Secure Coding Guidelines

This document contains descriptions and guidelines for addressing security vulnerabilities commonly identified in the GitLab codebase. They are intended to help developers identify potential security vulnerabilities early, with the goal of reducing the number of vulnerabilities released over time.


If you would like to contribute to one of the existing documents, or add guidelines for a new vulnerability type, please open an MR! Please try to include links to examples of the vulnerability found, and link to any resources used in defined mitigations. If you have questions or when ready for a review, please ping gitlab-com/gl-security/appsec.



Application permissions are used to determine who can access what and what actions they can perform. For more information about the permission model at GitLab, please see the GitLab permissions guide or the EE docs on permissions.


Improper permission handling can have significant impacts on the security of an application. Some situations may reveal sensitive data or allow a malicious actor to perform harmful actions. The overall impact depends heavily on what resources can be accessed or modified improperly.

A common vulnerability when permission checks are missing is called IDOR for Insecure Direct Object References.

When to Consider

Each time you implement a new feature/endpoint, whether it is at UI, API or GraphQL level.


Start by writing tests around permissions: unit and feature specs should both include tests based around permissions

  • Fine-grained, nitty-gritty specs for permissions are good: it is ok to be verbose here
    • Make assertions based on the actors and objects involved: can a user or group or XYZ perform this action on this object?
    • Consider defining them upfront with stakeholders, particularly for the edge cases
  • Do not forget abuse cases: write specs that make sure certain things can't happen
    • A lot of specs are making sure things do happen and coverage percentage doesn't take into account permissions as same piece of code is used.
    • Make assertions that certain actors cannot perform actions
  • Naming convention to ease auditability: to be defined, for example, a subfolder containing those specific permission tests or a #permissions block

Be careful to also test visibility levels and not only project access rights.

Some example of well implemented access controls and tests:

  1. example1
  2. example2
  3. example3

NB: any input from development team is welcome, for example, about Rubocop rules.

Regular Expressions guidelines

Anchors / Multi line

Unlike other programming languages (for example, Perl or Python) Regular Expressions are matching multi-line by default in Ruby. Consider the following example in Python:

import re
text = "foo\nbar"
matches = re.findall("^bar$",text)

The Python example will output an empty array ([]) as the matcher considers the whole string foo\nbar including the newline (\n). In contrast Ruby's Regular Expression engine acts differently:

text = "foo\nbar"
p text.match /^bar$/

The output of this example is #<MatchData "bar">, as Ruby treats the input text line by line. In order to match the whole string the Regex anchors \A and \z should be used.


This Ruby Regex specialty can have security impact, as often regular expressions are used for validations or to impose restrictions on user-input.


GitLab-specific examples can be found in the following path traversal and open redirect issues.

Another example would be this fictional Ruby on Rails controller:

class PingController < ApplicationController
  def ping
    if params[:ip] =~ /^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$/
      render :text => `ping -c 4 #{params[:ip]}`
      render :text => "Invalid IP"

Here params[:ip] should not contain anything else but numbers and dots. However this restriction can be easily bypassed as the Regex anchors ^ and $ are being used. Ultimately this leads to a shell command injection in ping -c 4 #{params[:ip]} by using newlines in params[:ip].


In most cases the anchors \A for beginning of text and \z for end of text should be used instead of ^ and $.

Denial of Service (ReDoS) / Catastrophic Backtracking

When a regular expression (regex) is used to search for a string and can't find a match, it may then backtrack to try other possibilities.

For example when the regex .*!$ matches the string hello!, the .* first matches the entire string but then the ! from the regex is unable to match because the character has already been used. In that case, the Ruby regex engine backtracks one character to allow the ! to match.

ReDoS is an attack in which the attacker knows or controls the regular expression used. The attacker may be able to enter user input that triggers this backtracking behavior in a way that increases execution time by several orders of magnitude.


The resource, for example Puma, or Sidekiq, can be made to hang as it takes a long time to evaluate the bad regex match. The evaluation time may require manual termination of the resource.


Here are some GitLab-specific examples.

User inputs used to create regular expressions:

Hardcoded regular expressions with backtracking issues:

Consider the following example application, which defines a check using a regular expression. A user entering user@aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa!.com as the email on a form will hang the web server.

class Email < ApplicationRecord
  DOMAIN_MATCH ='([a-zA-Z0-9]+)+\.com')

  validates :domain_matches


  def domain_matches
    errors.add(:email, 'does not match') if email =~ DOMAIN_MATCH



GitLab has Gitlab::UntrustedRegexp which internally uses the re2 library. re2 does not support backtracking so we get constant execution time, and a smaller subset of available regex features.

All user-provided regular expressions should use Gitlab::UntrustedRegexp.

For other regular expressions, here are a few guidelines:

  • If there's a clean non-regex solution, such as String#start_with?, consider using it
  • Ruby supports some advanced regex features like atomic groups and possessive quantifiers that eliminate backtracking
  • Avoid nested quantifiers if possible (for example (a+)+)
  • Try to be as precise as possible in your regex and avoid the . if there's an alternative
    • For example, Use _[^_]+_ instead of _.*_ to match _text here_
  • If in doubt, don't hesitate to ping @gitlab-com/gl-security/appsec


Go's regexp package uses re2 and isn't vulnerable to backtracking issues.

Further Links

Server Side Request Forgery (SSRF)


A Server-side Request Forgery (SSRF) is an attack in which an attacker is able coerce a application into making an outbound request to an unintended resource. This resource is usually internal. In GitLab, the connection most commonly uses HTTP, but an SSRF can be performed with any protocol, such as Redis or SSH.

With an SSRF attack, the UI may or may not show the response. The latter is called a Blind SSRF. While the impact is reduced, it can still be useful for attackers, especially for mapping internal network services as part of recon.


The impact of an SSRF can vary, depending on what the application server can communicate with, how much the attacker can control of the payload, and if the response is returned back to the attacker. Examples of impact that have been reported to GitLab include:

  • Network mapping of internal services
    • This can help an attacker gather information about internal services that could be used in further attacks. More details.
  • Reading internal services, including cloud service metadata.
    • The latter can be a serious problem, because an attacker can obtain keys that allow control of the victim's cloud infrastructure. (This is also a good reason to give only necessary privileges to the token.). More details.
  • When combined with CRLF vulnerability, remote code execution. More details.

When to Consider

  • When the application makes any outbound connection


In order to mitigate SSRF vulnerabilities, it is necessary to validate the destination of the outgoing request, especially if it includes user-supplied information.

The preferred SSRF mitigations within GitLab are:

  1. Only connect to known, trusted domains/IP addresses.
  2. Use the GitLab::HTTP library
  3. Implement feature-specific mitigations

GitLab HTTP Library

The GitLab::HTTP wrapper library has grown to include mitigations for all of the GitLab-known SSRF vectors. It is also configured to respect the Outbound requests options that allow instance administrators to block all internal connections, or limit the networks to which connections can be made.

In some cases, it has been possible to configure GitLab::HTTP as the HTTP connection library for 3rd-party gems. This is preferable over re-implementing the mitigations for a new feature.

Feature-specific mitigations

For situations in which an allowlist or GitLab:HTTP cannot be used, it will be necessary to implement mitigations directly in the feature. It is best to validate the destination IP addresses themselves, not just domain names, as DNS can be controlled by the attacker. Below are a list of mitigations that should be implemented.

There are many tricks to bypass common SSRF validations. If feature-specific mitigations are necessary, they should be reviewed by the AppSec team, or a developer who has worked on SSRF mitigations previously.

  • Block connections to all localhost addresses
    • (IPv4 - note the subnet mask)
    • ::1 (IPv6)
  • Block connections to networks with private addressing (RFC 1918)
  • Block connections to link-local addresses (RFC 3927)
    • In particular, for GCP: ->
  • For HTTP connections: Disable redirects or validate the redirect destination
  • To mitigate DNS rebinding attacks, validate and use the first IP address received

See url_blocker_spec.rb for examples of SSRF payloads

XSS guidelines


Cross site scripting (XSS) is an issue where malicious JavaScript code gets injected into a trusted web application and executed in a client's browser. The input is intended to be data, but instead gets treated as code by the browser.

XSS issues are commonly classified in three categories, by their delivery method:


The injected client-side code is executed on the victim's browser in the context of their current session. This means the attacker could perform any same action the victim would normally be able to do through a browser. The attacker would also have the ability to:

Much of the impact is contingent upon the function of the application and the capabilities of the victim's session. For further impact possibilities, please check out the beef project.

When to consider?

When user submitted data is included in responses to end users, which is just about anywhere.


In most situations, a two-step solution can be used: input validation and output encoding in the appropriate context.

Input validation

Setting expectations

For any and all input fields, ensure to define expectations on the type/format of input, the contents, size limits, the context in which it will be output. It's important to work with both security and product teams to determine what is considered acceptable input.

Validate input
  • Treat all user input as untrusted.
  • Based on the expectations you defined above:
    • Validate the input size limits.
    • Validate the input using an allowlist approach to only allow characters through which you are expecting to receive for the field.
      • Input which fails validation should be rejected, and not sanitized.
  • When adding redirects or links to a user-controlled URL, ensure that the scheme is HTTP or HTTPS. Allowing other schemes like javascript:// can lead to XSS and other security issues.

Note that denylists should be avoided, as it is near impossible to block all variations of XSS.

Output encoding

Once you've determined when and where the user submitted data will be output, it's important to encode it based on the appropriate context. For example:

Additional information

XSS mitigation and prevention in Rails

By default, Rails automatically escapes strings when they are inserted into HTML templates. Avoid the methods used to keep Rails from escaping strings, especially those related to user-controlled values. Specifically, the following options are dangerous because they mark strings as trusted and safe:

Method Avoid these options
HAML templates html_safe, raw, !=
Embedded Ruby (ERB) html_safe, raw, <%== %>

In case you want to sanitize user-controlled values against XSS vulnerabilities, you can use ActionView::Helpers::SanitizeHelper. Calling link_to and redirect_to with user-controlled parameters can also lead to cross-site scripting.

Do also sanitize and validate URL schemes.


XSS mitigation and prevention in JavaScript and Vue

  • When updating the content of an HTML element using JavaScript, mark user-controlled values as textContent or nodeValue instead of innerHTML.
  • Avoid using v-html with user-controlled data, use v-safe-html instead.
  • Render unsafe or unsanitized content using dompurify.
  • Consider using gl-sprintf to interpolate translated strings securely.
  • Avoid __() with translations that contain user-controlled values.
  • When working with postMessage, ensure the origin of the message is allowlisted.
  • Consider using the Safe Link Directive to generate secure hyperlinks by default.

GitLab specific libraries for mitigating XSS


Content Security Policy

Free form input field

Select examples of past XSS issues affecting GitLab

Internal Developer Training

Path Traversal guidelines


Path Traversal vulnerabilities grant attackers access to arbitrary directories and files on the server that is executing an application, including data, code or credentials.


Path Traversal attacks can lead to multiple critical and high severity issues, like arbitrary file read, remote code execution or information disclosure.

When to consider

When working with user-controlled filenames/paths and file system APIs.

Mitigation and prevention

In order to prevent Path Traversal vulnerabilities, user-controlled filenames or paths should be validated before being processed.

  • Comparing user input against an allowlist of allowed values or verifying that it only contains allowed characters.
  • After validating the user supplied input, it should be appended to the base directory and the path should be canonicalized using the file system API.

GitLab specific validations

The methods Gitlab::Utils.check_path_traversal!() and Gitlab::Utils.check_allowed_absolute_path!() can be used to validate user-supplied paths and prevent vulnerabilities. check_path_traversal!() will detect their Path Traversal payloads and accepts URL-encoded paths. check_allowed_absolute_path!() will check if a path is absolute and whether it is inside the allowed path list. By default, absolute paths are not allowed, so you need to pass a list of allowed absolute paths to the path_allowlist parameter when using check_allowed_absolute_path!().

To use a combination of both checks, follow the example below:

path = Gitlab::Utils.check_path_traversal!(path)
Gitlab::Utils.check_allowed_absolute_path!(path, path_allowlist)

In the REST API, we have the FilePath validator that can be used to perform the checking on any file path argument the endpoints have. It can be used as follows:

requires :file_path, type: String, file_path: { allowlist: ['/foo/bar/', '/home/foo/', '/app/home'] }

The Path Traversal check can also be used to forbid any absolute path:

requires :file_path, type: String, file_path: true

Absolute paths are not allowed by default. If allowing an absolute path is required, you need to provide an array of paths to the parameter allowlist.

OS command injection guidelines

Command injection is an issue in which an attacker is able to execute arbitrary commands on the host operating system through a vulnerable application. Such attacks don't always provide feedback to a user, but the attacker can use simple commands like curl to obtain an answer.


The impact of command injection greatly depends on the user context running the commands, as well as how data is validated and sanitized. It can vary from low impact because the user running the injected commands has limited rights, to critical impact if running as the root user.

Potential impacts include:

  • Execution of arbitrary commands on the host machine.
  • Unauthorized access to sensitive data, including passwords and tokens in secrets or configuration files.
  • Exposure of sensitive system files on the host machine, such as /etc/passwd/ or /etc/shadow.
  • Compromise of related systems and services gained through access to the host machine.

You should be aware of and take steps to prevent command injection when working with user-controlled data that are used to run OS commands.

Mitigation and prevention

To prevent OS command injections, user-supplied data shouldn't be used within OS commands. In cases where you can't avoid this:

  • Validate user-supplied data against an allowlist.
  • Ensure that user-supplied data only contains alphanumeric characters (and no syntax or whitespace characters, for example).
  • Always use -- to separate options from arguments.


Consider using system("command", "arg0", "arg1", ...) whenever you can. This prevents an attacker from concatenating commands.

For more examples on how to use shell commands securely, consult Guidelines for shell commands in the GitLab codebase. It contains various examples on how to securely call OS commands.


Go has built-in protections that usually prevent an attacker from successfully injecting OS commands.

Consider the following example:

package main

import (

func main() {
  cmd := exec.Command("echo", "1; cat /etc/passwd")
  out, _ := cmd.Output()
  fmt.Printf("%s", out)

This echoes "1; cat /etc/passwd".

Do not use sh, as it bypasses internal protections:

out, _ = exec.Command("sh", "-c", "echo 1 | cat /etc/passwd").Output()

This outputs 1 followed by the content of /etc/passwd.

GitLab Internal Authorization


There are some cases where users passed in the code is actually referring to a DeployToken/DeployKey entity instead of a real User, because of the code below in /lib/api/api_guard.rb

      def find_user_from_sources
        strong_memoize(:find_user_from_sources) do
          deploy_token_from_request ||
            find_user_from_bearer_token ||
            find_user_from_job_token ||

Past Vulnerable Code

In some scenarios such as this one, user impersonation is possible because a DeployToken ID can be used in place of a User ID. This happened because there was no check on the line with Gitlab::Auth::CurrentUserMode.bypass_session!( In this case, the id is actually a DeployToken ID instead of a User ID.

      def find_current_user!
        user = find_user_from_sources
        return unless user

        # Sessions are enforced to be unavailable for API calls, so ignore them for admin mode
        Gitlab::Auth::CurrentUserMode.bypass_session!( if Gitlab::CurrentSettings.admin_mode

        unless api_access_allowed?(user)

Best Practices

In order to prevent this from happening, it is recommended to use the method user.is_a?(User) to make sure it returns true when we are expecting to deal with a User object. This could prevent the ID confusion from the method find_user_from_sources mentioned above. Below code snippet shows the fixed code after applying the best practice to the vulnerable code above.

      def find_current_user!
        user = find_user_from_sources
        return unless user

        if user.is_a?(User) && Gitlab::CurrentSettings.admin_mode
          # Sessions are enforced to be unavailable for API calls, so ignore them for admin mode

        unless api_access_allowed?(user)