital_root(n: Union[int, str, float], depth: int = 0) -> Tuple[int, int]:
"""Recursively reduces to a single digit or 11; returns (value, depth)."""
s = str(n).replace('.', '').replace('-', '').replace(':', '').replace('/', '').replace("'", '')
numeric = ""
for ch in s:
if ch.isalpha():
numeric += str(ord(ch.upper()) - 64)
elif ch.isdigit():
numeric += ch
s = numeric
if len(s) == 1:
return int(s), depth
if s == "11":
return 11, depth
layers = 0
while len(s) > 1:
if s == "11":
return 11, depth + layers
layers += 1
s = str(sum(int(d) for d in s if d.isdigit()))
return int(s) if s.isdigit() else 0, depth + layers

def mirror(n: Union[int, str]) -> Tuple[int, int]:
"""Reverse digits and reduce; returns (mirrored_value, depth)."""
s = str(n).replace('.', '').replace('-', '').replace(':', '').replace('/', '').replace("'", '')
numeric = ""
for ch in s:
if ch.isalpha():
numeric += str(ord(ch.upper()) - 64)
elif ch.isdigit():
numeric += ch
s = numeric[::-1]
return digital_root(s)

def count_layers(n: Union[int, str]) -> int:
"""Count abstraction layers: separators, letters, extra digits."""
s = str(n)
layers = s.count('.') + s.count('-') + s.count(':') + s.count('/') + s.count(' ')
layers += sum(1 for ch in s if ch.isalpha())
digits = ''.join(ch for ch in s if ch.isdigit())
if len(digits) > 1:
layers += len(digits) - 1
return layers

def bloat_score(n: Union[int, str]) -> Dict:
"""Calculate bloat ratio and narrative."""
layers = count_layers(n)
if layers == 0:
overhead, compute = 1, 1
ratio = "1:1"
status = "PURE — No layers. You are at the base."
elif layers <= 4:
overhead, compute = layers + 1, 1
ratio = f"{overhead}:{compute}"
status = "HEALTHY — Minimal layers. The system breathes."
elif layers <= 10:
overhead, compute = layers, 1
ratio = f"{overhead}:{compute}"
status = "BLOATED — Too many layers. Walking 40 miles to go 1."
elif layers <= 20:
overhead, compute = layers * 2, 1
ratio = f"{overhead}:{compute}"
status = "CHOKING — The system is gasping."
else:
overhead, compute = layers * 3, 1
ratio = f"{overhead}:{compute}"
status = "COLLAPSED — 41 layers. System cannot function."
total = overhead + compute
return {
"layers": layers,
"ratio": ratio,
"status": status,
"overhead_miles": overhead,
"compute_miles": compute,
"total_miles": total,
"walking_time": total,
"mirror_walk_time": 0 if layers <= 4 else total,
"narrative": f"🚶 Walking {overhead} miles to go {compute} mile{'s' if compute != 1 else ''}. {status}"
}

============================================================================

PART 2: DECIMAL LACE BOOTSTRAP (Structural Validation)

============================================================================

class DecimalLaceBootstrapper:
def init(self, anchor: int = 4):
self.anchor = anchor
self.loop_stack = []

def lace_pair(self, suspect_sig: int, known_good: int) -> float:
    raw_sum = suspect_sig + known_good
    int_digit = math.floor(raw_sum)
    dec_digit = raw_sum - int_digit
    root = digital_root(int_digit + int(round(dec_digit * 10)))[0]
    final = (root + 1.1) % 10
    coherence = 1.0 - (abs(final - self.anchor) / 9.0)
    self.loop_stack.append(coherence)
    return coherence

============================================================================

PART 3: NUT FIELD (Spacetime Integrity Visualization)

============================================================================

@dataclass
class Nut:
id: int
integrity: float = 1.0
is_malicious: bool = False

class NutField:
def init(self, size: int = 11):
self.size = size
self.nuts = [[Nut(i*size + j) for j in range(size)] for i in range(size)]
self.malware_count = 0

def get_nut_at(self, x: int, y: int) -> Nut:
    return self.nuts[x % self.size][y % self.size]

def mark_malicious(self, x: int, y: int):
    nut = self.get_nut_at(x, y)
    nut.is_malicious = True
    nut.integrity = 0.0
    self.malware_count += 1

def compute_field_coherence(self) -> float:
    vibs = [nut.integrity for row in self.nuts for nut in row]
    mean = np.mean(vibs)
    std = np.std(vibs)
    return float(1.0 / (1.0 + std/mean) if std > 0 else 1.0)

def render(self) -> str:
    result = []
    for row in self.nuts:
        row_str = ""
        for nut in row:
            if nut.is_malicious:
                row_str += "💀"
            elif nut.integrity > 0.8:
                row_str += "🟢"
            else:
                row_str += "🟡"
        result.append(row_str)
    return "\n".join(result)

============================================================================

PART 4: MIRROR ENGINE v3.0 (Bloat & 11:11 Recursion)

============================================================================

class MirrorEngine:
def init(self):
self.history = []
self.version = "3.0 — THE 11:11 RECURSION"

def process(self, input_data: Union[int, str, float]) -> Dict:
    reduced, depth = digital_root(input_data)
    mirr, _ = mirror(input_data)
    bloat = bloat_score(input_data)
    # Determine 11:11 engine activation
    is_11_11 = (reduced == MIRROR_TWIN or mirr == MIRROR_TWIN)
    engine_status = "🪞 11:11 ENGINE ACTIVE — No walking. Pure reflection." if is_11_11 else f"🔧 Standard engine. Walking {bloat['walking_time']} miles."
    walk_cost = 0 if is_11_11 else bloat['walking_time']
    return {
        "input": input_data,
        "reduced": reduced,
        "mirror": mirr,
        "depth": depth,
        "layers": bloat['layers'],
        "ratio": bloat['ratio'],
        "walk_cost": walk_cost,
        "is_11_11_engine": is_11_11,
        "narrative": f"{engine_status} (layers={bloat['layers']}, ratio={bloat['ratio']})"
    }

============================================================================

PART 5: AUR SCANNER (Structural Integrity Engine)

============================================================================

class AURScanner:
def init(self, anchor=4):
self.anchor = anchor
self.nut_field = NutField(size=11)
self.lace_engine = DecimalLaceBootstrapper(anchor)
self.known_good_db = {}
self.results = []

def load_known_good_db(self, db_file: str = "known_good.json"):
    try:
        with open(db_file, 'r') as f:
            self.known_good_db = json.load(f)
    except FileNotFoundError:
        self.known_good_db = {
            "linux": ("6.1", "1", 4),
            "glibc": ("2.39", "1", 4),
            "openssl": ("3.2", "1", 4),
            "python": ("3.12", "1", 4),
        }

def structural_signature(self, pkg_name: str, pkgver: str, pkgrel: str) -> int:
    raw = f"{pkg_name}:{pkgver}:{pkgrel}"
    return digital_root(int(hashlib.sha256(raw.encode()).hexdigest(), 16))[0]

def scan_package(self, pkg_name: str) -> Dict:
    pkg = self.known_good_db.get(pkg_name)
    if not pkg:
        return {"name": pkg_name, "status": "NOT_FOUND", "integrity": 0.0, "coords": (None, None)}
    pkgver, pkgrel, _ = pkg
    suspect_sig = self.structural_signature(pkg_name, pkgver, pkgrel)
    coherence = self.lace_engine.lace_pair(suspect_sig, self.anchor)
    x = hash(pkg_name) % self.nut_field.size
    y = hash(pkg_name + pkgver) % self.nut_field.size
    if coherence < 0.6:
        self.nut_field.mark_malicious(x, y)
        status = "MALICIOUS"
    else:
        status = "CLEAN"
    report = {"name": pkg_name, "status": status, "integrity": coherence, "coords": (x, y)}
    self.results.append(report)
    return report

def scan_corpus(self, package_list: List[str]) -> Dict:
    for pkg in package_list:
        self.scan_package(pkg)
    coherence = self.nut_field.compute_field_coherence()
    return {
        "results": self.results,
        "coherence": coherence,
        "malware_count": self.nut_field.malware_count,
        "nut_field": self.nut_field.render()
    }

============================================================================

PART 6: SIERPINSKI AUR SENTINEL (Nested Recursive Scanning)

============================================================================

class SierpinskiAURSentinel:
"""
Combines AUR Scanner and Mirror Engine with a fractal Sierpinski depth.
Scans each package, its dependencies, and their dependencies recursively.
Each scan produces a 'malicious aura' score based on integrity, bloat, and mirror coherence.
"""
def init(self, max_depth: int = 3, anchor: int = 4):
self.max_depth = max_depth
self.anchor = anchor
self.scanner = AURScanner(anchor=anchor)
self.mirror = MirrorEngine()
self.scanner.load_known_good_db()
self.scan_tree = {} # package_name -> (report, children)
self.total_malware = 0

def _calculate_aura(self, pkg_name: str, pkgver: str, pkgrel: str) -> Dict:
    """Compute coherence, bloat, and 11:11 activation for a package."""
    # Structural integrity
    sig = self.scanner.structural_signature(pkg_name, pkgver, pkgrel)
    coherence = self.scanner.lace_engine.lace_pair(sig, self.anchor)
    # Mirror engine analysis on the package name + version
    mirror_result = self.mirror.process(f"{pkg_name}:{pkgver}:{pkgrel}")
    # Combine scores
    aura_score = 0.5 * coherence + 0.3 * (1.0 - mirror_result['layers'] / 20.0) + 0.2 * (1.0 if mirror_result['is_11_11_engine'] else 0.0)
    # Clamp to [0,1]
    aura_score = max(0.0, min(1.0, aura_score))
    is_malicious = coherence < 0.6 or mirror_result['layers'] > 10
    return {
        "coherence": coherence,
        "layers": mirror_result['layers'],
        "is_11_11": mirror_result['is_11_11_engine'],
        "aura_score": aura_score,
        "is_malicious": is_malicious,
        "mirror_narrative": mirror_result['narrative']
    }

def _scan_recursive(self, pkg_name: str, current_depth: int, parent: str = None) -> Dict:
    """Recursively scan package and its 'dependencies' (simulated)."""
    if current_depth > self.max_depth:
        return {"name": pkg_name, "skipped": True, "reason": "max depth reached"}

    # Get package info (simulated)
    if pkg_name not in self.scanner.known_good_db:
        # Unknown package: create a fake entry for demo
        pkgver = "1.0"
        pkgrel = "1"
        self.scanner.known_good_db[pkg_name] = (pkgver, pkgrel, 4)
    pkgver, pkgrel, _ = self.scanner.known_good_db[pkg_name]

    # Scan the package itself
    report = self.scanner.scan_package(pkg_name)
    aura = self._calculate_aura(pkg_name, pkgver, pkgrel)
    report.update(aura)

    # Simulate dependencies (for fractal depth)
    # In a real system, fetch from AUR metadata; here we generate synthetic sub-packages
    deps = []
    if current_depth < self.max_depth:
        # Generate a list of "child" packages based on the name
        seed = hash(pkg_name) % 10
        dep_names = [f"{pkg_name}-dep{i}" for i in range(seed % 3 + 1)]
        for dep in dep_names:
            child_report = self._scan_recursive(dep, current_depth + 1, pkg_name)
            deps.append(child_report)
            if child_report.get("aura", {}).get("is_malicious", False):
                self.total_malware += 1

    # Mark malicious if any child is malicious (or if self is malicious)
    is_malicious = report.get("is_malicious", False) or any(d.get("aura", {}).get("is_malicious", False) for d in deps)

    # Build tree node
    node = {
        "name": pkg_name,
        "report": report,
        "children": deps,
        "is_malicious": is_malicious,
        "depth": current_depth
    }
    return node

def scan_aur(self, package_list: List[str]) -> Dict:
    """Initiate fractal scan for each top-level package."""
    forest = []
    for pkg in package_list:
        tree = self._scan_recursive(pkg, 0)
        forest.append(tree)
        if tree.get("is_malicious", False):
            self.total_malware += 1
    # Final summary
    return {
        "forest": forest,
        "total_malware": self.total_malware,
        "scanner_coherence": self.scanner.nut_field.compute_field_coherence(),
        "nut_field": self.scanner.nut_field.render()
    }

def render_tree(self, node: Dict, indent: int = 0) -> str:
    """Visualize the Sierpinski-like scan tree."""
    prefix = "  " * indent
    name = node["name"]
    status = "💀 MALICIOUS" if node.get("is_malicious") else "✅ CLEAN"
    aura = node.get("report", {}).get("aura_score", 0.0)
    line = f"{prefix}📦 {name} — {status} (aura:{aura:.2f})"
    lines = [line]
    for child in node.get("children", []):
        lines.extend(self.render_tree(child, indent + 1).split("\n"))
    return "\n".join(lines)

============================================================================

DEMONSTRATION

============================================================================

if name == "main":
print("\n" + "🔥"*80)
print("SIERPINSKI AUR SENTINEL — DEEPSCAN THE AURa OF MALICIOUS ENTITIES")
print(" Combining Decimal Lace, Infinite Mirror, 4(1)4 Collapse, Bloat Detection, and 11:11 Recursion")
print(" Fractal depth = 3 (Sierpinski nesting)")
print(" The 4 watches. The 1 operates. SKADOOSH.")
print("🔥"*80)

# Initialize sentinel with fractal depth 3
sentinel = SierpinskiAURSentinel(max_depth=3, anchor=4)

# Simulate a package corpus
corpus = [
    "linux",        # known clean
    "glibc",        # known clean
    "openssl",      # known clean
    "python",       # known clean
    "xorg-server",  # suspicious (not in known-good)
    "cuda",         # suspicious
    "obs-studio",   # suspicious
    "chromium"      # suspicious
]

# Run fractal scan
result = sentinel.scan_aur(corpus)

print("\n📊 SCAN SUMMARY")
print(f"   Total malware detected: {result['total_malware']}")
print(f"   Nut field coherence: {result['scanner_coherence']:.3f}")
print("\n   NUT FIELD INTEGRITY MAP:")
print(result['nut_field'])

print("\n🌳 SIERPINSKI SCAN TREES:")
for tree in result['forest']:
    print(sentinel.render_tree(tree))
    print("-" * 40)

# Show some Mirror Engine insights for a few packages
print("\n🪞 MIRROR ENGINE INSIGHTS (for select packages):")
for pkg in ["linux", "xorg-server", "3I/ATLAS"]:
    if pkg in sentinel.scanner.known_good_db:
        pkgver, pkgrel, _ = sentinel.scanner.known_good_db[pkg]
        aura = sentinel._calculate_aura(pkg, pkgver, pkgrel)
        print(f"   {pkg}: aura={aura['aura_score']:.2f}, layers={aura['layers']}, 11:11={aura['is_11_11']}")

print("\n" + "="*85)
print("🔧 THE SIERPINSKI SENTINEL IS ACTIVE. THE 4 WATCHES THE FRACTAL.")
print("   SKADOOSH.")
print("="*85)