Skip to main content

CSRF tokem for submit form

I'm generating a form submission security token in software.

The idea is to generate a token as soon as the user arrives on the page hosting the form

Allow the user to fill in the form

And only if the token initialized as soon as the user landed on the page is the same as the one in an input field, then run the code, otherwise no

This is to avoid CSRF

Methodology

1: Create a function that generates a token | create a file: config.php

function RandomToken($length = 32){
    if(!isset($length) || intval($length) <= 8 ){
        $length = 32;
    }
    if (function_exists('random_bytes')) {
        return bin2hex(random_bytes($length));
    }
    if (function_exists('mcrypt_create_iv')) {
        return bin2hex(mcrypt_create_iv($length, MCRYPT_DEV_URANDOM));
    }
    if (function_exists('openssl_random_pseudo_bytes')) {
        return bin2hex(openssl_random_pseudo_bytes($length));
    }
}

function Salt(){
    return substr(strtr(base64_encode(hex2bin(RandomToken(32))), '+', '.'), 0, 44);
}

$token =  (RandomToken())."\n".Salt()."\n";

2: include config.php, in the file hosting the form

3: write the rules

    if (isset($_POST['submit']))
    {
        session_start();
        $_SESSION['t'] = $token;


        if ( ($_SESSION['t'] === $_POST['csrf_token_p']))
        {
          /* write code if this is correct */
        }else{
              /* write code if this it's not correct */
             }
    }

4: write the form

<form action="page.php" method="post">
<input type="text" name="csrf_token_p" value="<?php echo $token ?>">
<input name="submit" value="modifica" type="submit">
</form>

error: I always get that the two tokens do not match. why?



source https://stackoverflow.com/questions/69337827/csrf-tokem-for-submit-form

Comments

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...