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You can implement all validation in the language of choice, whether that s Java, C#, C++, PHP or Ruby. , Server-side validation requires a round trip between the client and the server, which wastes network resources. Server-side validation is considered secure, because you can use a firewall to control access to the server-side resource. Client-side validation is the preferred route from a performance perspective, and serverside validation is the preferred route from a security perspective. However, you want both the best performance and the best security, which seems impossible. You must choose between performance and security. No magic trick gives you both without any disadvantages. If you were to use a compiled application instead of a Web client, you d still have the same problems. Even if your compiled client application were to use encryption, you d still have security problems. And if you have security problems, then you have validation problems, so client-side validation must be considered insecure. Having established that you cannot ensure the validity of the data from a security perspective, you need to consider whether you need the performance or the partial security. Going back to the calculator application shown in Figure 3-1, you can make the argument that client-side validation is good enough. If a hacker were to present invalid data, then the calculation would not work, and the server would generate an error. If the server is presented with invalid data, under no circumstance should the invalid data cause the server to generate a general protection fault (GPF). You need to distinguish validation for system correctness from validation for application correctness. When data has been verified for system correctness, it means that the data is correct, but it might not make sense. When data has been verified for application correctness, it means that the data is correct and makes sense. Most developers focus on application data validation and not system data validation, partly because application data validation implies system data validation. However, by mixing the two validations, you can miss many system validation scenarios. Consider this example, which illustrates the problems of mixing different validations: In a quest to provide the best security, a well-known online Web mail provider implements a server-side validation tool to filter email for malicious JavaScript statements. Without the filter, users could inadvertently display an email that could act as a Trojan or a virus. However, a hacker manages to fool the filter with the following code: <img src='http://server/image.gif' target=""onload="javascript that uses single quotes and just goes on and on"> In the example source, the HTML tag img has an src attribute, but also a target and an onload attribute. From a system-level perspective, this means there are three attributes. The problem with the server filter is that it treats the target and onload attributes as one attribute. This probably occurs because an application-level validation filter was created that didn t verify the data at the system level. Had the validation routines performed both a system-level validation and an application-level validation, the error most likely would have been caught.
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State and validation are not a simple problem. State and validation involve both a client side and a server side, and involve both system-level validation and application-level validation. With this knowledge, you can now assemble the calculator application into an architecture (see Figure 3-2).
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Figure 3-2. Proposed validation architecture
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Figure 3-2 shows two levels of validation: system-level validation performed by the client, and application-level validation performed by the server. In the calculator example, that means that the client validates the correctness of the number entered by the user, and the server validates that the two numbers can be added together and that no overflow or underflow will happen. In the proposed validation architecture, one problem remains: The client is considered insecure, but the server expects that the client will send the right data. This could be a recipe for disaster, but not because of how application validation is implemented. With most technical implementations, application validation implies system-level validation. The architecture of Figure 3-2 proposes an overall plan of action: to let the client do system-level validation only, and to let the server handle the heavy-duty work of validating the data completely. The client fixes up the data so that errors are already removed. The server side assumes that the data is correct, but still has the capability to catch errors if they occur.
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