Joseki.jl: Suggested Opening Moves for Building APIs in Julia

Joseki.jl

Want to make an API in Julia but not sure where to start? Newer versions of HTTP.jl have everything you need to build one from scratch, but getting started can be a bit intimidating at the moment. Joseki.jl is a set of examples and tools to help you on your way. It's inspired by Mux.jl and Express.

Add it to your project with ] add Joseki from the REPL, or using Pkg; Pkg.add("Joseki").

The basics

Middleware in Joseki is any function that takes a HTTP.Request and modifies it (and the associated response). Endpoints are functions that accept a HTTP.Request and returns a modified version of its associated HTTP.Response. Typically any request is passed through the same set of middleware layers before being routed to a single endpoint.

You combine a set of middleware, endpoints, and optionally an error-handling function with Joseki.router(endpoints; middleware=default_middleware error_fn=error_responder) to create a HTTP.Router. This can be used with standard HTTP.jl methods to create a server.

A simple example

using Joseki, JSON, HTTP

### Create some endpoints

# This function takes two numbers x and y from the query string and returns x^y
# In this case they need to be identified by name and it should be called with
# something like 'http://localhost:8000/pow/?x=2&y=3'
function pow(req::HTTP.Request)
    j = HTTP.queryparams(HTTP.URI(req.target))
    has_all_required_keys(["x", "y"], j) || return error_responder(req, "You need to specify values for x and y!")
    # Try to parse the values as numbers.  If there's an error here the generic
    # error handler will deal with it.
    x = parse(Float32, j["x"])
    y = parse(Float32, j["y"])
    json_responder(req, x^y)
end

# This function takes two numbers n and k from a JSON-encoded request
# body and returns binomial(n, k)
function bin(req::HTTP.Request)
    j = try
        body_as_dict(req)
    catch err
        return error_responder(req, "I was expecting a json request body!")
    end
    has_all_required_keys(["n", "k"], j) || return error_responder(req, "You need to specify values for n and k!")
    json_responder(req, binomial(j["n"],j["k"]))
end

### Create and run the server

# Make a router and add routes for our endpoints.
endpoints = [
    (pow, "GET", "/pow"),
    (bin, "POST", "/bin")
]
r = Joseki.router(endpoints)

# Fire up the server
HTTP.serve(r, "127.0.0.1", 8000; verbose=false)

If you run this example you can try it out by going to http://localhost:8000/pow/?x=2&y=3. You should see a response like:

{"error": false, "result": 8.0}

In order to test the 2nd endpoint, you can make a POST request from within a different Julia session:

using HTTP, JSON
HTTP.post("http://localhost/bin", [], JSON.json(Dict("n" => 4, "k" => 3)))

You can also do this from the command line with cURL:

curl -X POST \
  http://localhost:8000/bin \
  -H 'Cache-Control: no-cache' \
  -H 'Content-Type: application/json' \
  -d '{"n": 4, "k": 3}'

or use a tool like Postman.

Next steps

You can modify or add to the default middleware stack, write your own responders, or create additional endpoints.

Containers and deploying

In many cases you will want to deploy your API as a Docker container. This makes it possible to deploy to most hosting services. This folder contains a Dockerfile that demonstrates hosting the example above (with a few minor modifications to make it work in Docker).

To build the image you can run

docker build -t joseki .

from this folder and then run

docker run --rm -p 8000:8000 joseki

to start the server. If you need to debug anything you can start an interactive session with

docker run --rm -p 8000:8000 -it --entrypoint=/bin/bash joseki

This runs Joseki from within its own package environment, but a more common use case would be to create a new project that adds Joseki as a dependency. You can find examples that do this in separate repositories within the Joseki org.

Author: Joseki-jl
Source Code: https://github.com/Joseki-jl/Joseki.jl 
License: View license

#julia #api 

What is GEEK

Buddha Community

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

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:

• Documentation is where just the Swagger/OpenAPI docs are hosted somewhere. e.g. https://api.linkgroup.com/member/docs/index
• Portal is where an interactive portal has been developed. e.g. https://dev.telstra.com/
• The web page is where the company has a single page that isn’t interactive explaining their Public APIs. e.g. https://www.bendigoadelaide.com.au/banking-products-api.asp

#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

Joseki.jl: Suggested Opening Moves for Building APIs in Julia

Joseki.jl

Want to make an API in Julia but not sure where to start? Newer versions of HTTP.jl have everything you need to build one from scratch, but getting started can be a bit intimidating at the moment. Joseki.jl is a set of examples and tools to help you on your way. It's inspired by Mux.jl and Express.

Add it to your project with ] add Joseki from the REPL, or using Pkg; Pkg.add("Joseki").

The basics

Middleware in Joseki is any function that takes a HTTP.Request and modifies it (and the associated response). Endpoints are functions that accept a HTTP.Request and returns a modified version of its associated HTTP.Response. Typically any request is passed through the same set of middleware layers before being routed to a single endpoint.

You combine a set of middleware, endpoints, and optionally an error-handling function with Joseki.router(endpoints; middleware=default_middleware error_fn=error_responder) to create a HTTP.Router. This can be used with standard HTTP.jl methods to create a server.

A simple example

using Joseki, JSON, HTTP

### Create some endpoints

# This function takes two numbers x and y from the query string and returns x^y
# In this case they need to be identified by name and it should be called with
# something like 'http://localhost:8000/pow/?x=2&y=3'
function pow(req::HTTP.Request)
    j = HTTP.queryparams(HTTP.URI(req.target))
    has_all_required_keys(["x", "y"], j) || return error_responder(req, "You need to specify values for x and y!")
    # Try to parse the values as numbers.  If there's an error here the generic
    # error handler will deal with it.
    x = parse(Float32, j["x"])
    y = parse(Float32, j["y"])
    json_responder(req, x^y)
end

# This function takes two numbers n and k from a JSON-encoded request
# body and returns binomial(n, k)
function bin(req::HTTP.Request)
    j = try
        body_as_dict(req)
    catch err
        return error_responder(req, "I was expecting a json request body!")
    end
    has_all_required_keys(["n", "k"], j) || return error_responder(req, "You need to specify values for n and k!")
    json_responder(req, binomial(j["n"],j["k"]))
end

### Create and run the server

# Make a router and add routes for our endpoints.
endpoints = [
    (pow, "GET", "/pow"),
    (bin, "POST", "/bin")
]
r = Joseki.router(endpoints)

# Fire up the server
HTTP.serve(r, "127.0.0.1", 8000; verbose=false)

If you run this example you can try it out by going to http://localhost:8000/pow/?x=2&y=3. You should see a response like:

{"error": false, "result": 8.0}

In order to test the 2nd endpoint, you can make a POST request from within a different Julia session:

using HTTP, JSON
HTTP.post("http://localhost/bin", [], JSON.json(Dict("n" => 4, "k" => 3)))

You can also do this from the command line with cURL:

curl -X POST \
  http://localhost:8000/bin \
  -H 'Cache-Control: no-cache' \
  -H 'Content-Type: application/json' \
  -d '{"n": 4, "k": 3}'

or use a tool like Postman.

Next steps

You can modify or add to the default middleware stack, write your own responders, or create additional endpoints.

Containers and deploying

In many cases you will want to deploy your API as a Docker container. This makes it possible to deploy to most hosting services. This folder contains a Dockerfile that demonstrates hosting the example above (with a few minor modifications to make it work in Docker).

To build the image you can run

docker build -t joseki .

from this folder and then run

docker run --rm -p 8000:8000 joseki

to start the server. If you need to debug anything you can start an interactive session with

docker run --rm -p 8000:8000 -it --entrypoint=/bin/bash joseki

This runs Joseki from within its own package environment, but a more common use case would be to create a new project that adds Joseki as a dependency. You can find examples that do this in separate repositories within the Joseki org.

Author: Joseki-jl
Source Code: https://github.com/Joseki-jl/Joseki.jl 
License: View license

#julia #api 

What Are Good Traits That Make Great API Product Managers

As more companies realize the benefits of an API-first mindset and treating their APIs as products, there is a growing need for good API product management practices to make a company’s API strategy a reality. However, API product management is a relatively new field with little established knowledge on what is API product management and what a PM should be doing to ensure their API platform is successful.

Many of the current practices of API product management have carried over from other products and platforms like web and mobile, but API products have their own unique set of challenges due to the way they are marketed and used by customers. While it would be rare for a consumer mobile app to have detailed developer docs and a developer relations team, you’ll find these items common among API product-focused companies. A second unique challenge is that APIs are very developer-centric and many times API PMs are engineers themselves. Yet, this can cause an API or developer program to lose empathy for what their customers actually want if good processes are not in place. Just because you’re an engineer, don’t assume your customers will want the same features and use cases that you want.

This guide lays out what is API product management and some of the things you should be doing to be a good product manager.

#api #analytics #apis #product management #api best practices #api platform #api adoption #product managers #api product #api metrics