Applications of cross-site scripting:-

An attacker that uses a cross-site scripting flaw can usually do the following:

Assume the identity of the victim user.

Execute every action that the user is capable of.

Read any data that the user has permission to see.

Deface the website using a virtual defacement.

Incorporate trojan-like behaviour into the website.

How to find XSS vulnerabilities:

Burp Suite's web vulnerability scanner can quickly and accurately detect the vast majority of XSS vulnerabilities.

Manually testing for reflected and stored XSS usually entails entering some simple unique input (such as a short alphanumeric string) into each entry point in the application, identifying every location where the submitted input is returned in HTTP responses, and testing each location separately to see if suitably crafted input can be used to execute arbitrary JavaScript. This allows you to identify the context in which the XSS happens and choose an appropriate payload to exploit it.

Manually testing for DOM-based XSS in URL parameters follows a similar pattern: enter some simple unique input in the parameter, use the browser's developer tools to search the DOM for this input, then test each place to see if it's exploitable. Other varieties of DOM XSS, on the other hand, are more difficult to detect. There is no replacement for studying JavaScript code, which can be incredibly time-consuming, to uncover DOM-based vulnerabilities in non-URL-based input (such as document.cookie) or non-HTML-based sinks (such as setTimeout).

XSS attack prevention:

Preventing cross-site scripting can be simple in some circumstances, but it can be much more difficult in others, depending on the application's sophistication and how it handles user-controllable data.

In general, preventing XSS vulnerabilities will almost certainly need a mix of the following measures:

On arrival, filter the input. Filter user input as precisely as feasible at the point when it is received, based on what is expected or valid input.

Data on the output should be encoded. Encode user-controllable data in HTTP responses to avoid it being misinterpreted as active content. This may necessitate a combination of HTML, URL, JavaScript, and CSS encoding, depending on the output context.

Use response headers that are relevant. You can use the Content-Type and X-Content-Type-Options headers to ensure that browsers read HTTP responses in the way you intend, preventing XSS in HTTP responses that aren't supposed to contain any HTML or JavaScript.

Topic:- Use case Scenario on XSS

Threat Agents / Attack Vectors

Almost every major incident is built on the foundation of insufficient logging and monitoring.

To achieve their objectives without being caught, attackers rely on a lack of monitoring and prompt action.

Is the Application Vulnerable?

* Logins, unsuccessful logins, and high-value transactions are not logged as auditable events.

* Errors and warnings provide no, insufficient, or ambiguous log messages.

* Suspicious activity is not detected in application and API logs.

* Logs are only kept on-site.

* Appropriate alerting thresholds and response escalation processes aren't in place or aren't working properly.

* Penetration testing and DAST tool scans (such as OWASP ZAP) do not generate alarms.

* In real time or near real time, the programme is unable to detect, escalate, or alert for active attacks.

Attack Scenarios:-

Scenario #1: An open source project forum software run by a small team was hacked using a flaw in its software. The attackers managed to wipe out the internal source code repository containing the next version, and all of the forum contents. Although source could be recovered, the lack of monitoring, logging or alerting led to a far worse breach. The forum software project is no longer active as a result of this issue.

Scenario #2: An attacker uses scans for users using a common password. They can take over all accounts using this password. For all other users, this scan leaves only one false login behind. After some days, this may be repeated with a different password.

Scenario #3: A major US retailer reportedly had an internal malware analysis sandbox analyzing attachments. The sandbox software had detected potentially unwanted software, but no one responded to this detection. The sandbox had been producing warnings for some time before the breach was detected due to fraudulent card transactions by an external bank.