Enumerating Lambda functions for Pentesting

Lambda functions can be directly pentested as discussed in the last post. We would like to take it to the next level by illustrating the methodology to automate  pentesting. It is interesting to leverage scripting to automate reviewing Lambda functions from security standpoint. We can use SDK and libraries available in various languages. In this post, we are using python with boto3. More detail and documentation can be found at (https://boto3.readthedocs.io/en/latest/reference/services/lambda.html).

Let’s use a simple sample and run against our target deployment. Before running these scripts, one needs to setup AWS configuration as discussed in the last post. We can run script and use “list_functions” to fetch all functions deployed on the target environment. Here is the list of functions, which are fetched from deployment.

tools $python3 listfunction.py
(+) Lambda functions ...
   (-)pyhello
   (-)login
   (-)hello
   (-)myService-dev-helloworld
   (-)delete
   (-)getuserinfo
   


Here is the code snippet for the function used.

def getFunctions():
    raw_functions = client.list_functions()
    all_functions = raw_functions["Functions"]
    #print(json.dumps(all_functions,indent=1))
    list_of_functions = []
    for i in all_functions:
        list_of_functions.append(i["FunctionName"])
    return list_of_functions


This can be entry point for pentesting. You can uncomment the line where we are using json.dumps. It will give you entire stream for evaluation. Now, we can take each function and start enumerating as shown below. We can start evaluating important parameters and its impact on security.

tools $python3 getFunctionInfo.py login
(+) Fetching Lambda function login...
       (+) Platform: nodejs6.10
       (+) Permission: arn:aws:iam::313588302550:role/service-role/access
       (+) Code-Location: https://awslambda-us-east-2-tasks.s3.us-east-2.amazonaws.com/snapshots/313588302550/login-a1488a4f-………69c59232e73703


In above case, we can fetch important information like platform, permission and code-location to fetch source. We can use “get_function” to fetch detail about function. Here is the code snippet -

target_function = sys.argv[1]
print("(+) Fetching Lambda function "+target_function+"...")
myfunc = client.get_function(FunctionName=target_function)
#print(json.dumps(myfunc,indent=1))
temp = myfunc["Configuration"]
print ("       (+) Platform: "+temp["Runtime"])
print ("       (+) Permission: "+temp["Role"])
temp_code = myfunc["Code"]
print ("       (+) Code-Location: "+temp_code["Location"]+"\n")


In case, if you are interested in seeing the entire object, just use json.dump() and print the object as line commented in both of the above cases.

We can enumerate other mapping information as well, here is the way we can leverage “list_event_source_mappings”.

tools $python3 listmap.py
[{'UUID': '682c8cb8-cb32-4cdc-b059-8f655f71fe07', 'BatchSize': 100, 'EventSourceArn': 'arn:aws:dynamodb:us-east-1:223983707454:table/targetlocations/stream/2018-05-30T09:41:22.995', 'FunctionArn': 'arn:aws:lambda:us-east-1:223983707454:function: targetlocations', 'LastModified': datetime.datetime(2018, 7, 4, 8, 10, tzinfo=tzlocal()), 'LastProcessingResult': 'OK', 'State': 'Enabled', 'StateTransitionReason': 'User action'}]

Here is the code for the same.

myfunc = client.list_event_source_mappings(FunctionName='targetlocations')
temp = myfunc["EventSourceMappings"]
print(temp)

It seems function is using “dynamodb” from ARN.

In next posts, we will go over  invoke and tracing the functions.  

Article by Amish Shah & Shreeraj Shah

Fuzzing Serverless Lambda functions directly

Serverless application (FaaS - Function as a Service) development and use of microservices model are emerging in next generation applications and architecture. It is becoming easier to maintain and cost effective in the days of DevOps era. It is imperative to do a quick testing of these functions from security standpoint and look for common vulnerabilities like injections. Amazon provides Lambda functions for serverless architecture whereas Google and Azure also implemented these types of support and having FaaS in their own portfolio. As shown in the below figure, lambda function is created and deployed on amazon and can be triggered by set of events like HTTP gateway, S3 bucket and number of other events. At the end, the functions are being “invoked” and executed by the end client (Browser, mobile or API users). The challenge from security standpoint is to fuzz these inputs going to functions and identifies any defect in the code via error or behavioural observations (purely DAST approach).


Figure 1 - Lambda invoke and integration

To address the issue of fuzzing, we can leverage AWS client (command-line) directly and interact with functions without going through the actual events as shown in the above diagram. It is possible to test these functions if developer provides right environment along with credentials to the pentester. We can set up AWS client and run some quick tests to discover vulnerabilities and weakness.

One needs to setup AWS client and you can find guideline over here - https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html

First, one needs to setup the access for the environment by given keys from developers as shown below. It is quick process and needs basic detail.

$ aws configure
AWS Access Key ID [None]: …
AWS Secret Access Key [None]: …
Default region name [None]: …
Default output format [None]: …


Once it is set, we can go ahead and enumerate the functions deployed on the server as below by using “list-function” option. It helps in enumerating all functions deployed with some basic information including permissions.



As shown above, we get list of all the functions. Next, we can enumerate the functions in more detail. For example, getting configuration and actual location (code) as shown below.



One can get location of the code by following call, “Location” attribute give the code for review if required.



Now, we can get into the most critical part of the testing. We can invoke the function and start interacting with it as shown below over AWS APIs without actual event. Event can be coming from any source but we are keeping focus on directly testing the function.



In above case, we invoked “login” function with “payload”. We directed out to the file and can see the results.

Now, we can just go ahead and start manipulating “payload” with all different values from DAST/Blackbox standpoint. We can fuzz the payload and start injecting values to discover vulnerabilities within lambda functions.

In a nutshell, it is easy to fuzz lambda functions and test them thoroughly. It is possible to add them into DevOps pipe. AWS client can be used with different languages as well to automate the process. For example following code with python and boto3 client helps in automate fuzzing.

 

Here, we are passing ‘john OR 1=1’ as payload to invoke the function. We are getting following response.

 

We get “Error in fetching value from table” as status message. It implies something to do with SQL injection. Again, we need to dive deep and find exact payload. We can automate the script and start fuzzing the lambda functions.

Article by Amish Shah & Shreeraj Shah

JSON Parameter Pollution

HTTP parameter pollution attack is known to the industry for quite some time now. In HTTP parameter pollution attack, an attacker plays with order of HTTP parameters going to web/application server as part of querystring and/or POST parameter. Attacker tries to confuse HTTP parsers and leverages vulnerable code. Further details on HTTP parameter pollution (HPP) can be found at OWASP - https://www.owasp.org/index.php/Testing_for_HTTP_Parameter_pollution_(OTG-INPVAL-004)

HTTP parameter pollution vector can be extended to JSON streams as well. If application is consuming JSON stream and parsing based on their order then it is possible to manipulate order and reach to the vulnerable code. Let’s take this simple example.

Figure 1 - Possible Scenario of JSON Parameter Pollution

Here is the original HTTP request/response for the target application,

HTTP Request

POST /starter/login HTTP/1.1
Host: target
Connection: close
Content-Length: 57
Origin: chrome://newtab
User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.87 Safari/537.36
content-type: application/json
Accept: */*
Accept-Encoding: gzip, deflate
Accept-Language: en-US,en;q=0.9

{"login":"john","password":"letmein"}


HTTP Response

HTTP/1.1 200 OK
Date: Tue, 03 Jul 2018 06:04:11 GMT
Content-Type: application/json
Content-Length: 20
Connection: close
Access-Control-Allow-Origin: *

{"status":"success"}


As you can see over here, we have passed right credentials and got “success”.

Let’s try wrong credentials and see what response we get,

HTTP Request

POST /starter/login HTTP/1.1
Host: target
Connection: close
Content-Length: 57
Origin: chrome://newtab
User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.87 Safari/537.36
content-type: application/json
Accept: */*
Accept-Encoding: gzip, deflate
Accept-Language: en-US,en;q=0.9

{"login":"john","password":"junk"}


HTTP Response

HTTP/1.1 200 OK
Date: Tue, 03 Jul 2018 06:04:11 GMT
Content-Type: application/json
Content-Length: 20
Connection: close
Access-Control-Allow-Origin: *

{"status":"failure"}


So clearly we get “failure” over here. Now we can go ahead and add one more parameter to JSON stream like below and analyze the response.

HTTP Request

POST /starter/login HTTP/1.1
Host: target
Connection: close
Content-Length: 57
Origin: chrome://newtab
User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.87 Safari/537.36
content-type: application/json
Accept: */*
Accept-Encoding: gzip, deflate
Accept-Language: en-US,en;q=0.9

{"login":"john","password":"junk",”password”:”letmein”}


HTTP Response

HTTP/1.1 200 OK
Date: Tue, 03 Jul 2018 06:04:11 GMT
Content-Type: application/json
Content-Length: 20
Connection: close
Access-Control-Allow-Origin: *

{"status":"success"}


Hence, as we passed JSON stream like this - {"login":"john","password":"junk",”password”:”letmein”} and end up getting “success”.

JSON parameter pollution conclusion:

In this case or many other cases, it is possible that underlying code is taking last parameter for JSON processing. It depends on library to library, how they are processing the streams. Hence, an attacker can send two parameters and possibly WAF would process first value and library would take second value. It leads to WAF value bypass. Attacker can pass real attack payload in the second parameter and genuine value in the first parameter so that WAF will allow the request and attacker can successfully execute injection on the application through JSON streams. Also, nowadays, applications are running in multi layers where logic is spread across multiple layers and each layer processes JSON data with their own JSON library. Hence, it is quite possible that one library considers first parameter value and second library considers second parameter value. In this situation, attacker can supply different values in both parameters and bypass application business logic validation through invalid values. 

Securing APIs – Defence Controls for Developers

APIs have emerged as a solid backbone of applications in this modern world of mashups where applications are using one back-end with multiple front-ends. REST based APIs running over HTTP with JSON or XML are becoming preferred choices for developers. However, API end points are also becoming points of attack for attackers. Hence, developers need to implement proper security controls across APIs during design and development. Here are some important security controls for APIs :

Authentication control – APIs should have proper authentication control in place. APIs mostly run with access tokens/keys. OAuth is a popular building mechanism for tokens or keys. One should make sure that the tokens get validated with every API call/request. If session based authentication is defined, session management along with proper validation must be in place.

Authorization control
– APIs should be well guarded by a proper authorization layer on two fronts – token layer and HTTP method access. REST APIs use HTTP methods like GET for read, POST for create an entry, PUT for update and DELETE for remove. Hence, it is imperative to implement double locking with authorization both at the token layer and at the method layer. Also, in certain cases, resource locking is required at path level as well (example: /admin/ or /globalconfig/).

Injection Controls – API parameters need to be validated before consuming into business logic. All these parameters come over HTTP and can be easily tampered with. Hence, all traditional attacks like SQLi, XSS, CMDinjections etc. are possible on each of these parameters. One needs to have strong controls for injections and at the validation layer across API calls.

CSRF Control
– CSRF is a highly likely attack vector with session cookies in play. Hence, methods like PUT, DELETE or POST need to be validated with tokens to avoid CSRF attacks. Also, CORS can be used to strengthen the defence against CSRF attack vectors using preflight check with a set of rules.

Client Side Controls – Browsers are powerful points of abuse for attackers. Hence, critical vectors like XSS or ClickJacking can abuse APIs. It is important to apply appropriate types of HTTP headers like “nosniff” on X-Content, X-Frame options, Content-Type etc. to protect against these vectors. Also, it is critical to apply JSON and XML encoding as appropriate for the API context. Since DOM based XSS are also on the rise, using secure methods in the browser after consuming APIs is also a must (avoid .innerHTML call and use other pure text calls).

Third-Party-Integration Controls – At times, APIs are using various third-party components and it is imperative to use right coding practices before consuming them. Many applications leverage third party APIs for authentication purpose but fail to make calls to third party APIs when the user logs out of the application, keeping the session alive and exposed for a long duration.  Further, before serializing and de-serializing objects, it is important to make sure that the used libraries are secure and do not have intrinsic vulnerabilities like command injection or similar. Also, many times parsers introduce weaknesses into API calls. Hence, strong overall vetting and controls are required when using third-party components in the code base.

Information Leakage Controls
– HTTP status codes are important for context analysis of APIs. In many cases, these codes help in enumerating information. APIs should not spit out exceptions causing internal implementation or other sensitive information leakage. Hence, proper security controls around exception handling are a must for information leakage protection.

DoS Controls – REST APIs are easy to DoS by overloading with multiple requests in a short span of time. It is a good practice to keep “Rate Limit” on the basis of keys or users in many cases. Also, publicly open calls can be controlled by IP or on session basis to provide robust defence against API layer DoS.

Crypto & Sensitive Data Controls – Obviously, it is important to have SSL/TLS controls (HTTPS) in place for API communication over Internet. Apart from that, one should avoid having sensitive data in the API URL itself. This data can be harvested and misused from time to time at intermediate levels depending on the implementation. Data stored should be kept securely and must also have crypto applied to sensitive fields. If the API is using third party protocols or controls, then their implementation should be verified as well. (Example – JWT integrity).

Auditing Controls – APIs need strong audit and logging controls from security standpoint. API methods and its usage should be logged for various details like authentications, authorizations and injections. If any attempt of bypass or injection is happening across APIs, it should not only be logged but also flagged from time to time for protection of the APIs. One should analyse logs and extract security related incidents from them for improving defences.

Conclusion

Guarding and protecting APIs is becoming very critical for enterprises. We have seen many recent breaches where APIs are being leveraged to enter into corporate networks. API controls are different from regular web applications and need to be addressed at the design and development levels themselves. Controls covered in this article should help as a guideline for developers.

Article by Hemil Shah

Server Side Request Forgery (SSRF) Attack and Defence

Server Side Request Forgery (SSRF) is an interesting vulnerability, which can have potential impact on internal infrastructure residing behind firewall. In this case, HTTP server running over ports like 80/443 becomes an entry point for an attacker to enter into internal network over as legitimate HTTP/HTTPS tunnel.

To understand this vulnerability in detail, let’s assume we have a vulnerable application running on a hypothetical domain www.victim-example.com having a resource named “profile.php”. It is having a parameter named “propic” and it seems to be fetching picture from a resources as below.

GET /profile.php?propic=http://www.someserver.com/mypicture.png&id=9826739HTTP/1.1
Host: www.victim-example.com


Now, looking at the parameter propic, it is taking URL and fetching file from third party server. What if we can tamper with it and try to fetch something else instead? To try it out, we make a following request.


GET /profile.php?propic=http://www.myblueserver.com/foobar.html HTTP/1.1
Host: www.victim-example.com


This example server www.myblueserver.com belongs to us so we can see the logs of it. We can see this entry in it.

<IP of www.victim-example.com> - - [14/Dec/2017:00:06:28 -0700] "GET /foobar.html HTTP/1.1" 404 113 "-" "<Client type>"


Hence, clearly we got out-of-band call from the application. Application is processing propic (URL)parameter and making call to external app or resources. Application page may have lines like below.

$getpicurl = $_GET['propic'];
$profilepic = fopen($getpicurl, 'rb');


Now, this opens up various exploitation opportunities for an attacker. One of them is shown in figure below.



An attacker can start scanning internal hosts and network with reverse HTTP calls like below -
 
GET /profile.php?propic=http://192.168.100.X HTTP/1.1
Host: www.victim-example.com


It may get access to internal files and resources. This type of vulnerability is known as SSRF. It is like abusing HTTP calls with request forgery.

Exploit scenarios:


This functionality can be abused and following types of exploitation can be done.

•    Internal resource scanning and stealing.
•    Using file:// schema to access sensitive resources/files like /etc/passwd or other resources from the same server.
•    One can use other schemas like "ftp://", “dict://” or "gopher://" to abuse vulnerability further.
•    Attacking some other ports as well with cross protocol requests if possible and given scenario.

Conclusion:

SSRF is relatively easy to detect by DAST specially using manual pentesting. One can fuzz requests and look for 200 OK coming from the same server with content coming from different server (internal/external). It may require out-of-band testing setup in some cases if there is a blind SSRF. If vulnerability is identified then it brings major threat to internal resources and should be fixed immediately by proper validations, whitelisting and other secure coding practices.

XXE Attack – A4 of OWASP Top 10

XML External Entities (XXE) issue is added to newly listed OWASP Top 10 vulnerabilities list. In current world, number of applications is using XML streams or Web Services (SOAP) for back-end processing. Hence, browser or client can make this simple XML call over HTTP POST and fetch XML response from the server as shown in the figure -



Once XML stream hits to the application server, it needs to process through XML parser. This opens up an opportunity for attacker to inject malicious payload. XML processing or parser may be weakly designed (DTD or XSD parsing) or not properly configured; it allows external entity attributes to get processed. This can lead to access to file system, network drives, network resources or other OS level access.

As shown in the above diagram, one can craft following XML document where XXE is defined to read “/etc/passwd”.

<?xml version="1.0" encoding="ISO-8859-1"?>
<!DOCTYPE test [
<!ELEMENT test ANY >
<!ENTITY xxe SYSTEM "file:///etc/passwd" >]>
<test>&xxe;</test>


Hence, if an attacker can successfully execute the above payload then application end up serving /etc/passwd as HTTP response (XML stream). It is also possible to inject internal URL or causing DoS (/dev/random file call). In certain cases, parser breaks with error while sending data back into XML stream. One can overcome that by (i) an attacker can call content by using “CDATA” wrapper in case getting error from the parser while displaying content. (ii) by sending data to external system (out-of-band) injection.

Conclusion:

Though XXE is not very common issue but the nature of vulnerability is very serious and can have devastating impact on the target application/infrastructure. By leveraging this issue, an attacker can launch SSRF, steal file/source-code/confidential-information from the system or DoS the system. Hence, it is imperative to provide mitigation by proper patching, verifying XML streams and validations.

Insecure Deserialization Attacks – OWASP A8 2017

HTML5 and Web 2.0 applications are using modern architecture and modelling for web programming. It has opened up relatively different ways of attacking and exploiting. One of the issues, which are easy to detect and exploit by manual analysis, is called insecure deserialization. This is not new attack category but OWASP Top 10 came up with this vulnerability into their current list and started to get noticed.

Web programming language uses objects extensively and at some point in time, it is required to store these objects or transfer them over network. Hence, simple mechanism is developed; it is called serialization and deserialization.

Serialization – Converting an object instance into simpler form like XML, JSON, text or binary.
Deserialization – Converting XML, JSON, text or binary back into Object for consumption.

In web applications, these converted streams go back and forth between browser and servers. It goes over HTTP(S) and can be dissected at client end. It opens up opportunities for attacker to understand and tamper these object streams to exploit programming weaknesses. Here is a quick look at possible attacks and exploit scenarios.

1. Command Injections
- Object streams get handled at two layers – framework and programming (developers). At framework layer, in some cases, it gets parsed by using underlying operating systems resources to make some modifications. This opens up an opportunity to inject OS commands.

2. Privilege escalation
- Object stream may contain tokens or reference about ACLs (Access Control List). In some cases, an attacker can decode the information and manipulate it to gain higher level of access.

3. Reverse engineering
- In modern day applications, developers are using these objects on the fly and in some cases, they store very sensitive information. Data contained in these objects become a rich source of information for reverse engineering. By dissecting and decoding these objects, one can build a set of possible attack vectors. Hence, these streams coming to browser opens up bundle of opportunities for reverse engineering.

4. Authorization bypass -
Objects coming to the browser ends are having some tokens to access information time to time. These tokens can be guessed, reverse engineered or tampered, it can be sent back to server with mutation. It certainly opens up opportunities for authorization bypass and access to other user’s information.

5. Object stealing from browser space
- Objects are serialized and get stored in browser memory space. Libraries and developers are using HTML5 features like localStorage and file APIs to store these objects. If application is having XSS or DOM Injections then it can lead to information extraction from the browser. Also, developers build object maps via JavaScript within browser, one can enumerate entire object map and extract information from it via XSS. Hence, it is imperative not to have XSS across application to avoid this type of exploitation.

Conclusion

In this article, we have a brief overview of this attack vector (A8), which is newly added to OWASP. Top 10. There is more research going on in the area and we may end up seeing innovative way of both detecting and exploiting this mechanism. You can read more about it over here.

OWASP top 10 (A8) - https://www.owasp.org/images/7/72/OWASP_Top_10-2017_%28en%29.pdf.pdf

Untrusted streams - https://www.owasp.org/index.php/Deserialization_of_untrusted_data

Cheatsheet - https://www.owasp.org/index.php/Deserialization_Cheat_Sheet