Dahlia  Muller

Dahlia Muller

1589934960

Nuxt Auth: Why does login with call both ‘login' and ‘user' API endpoints?

One of the most common questions I’ve gotten on my Nuxt Auth video is about why the loginWith method calls both the ‘login’ and ‘user’ API endpoints.
To answer this question, we’re going to be doing a source dive into the Nuxt Auth codebase.
We’ll also talk about options for what you can do if you need to work with a suboptimal API.

#nuxt #nuxt.js #api

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Nuxt Auth: Why does login with call both ‘login' and ‘user' API endpoints?
Dahlia  Muller

Dahlia Muller

1589934960

Nuxt Auth: Why does login with call both ‘login' and ‘user' API endpoints?

One of the most common questions I’ve gotten on my Nuxt Auth video is about why the loginWith method calls both the ‘login’ and ‘user’ API endpoints.
To answer this question, we’re going to be doing a source dive into the Nuxt Auth codebase.
We’ll also talk about options for what you can do if you need to work with a suboptimal API.

#nuxt #nuxt.js #api

Top 10 API Security Threats Every API Team Should Know

As more and more data is exposed via APIs either as API-first companies or for the explosion of single page apps/JAMStack, API security can no longer be an afterthought. The hard part about APIs is that it provides direct access to large amounts of data while bypassing browser precautions. Instead of worrying about SQL injection and XSS issues, you should be concerned about the bad actor who was able to paginate through all your customer records and their data.

Typical prevention mechanisms like Captchas and browser fingerprinting won’t work since APIs by design need to handle a very large number of API accesses even by a single customer. So where do you start? The first thing is to put yourself in the shoes of a hacker and then instrument your APIs to detect and block common attacks along with unknown unknowns for zero-day exploits. Some of these are on the OWASP Security API list, but not all.

Insecure pagination and resource limits

Most APIs provide access to resources that are lists of entities such as /users or /widgets. A client such as a browser would typically filter and paginate through this list to limit the number items returned to a client like so:

First Call: GET /items?skip=0&take=10 
Second Call: GET /items?skip=10&take=10

However, if that entity has any PII or other information, then a hacker could scrape that endpoint to get a dump of all entities in your database. This could be most dangerous if those entities accidently exposed PII or other sensitive information, but could also be dangerous in providing competitors or others with adoption and usage stats for your business or provide scammers with a way to get large email lists. See how Venmo data was scraped

A naive protection mechanism would be to check the take count and throw an error if greater than 100 or 1000. The problem with this is two-fold:

  1. For data APIs, legitimate customers may need to fetch and sync a large number of records such as via cron jobs. Artificially small pagination limits can force your API to be very chatty decreasing overall throughput. Max limits are to ensure memory and scalability requirements are met (and prevent certain DDoS attacks), not to guarantee security.
  2. This offers zero protection to a hacker that writes a simple script that sleeps a random delay between repeated accesses.
skip = 0
while True:    response = requests.post('https://api.acmeinc.com/widgets?take=10&skip=' + skip),                      headers={'Authorization': 'Bearer' + ' ' + sys.argv[1]})    print("Fetched 10 items")    sleep(randint(100,1000))    skip += 10

How to secure against pagination attacks

To secure against pagination attacks, you should track how many items of a single resource are accessed within a certain time period for each user or API key rather than just at the request level. By tracking API resource access at the user level, you can block a user or API key once they hit a threshold such as “touched 1,000,000 items in a one hour period”. This is dependent on your API use case and can even be dependent on their subscription with you. Like a Captcha, this can slow down the speed that a hacker can exploit your API, like a Captcha if they have to create a new user account manually to create a new API key.

Insecure API key generation

Most APIs are protected by some sort of API key or JWT (JSON Web Token). This provides a natural way to track and protect your API as API security tools can detect abnormal API behavior and block access to an API key automatically. However, hackers will want to outsmart these mechanisms by generating and using a large pool of API keys from a large number of users just like a web hacker would use a large pool of IP addresses to circumvent DDoS protection.

How to secure against API key pools

The easiest way to secure against these types of attacks is by requiring a human to sign up for your service and generate API keys. Bot traffic can be prevented with things like Captcha and 2-Factor Authentication. Unless there is a legitimate business case, new users who sign up for your service should not have the ability to generate API keys programmatically. Instead, only trusted customers should have the ability to generate API keys programmatically. Go one step further and ensure any anomaly detection for abnormal behavior is done at the user and account level, not just for each API key.

Accidental key exposure

APIs are used in a way that increases the probability credentials are leaked:

  1. APIs are expected to be accessed over indefinite time periods, which increases the probability that a hacker obtains a valid API key that’s not expired. You save that API key in a server environment variable and forget about it. This is a drastic contrast to a user logging into an interactive website where the session expires after a short duration.
  2. The consumer of an API has direct access to the credentials such as when debugging via Postman or CURL. It only takes a single developer to accidently copy/pastes the CURL command containing the API key into a public forum like in GitHub Issues or Stack Overflow.
  3. API keys are usually bearer tokens without requiring any other identifying information. APIs cannot leverage things like one-time use tokens or 2-factor authentication.

If a key is exposed due to user error, one may think you as the API provider has any blame. However, security is all about reducing surface area and risk. Treat your customer data as if it’s your own and help them by adding guards that prevent accidental key exposure.

How to prevent accidental key exposure

The easiest way to prevent key exposure is by leveraging two tokens rather than one. A refresh token is stored as an environment variable and can only be used to generate short lived access tokens. Unlike the refresh token, these short lived tokens can access the resources, but are time limited such as in hours or days.

The customer will store the refresh token with other API keys. Then your SDK will generate access tokens on SDK init or when the last access token expires. If a CURL command gets pasted into a GitHub issue, then a hacker would need to use it within hours reducing the attack vector (unless it was the actual refresh token which is low probability)

Exposure to DDoS attacks

APIs open up entirely new business models where customers can access your API platform programmatically. However, this can make DDoS protection tricky. Most DDoS protection is designed to absorb and reject a large number of requests from bad actors during DDoS attacks but still need to let the good ones through. This requires fingerprinting the HTTP requests to check against what looks like bot traffic. This is much harder for API products as all traffic looks like bot traffic and is not coming from a browser where things like cookies are present.

Stopping DDoS attacks

The magical part about APIs is almost every access requires an API Key. If a request doesn’t have an API key, you can automatically reject it which is lightweight on your servers (Ensure authentication is short circuited very early before later middleware like request JSON parsing). So then how do you handle authenticated requests? The easiest is to leverage rate limit counters for each API key such as to handle X requests per minute and reject those above the threshold with a 429 HTTP response. There are a variety of algorithms to do this such as leaky bucket and fixed window counters.

Incorrect server security

APIs are no different than web servers when it comes to good server hygiene. Data can be leaked due to misconfigured SSL certificate or allowing non-HTTPS traffic. For modern applications, there is very little reason to accept non-HTTPS requests, but a customer could mistakenly issue a non HTTP request from their application or CURL exposing the API key. APIs do not have the protection of a browser so things like HSTS or redirect to HTTPS offer no protection.

How to ensure proper SSL

Test your SSL implementation over at Qualys SSL Test or similar tool. You should also block all non-HTTP requests which can be done within your load balancer. You should also remove any HTTP headers scrub any error messages that leak implementation details. If your API is used only by your own apps or can only be accessed server-side, then review Authoritative guide to Cross-Origin Resource Sharing for REST APIs

Incorrect caching headers

APIs provide access to dynamic data that’s scoped to each API key. Any caching implementation should have the ability to scope to an API key to prevent cross-pollution. Even if you don’t cache anything in your infrastructure, you could expose your customers to security holes. If a customer with a proxy server was using multiple API keys such as one for development and one for production, then they could see cross-pollinated data.

#api management #api security #api best practices #api providers #security analytics #api management policies #api access tokens #api access #api security risks #api access keys

Autumn  Blick

Autumn Blick

1601381326

Public ASX100 APIs: The Essential List

We’ve conducted some initial research into the public APIs of the ASX100 because we regularly have conversations about what others are doing with their APIs and what best practices look like. Being able to point to good local examples and explain what is happening in Australia is a key part of this conversation.

Method

The method used for this initial research was to obtain a list of the ASX100 (as of 18 September 2020). Then work through each company looking at the following:

  1. Whether the company had a public API: this was found by googling “[company name] API” and “[company name] API developer” and “[company name] developer portal”. Sometimes the company’s website was navigated or searched.
  2. Some data points about the API were noted, such as the URL of the portal/documentation and the method they used to publish the API (portal, documentation, web page).
  3. Observations were recorded that piqued the interest of the researchers (you will find these below).
  4. Other notes were made to support future research.
  5. You will find a summary of the data in the infographic below.

Data

With regards to how the APIs are shared:

#api #api-development #api-analytics #apis #api-integration #api-testing #api-security #api-gateway

An API-First Approach For Designing Restful APIs | Hacker Noon

I’ve been working with Restful APIs for some time now and one thing that I love to do is to talk about APIs.

So, today I will show you how to build an API using the API-First approach and Design First with OpenAPI Specification.

First thing first, if you don’t know what’s an API-First approach means, it would be nice you stop reading this and check the blog post that I wrote to the Farfetchs blog where I explain everything that you need to know to start an API using API-First.

Preparing the ground

Before you get your hands dirty, let’s prepare the ground and understand the use case that will be developed.

Tools

If you desire to reproduce the examples that will be shown here, you will need some of those items below.

  • NodeJS
  • OpenAPI Specification
  • Text Editor (I’ll use VSCode)
  • Command Line

Use Case

To keep easy to understand, let’s use the Todo List App, it is a very common concept beyond the software development community.

#api #rest-api #openai #api-first-development #api-design #apis #restful-apis #restful-api

坂本  篤司

坂本 篤司

1652450700

Pythonグローバル変数–グローバル変数の例を定義する方法

この記事では、グローバル変数の基本を学びます。

まず、Pythonで変数を宣言する方法と、「変数スコープ」という用語が実際に何を意味するかを学習します。

次に、ローカル変数とグローバル変数の違いを学び、グローバル変数の定義方法とglobalキーワードの使用方法を理解します。

Pythonの変数とは何ですか?どのように作成しますか?初心者のための紹介

変数はストレージコンテナと考えることができます。

これらは、コンピュータのメモリに保存したいデータ、情報、および値を保持するためのストレージコンテナです。その後、プログラムの存続期間中のある時点でそれらを参照したり、操作したりすることもできます。

変数にはシンボリックがあり、その名前は、その識別子として機能するストレージコンテナのラベルと考えることができます。

変数名は、その中に格納されているデータへの参照とポインターになります。したがって、データと情報の詳細を覚えておく必要はありません。そのデータと情報を保持する変数名を参照するだけで済みます。

変数に名前を付けるときは、変数が保持するデータを説明していることを確認してください。変数名は、将来の自分自身と一緒に作業する可能性のある他の開発者の両方にとって、明確で簡単に理解できる必要があります。

それでは、Pythonで実際に変数を作成する方法を見てみましょう。

Pythonで変数を宣言するときは、データ型を指定する必要はありません。

たとえば、Cプログラミング言語では、変数が保持するデータの型を明示的に指定する必要があります。

したがって、整数またはint型である年齢を格納したい場合、これはCで行う必要があることです。

#include <stdio.h>
 
int main(void)
{
  int age = 28;
  // 'int' is the data type
  // 'age' is the name 
  // 'age' is capable of holding integer values
  // positive/negative whole numbers or 0
  // '=' is the assignment operator
  // '28' is the value
}

ただし、これはPythonで上記を記述する方法です。

age = 28

#'age' is the variable name, or identifier
# '=' is the assignment operator
#'28' is the value assigned to the variable, so '28' is the value of 'age'

変数名は常に左側にあり、代入する値は代入演算子の後に右側に配置されます。

プログラムの存続期間中、変数の値を変更できることに注意してください。

my_age = 28

print(f"My age in 2022 is {my_age}.")

my_age = 29

print(f"My age in 2023 will be {my_age}.")

#output

#My age in 2022 is 28.
#My age in 2023 will be 29.

同じ変数名を保持しますが、値をからにmy_age変更するだけです。2829

Pythonの可変スコープとはどういう意味ですか?

変数スコープとは、変数が利用可能で、アクセス可能で、表示可能なPythonプログラムの部分と境界を指します。

Python変数のスコープには4つのタイプがあり、 LEGBルールとも呼ばれます。

  • 局所
  • 囲み
  • グローバル
  • ビルトイン

この記事の残りの部分では、グローバルスコープを使用した変数の作成について学習することに焦点を当て、ローカル変数スコープとグローバル変数スコープの違いを理解します。

Pythonでローカルスコープを使用して変数を作成する方法

関数の本体内で定義された変数にはローカルスコープがあります。つまり、その特定の関数内でのみアクセスできます。言い換えれば、それらはその関数に対して「ローカル」です。

ローカル変数にアクセスするには、関数を呼び出す必要があります。

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()


#output

#The best place to learn to code is with freeCodeCamp!

関数の本体の外部からローカルスコープを使用してその変数にアクセスしようとするとどうなるかを見てください。

def learn_to_code():
    #create local variable
    coding_website = "freeCodeCamp"
    print(f"The best place to learn to code is with {coding_website}!")

#try to print local variable 'coding_website' from outside the function
print(coding_website)

#output

#NameError: name 'coding_website' is not defined

NameErrorプログラムの残りの部分では「表示」されないため、aが発生します。定義された関数内でのみ「表示」されます。

Pythonでグローバルスコープを使用して変数を作成する方法

ファイルの先頭など、関数の外部で変数を定義すると、その変数はグローバルスコープを持ち、グローバル変数と呼ばれます。

グローバル変数は、プログラムのどこからでもアクセスできます。

関数の本体内で使用することも、関数の外部からアクセスすることもできます。

#create a global variable
coding_website = "freeCodeCamp"

def learn_to_code():
    #access the variable 'coding_website' inside the function
    print(f"The best place to learn to code is with {coding_website}!")

#call the function
learn_to_code()

#access the variable 'coding_website' from outside the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

グローバル変数とローカル変数があり、両方が同じ名前の場合はどうなりますか?

#global variable
city = "Athens"

def travel_plans():
    #local variable with the same name as the global variable
    city = "London"
    print(f"I want to visit {city} next year!")

#call function - this will output the value of local variable
travel_plans()

#reference global variable - this will output the value of global variable
print(f"I want to visit {city} next year!")

#output

#I want to visit London next year!
#I want to visit Athens next year!

上記の例では、その特定の出力を期待していなかった可能性があります。

city関数内で別の値を割り当てたときに、の値が変わると思ったかもしれません。

たぶん、私が行でグローバル変数を参照したときprint(f" I want to visit {city} next year!")、出力は#I want to visit London next year!の代わりになると予想しました#I want to visit Athens next year!

ただし、関数が呼び出されると、ローカル変数の値が出力されます。

次に、関数の外部でグローバル変数を参照すると、グローバル変数に割り当てられた値が出力されました。

彼らはお互いに干渉しませんでした。

ただし、グローバル変数とローカル変数に同じ変数名を使用することは、ベストプラクティスとは見なされません。プログラムを実行すると混乱する結果が生じる可能性があるため、変数の名前が同じでないことを確認してください。

Pythonでキーワードを使用する方法global

グローバル変数があり、関数内でその値を変更したい場合はどうなりますか?

私がそれをしようとすると何が起こるか見てください:

#global variable
city = "Athens"

def travel_plans():
    #First, this is like when I tried to access the global variable defined outside the function. 
    # This works fine on its own, as you saw earlier on.
    print(f"I want to visit {city} next year!")

    #However, when I then try to re-assign a different value to the global variable 'city' from inside the function,
    #after trying to print it,
    #it will throw an error
    city = "London"
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#output

#UnboundLocalError: local variable 'city' referenced before assignment

デフォルトでは、Pythonは関数内でローカル変数を使用したいと考えています。

そのため、最初に変数の値を出力してから、アクセスしようとしている変数に値再割り当てしようとすると、Pythonが混乱します。

関数内のグローバル変数の値を変更する方法は、次のglobalキーワードを使用することです。

#global variable
city = "Athens"

#print value of global variable
print(f"I want to visit {city} next year!")

def travel_plans():
    global city
    #print initial value of global variable
    print(f"I want to visit {city} next year!")
    #assign a different value to global variable from within function
    city = "London"
    #print new value
    print(f"I want to visit {city} next year!")

#call function
travel_plans()

#print value of global variable
print(f"I want to visit {city} next year!")

global次のエラーが発生するため、関数でキーワードを参照する前にキーワードを使用してくださいSyntaxError: name 'city' is used prior to global declaration

以前、関数内で作成された変数はローカルスコープを持っているため、それらにアクセスできないことを確認しました。

globalキーワードは、関数内で宣言された変数の可視性を変更します。

def learn_to_code():
   global coding_website
   coding_website = "freeCodeCamp"
   print(f"The best place to learn to code is with {coding_website}!")

#call function
learn_to_code()

#access variable from within the function
print(coding_website)

#output

#The best place to learn to code is with freeCodeCamp!
#freeCodeCamp

結論

そして、あなたはそれを持っています!これで、Pythonのグローバル変数の基本を理解し、ローカル変数とグローバル変数の違いを理解できます。

この記事がお役に立てば幸いです。

基本から始めて、インタラクティブで初心者に優しい方法で学びます。また、最後に5つのプロジェクトを構築して実践し、学んだことを強化するのに役立てます。

読んでくれてありがとう、そして幸せなコーディング!

ソース:https ://www.freecodecamp.org/news/python-global-variables-examples/

#python