Webroot Inc.

Open Text Corporation

Andrew L Sandoval

John R Shaw, Ii

Eric Klonowski

David Alan Myers

Examples of the present disclosure describe systems and methods for detecting and mitigating stack pivoting exploits. In aspects, various 'checkpoints' may be identified in software code. At each checkpoint, the current stack pointer, stack base, and stack limit for each mode of execution may be obtained. The current stack pointer for each mode of execution may be evaluated to determine whether the stack pointer falls within a stack range between the stack base and the stack limit of the respective mode of execution. When the stack pointer is determined to be outside of the expected stack range, a stack pivot exploit is detected and one or more remedial actions may be automatically performed.

Stack pivot exploit detection and mitigation

Examples of the present disclosure describe systems and methods for malicious software detection based on API trust. In an example, a set of software instructions executed by a computing device may call an API. A hook may be generated on the API, such that a threat processor may receive an indication when the API is called. Accordingly, the threat processor may generate a trust metric based on the execution of the set of software instructions, which may be used to determine whether the set of software instructions poses a potential threat. For example, one or more call stack frames may be evaluated to determine whether a return address is preceded by a call instruction, whether the return address is associated with a set of software instructions or memory associated with a set of software instructions, and/or whether the set of software instructions satisfies a variety of security criteria.

Malicious software detection based on API trust

The present disclosure relates to systems and methods for identifying highly sensitive modules and taking a remediation or preventative action if such modules are accessed by malicious software. For example, the likelihood that a module is used for an exploit, and is thus sensitive, is categorized as high, medium, or low. The likelihood that a module can be used for an exploit can dictate whether, and to what degree, an application accessing the module is 'suspicious.' However, in some instances, a sensitive module may have legitimate reasons to load when used in certain non-malicious ways. The system may also consider a trust level when determining what actions to take, such that an application and/or user having a higher trust level may be less suspicious when accessing a sensitive module as compared to an application or user having a lower trust level.

Managing the loading of sensitive modules

Examples of the present disclosure describe systems and methods for exploit detection via induced exceptions. One embodiment of a method can include generating an inspection point, the inspection point causing an exception when a set of software instructions encounters the inspection point during an execution of the set of software instructions by a processor, registering an exception handler to handle the exception associated with by the inspection point; receiving, in response to the set of software instructions encountering the inspection point, an indication of an exception, accessing a context record associated with the execution of the set of software instructions, evaluating the context record to determine if an exploit is present using the first reputation information, and based on a determination that an exploit is present, performing a corrective action for the exploit.

Exploit detection via induced exceptions

Examples of the present disclosure describe systems and methods for monitoring the security privileges of a process. In aspects, when a process is created, the corresponding process security token and privilege information is detected and recorded. At subsequent 'checkpoints,' the security token is evaluated to determine whether the security token has been replaced, or whether new or unexpected privileges have been granted to the created process. When a modification to the security token is determined, a warning or indication of the modification is generated and the process may be terminated to prevent the use of the modified security token.

Security privilege escalation exploit detection and mitigation

Examples of the present disclosure describe systems and methods for restricting access to application programming interfaces (APIs). For example, when a process calls an API, the API call may be intercepted by a security system for evaluation of its trustfulness before the API is allowed to run. Upon intercepting an API call, the process calling the API may be evaluated to determine if the process is known to the security system, such that known processes that are untrusted may be blocked from calling the API. Further, when the security system cannot identify the process calling the API, the security service may evaluate a call stack associated with the call operation to determine if attributes of the call operation are known to the security system. If the call operation is known to the security system as untrusted, the call operation may be blocked from calling the API.

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San Antonio, TX, United States of America

Andrew L Sandoval