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To minimize the risk that an adversary will modify control-flow and disable security controls with an application, consider doing the following:. Organizations may want to know that their code is running in a Jailbroken environment for a number of different reasons. For example, they may choose to not honor a financial transaction conducted on the device due to increased uncertainty of its security environment.
An adversary can force an application to run in these devices by modifying the logic of the jailbreak-detection code. Jailbreak detection code is notoriously difficult to implement correctly due to a myriad of evolving techniques available for an adversary to bypass or trick the code.
The adversary successfully tricks the code into running in a hostile environment. Many security-sensitive iOS apps such as mobile banking and peer-to-peer payment apps require a secure environment in order to execute. These apps have capabilities to detect whether their host is sound. They may choose to not execute in jailbroken environments due to valid security concerns. The jailbreak-detection mechanisms implemented within many apps are exposed in the clear, without protection, and can be defeated easily.
There are various ways to detect whether an iOS device has been jailbroken. Below are some examples:. The above algorithms represent a small subset of the necessary algorithms needed to properly detect a jailbroken environment. Adversaries can use a wide assortment of reverse-engineering and integrity-violating schemes to bypass each specific algorithm technique. To automate attacks against jailbreak-detection mechanisms, adversaries leverage automated tools like xCon.
It has succeeded in attacking many apps. To effectively prevent automated jailbreak-detection attacks with tools like xCon, organizations must build a detection control that includes an accurate and complete set of algorithms that will detect a jailbroken environment. The set of algorithms and other aspects to look for is quite extensive.
Then, organizations must combine all of these algorithms with appropriate reverse-engineering and integrity-violation prevention techniques.
To mitigate the risks that the organization has not implemented a complete and balanced jailbreak detection routine, consider doing the following:. Within hybrid apps, an application contains an outer shell that is typically written in Java or Objective-C.
In the example code below, the organization uses a hardcoded key that an adversary can find and replace within a data security control implemented in Objective-C:. The adversary can then steal or modify the associated data. This section focuses on technical risks that result when an adversary is able to determine how an application is built. Risks highlighted in green in the following graph are discussed in greater detail within this section:.
The primary audience of this section is a technical audience interested in learning more about relevant attack vectors and mitigation strategies that relate to unauthorized reverse engineering of software. Code built using an intermediate language such as Objective-C or Java is highly vulnerable to reverse engineering.
Compiled applications written in these languages include source-level class interfaces and other rich metadata that the associated compiler will automatically include within the final binary.
An adversary can use easily accessible tools to extract this metadata to reveal a great deal of information about sensitive parts of the program. The adversary may find such information useful on its own or use it as a stepping-stone to perform unauthorized code modifications.
Objective-C and Java programs contain rich information about themselves. Both language compilers will embed definitions of the class interfaces and the relationships among the classes in the binaries. Such information is one of the first things an adversary will seek when attacking an app.
In the example below, an adversary extracts class interfaces from the binary using the class-dump-z tool. The tool is specifically built for reverse-engineering. Below is a class interface extracted from a real-world iOS banking app:.
The interface describes the underlying architecture and design of the application. This information greatly aids the adversary in identifying valuable targets within the application. In this particular interface, an adversary is going to immediately identify the jailbreakStatus method as a particularly attractive target for modification. If the adversary can successfully disable this method, an adversary will force the app to run in a particularly insecure perform that allows for subsequent attacks.
To mitigate the technical risks associated with exposing method interfaces and associated metadata, consider doing the following:. Objective-C and Java support dynamic redirection of method invocations from one method to another of the same signature. This feature is typically used by organizations when an application needs to perform method substitution or method extension of code. In such a scenario, the organization may not have source code for the original method.
An adversary can leverage method swizzling to monitor the order of execution of Objective-C method calls. This feature is also exploitable within Java environments through Cydia Substrate tools that facilitate such attacks. In doing so, an application can patch a method and execute additional methods each time the original method is invoked by the runtime engine.
An adversary can take advantage of this feature to create a log of method calls invoked by the application. An adversary will be able to understand the controlflow of an application without decrypting the binary and analyzing it through the use of tools like IDA Pro.
To mitigate the technical risks associated with controlflow analysis through method swizzling, consider doing the following:. Compiled applications written in these languages include source-level metadata that is included within the final binary.
An adversary can use easily accessible tools to extract such metadata to reveal sensitive static fields or other global variables. Typically, the adversary will attempt to modify the value of these fields at runtime to alter the behavior of the application.
Native apps contain program symbols that reveal the locations and semantics of their data. These symbols provide helpful information that facilitates reverse engineering. Hackers can easily extract the symbols and analyze their associated data using tools such as IDA Pro. As an illustration of the amount of information these symbols can reveal, below is a partial list of the symbols found on a real-world iOS banking app the list was produced by nm, a symbol-dumping command-line tool:.
In this example, the application declares sensitive data fields about authentication and credit card information and accurately describes what they will contain at runtime. Symbol names and locations reveal the internal assets of the application. Gcc produces extraneous export-table symbols including local symbols that it should not export.
Often, the application will not use such symbols at runtime. Organizations release the application with these symbols due to the default compiler settings. Typically, such strings are used by the application as parameters. An adversary can examine the contents of these strings and achieve a number of different objectives: Exposed string tables pose similar technical risks as other forms of exposed metadata such as methods and class fields.
However, this particular form of information gathering attack is particularly attractive to an adversary as the tables typically reveal much more sensitive information compared to code or data symbols. Application binaries contain plaintext string literals carried over from their source code.
Adversaries can easily extract these strings using tools like strings to quickly search for information that may help them in subsequent attacks. For instance, an adversary may be interested in finding authentication and authorization-related code. She can look for method names that match the patterns authenticate , authorize , password , token , access , or similar words.
After finding the strings of interest, the adversary can locate code that uses these strings to further the analysis. Below is a partial dump of strings found in a real-world iOS banking application binary the list was produced by strings, a command-line tool that extracts printable strings from arbitrary files:.
The dump shows that the application stores user information within a local database. Furthermore, the application appears to connect to a MySQL database that gathers user information. To do this, the application connects to a user profile database using username incomingApp with password kl23k2ls.
In response to this new information, an adversary may choose to conduct an infrastructure attack and connect to the profile database to extract privacy related data about the users of the app. The adversary can now perform further analysis to understand all jailbreak detection algorithms associated with this string.
An adversary uses a disassembler or decompiler to analyze the code that uses these sensitive strings. Analysis will lead to the code that the adversary is interested in compromising e. Applications use cryptographic keys to encrypt or decrypt sensitive data. However, adversaries discover such keys through static or dynamic binary analysis.
Consider an application that uses cryptographic operations provided by system libraries. The application must pass appropriate keys to these libraries in order to decrypt the data. At runtime, adversaries may choose to monitor the system library interface and intercept calls to decryption methods.
The application will pass the appropriate key as a parameter to these methods and the adversary will successfully grab the key. As another example, imagine an application that tries to mitigate this risk by implementing its own cryptography or statically links to a third-party library.
Through this analysis, the adversary learns that the secret AES key passed to the AESDecrypt method is derived from an MD5 hash of several constant strings encoded in the program. The adversary discovers that the key is not really a secret. Lastly, adversaries may use more sophisticated means of identifying cryptographic algorithms in use within the application. Special binary patterns or numeric constants indicate the presence of specific cryptographic algorithms e.
This technique requires more work than searching through program symbols and strings. To mitigate the risk that an adversary will intercept and steal cryptographic keys from an application, consider doing the following:. Adversaries often target proprietary algorithms encoded within mission-critical software because they intend on reproducing similar software. Without protection of the algorithm from examination, such algorithms are vulnerable to disclosure through the use of commonly available tools like IDA Pro or Hopper.
An adversary can then replicate these algorithms in their own software. In a more advanced scenario, the adversary may have to bypass code encryption security controls that attempt to restrict access to the original form of the binary. This can be done easily using tools like clutchmod. After bypassing any local decryption, the adversary can then return to the original task of analysis of the original binary. Often, these tools are very effective at recreating high-level pseudocode that is quite similar to the original source code.
Commercial software applications contain important proprietary algorithms that are vital to their business. Such algorithms, if disclosed, may result in reproduction of the same types of services by competitors.
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