> For the complete documentation index, see [llms.txt](https://wiki.lucysecurity.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://wiki.lucysecurity.com/guides/attack-simulations/regular-expressions-in-login-fields.md). # Regular Expressions in Login Fields ### Introduction Lucy can create phishing scenarios where users are prompted to [login on a landing web page](/guides/attack-simulations/attack-types/data-entry-attack.md). To ensure that only valid logins are counted as successful attacks, Lucy allows you to define regular expressions within the login field, which serve as filters for login criteria. These criteria can include requirements such as: * Passwords containing at least two alphanumeric characters. * Usernames containing a specific domain name, among others. ### Configuration For Lucy to apply regular expressions in a login field, the login form must use a POST method with the login action set to "**?login**". Additionally, the name of the login field should be "**login**" and the name of the password field should be "**password**". A valid login field in Lucy might resemble the following HTML snippet: ```html ``` You can configure login filters [under scenario settings](/application-reference/campaigns/campaign-settings/main-settings/attack-simulation.md#regexp) once you've set up the login fields with the correct naming convention. Lucy will then be able to apply the filter mechanism. You can choose from a list of existing filter examples in the dropdown menu, or apply any POSIX regular expression filter within the input fields.

Additionally, Lucy supports JavaScript-based login filters. An example of such a function verifies if the username starts with certain letters and checks if the password is complex. If both conditions are met, the script sends fake login data to Lucy for admin verification. ```html ``` Make sure to download the corresponding JavaScript libraries and include them in your campaign template (landing page). {% file src="/files/drl1X0hMAzKqJ33RXsZi" %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://wiki.lucysecurity.com/guides/attack-simulations/regular-expressions-in-login-fields.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.