superfish.pem contains:
- the Superfish certificate as found by both Chris Palmer and Matt Burke;
- the encrypted private key as found by Karl Koscher.
$ openssl x509 -in superfish.pem -text
Certificate:
Data:
Version: 3 (0x2)| #Newbie programmer | |
| def factorial(x): | |
| if x == 0: | |
| return 1 | |
| else: | |
| return x * factorial(x - 1) | |
| print factorial(6) | |
| #First year programmer, studied Pascal |
| #include <stdio.h> | |
| #include <math.h> | |
| double lim(double (*f)(double), double p) | |
| { | |
| double a(int n) | |
| { | |
| if (isinf(p)) { | |
| return pow(2, n); | |
| } |
| #!/usr/bin/env python | |
| import base64, hashlib, hmac, json, sys, getpass | |
| from Crypto.Cipher import AES | |
| from Crypto.Hash import RIPEMD, SHA256 | |
| base58_chars = '123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz' | |
| def prompt(p): | |
| return getpass.getpass(p + ": ") |
| #!/usr/bin/python | |
| ################################################################################# | |
| # # | |
| #.______ _______. ______ ___ .__ __. # | |
| #| _ \ / | / | / \ | \ | | # | |
| #| |_) | ______ | (----`| ,----' / ^ \ | \| | # | |
| #| / |______| \ \ | | / /_\ \ | . ` | # | |
| #| |\ \----. .----) | | `----./ _____ \ | |\ | # | |
| #| _| `._____| |_______/ \______/__/ \__\ |__| \__| v0.2.0 # |
| import datetime | |
| import hashlib | |
| import hmac | |
| import random | |
| import string | |
| import time | |
| import unirest as unirest | |
| key = "da01c7e1f0dc4f166c6aa3d56add3293" | |
| secret = "XXXXXXXXXXXXXXXXXXXXXXXXXX" |
superfish.pem contains:
$ openssl x509 -in superfish.pem -text
Certificate:
Data:
Version: 3 (0x2)| #!/usr/bin/env python | |
| """A simple Bloom Filter implementation | |
| Calculating optimal filter size: | |
| Where: | |
| m is: self.bitcount (how many bits in self.filter) | |
| n is: the number of expected values added to self.filter | |
| k is: the number of hashes being produced | |
| (1 - math.exp(-float(k * n) / m)) ** k | |
| http://en.wikipedia.org/wiki/Bloom_filter | |
| """ |
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
| # Copyright 2014 Chris Cohen | |
| # | |
| # This program is free software: you can redistribute it and/or modify | |
| # it under the terms of the GNU General Public License as published by | |
| # the Free Software Foundation, either version 3 of the License, or | |
| # (at your option) any later version. | |
| # | |
| # This program is distributed in the hope that it will be useful, | |
| # but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| import socket | |
| from struct import * | |
| s = socket.socket(socket.AF_INET, socket.SOCK_RAW, socket.IPPROTO_TCP) | |
| while True: | |
| pack = s.recvfrom(20000) | |
| #Get the single element from the tuple |