Remediating rogue applications
US-2015326586-A1 · Nov 12, 2015 · US
US12021892B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12021892-B2 |
| Application number | US-201916382805-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 12, 2019 |
| Priority date | Sep 27, 2013 |
| Publication date | Jun 25, 2024 |
| Grant date | Jun 25, 2024 |
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There is disclosed in one example a remediation server including: a hardware platform, including a processor, a memory, and a network interface; and instructions encoded within the memory to instruct the processor to: receive an application binary; create an application logic model of the application binary; and create personalization rules for the application binary based on the application logic model.
Opening claim text (preview).
What is claimed is: 1. A remediation server comprising: a hardware platform, comprising a processor circuit, a memory, and a network interface; and instructions encoded within the memory to instruct the processor circuit to: receive an application binary; create an application logic model (ALM) of the application binary, wherein creating the ALM comprises disassembling the application binary, modeling application logic according to the disassembling, creating a data flow structure that represents a lifetime of an object that passes through the application logic, and stepping through the ALM while tracking the data flow structure; determine, from the ALM, runtime application behavior modifications; and create personalization rules for the application binary, including implementing one or more application behavior modifications. 2. The remediation server of claim 1 , wherein the instructions are further to instruct the processor circuit to: detect malware behavior in the application binary; and heal the application binary by inserting or removing instructions to ameliorate the malware behavior and recompile the application binary. 3. The remediation server of claim 1 , wherein creating personalization rules comprises receiving application programming interface (API) intelligence from a platform API intelligence database. 4. The remediation server of claim 1 , wherein creating personalization rules comprises receiving threat intelligence from a global threat intelligence database. 5. The remediation server of claim 1 , wherein creating personalization rules comprises performing heuristic analysis on the application binary. 6. The remediation server of claim 1 , wherein the application logic model comprises structured text configured to contain text objects representing application programming interface (API) elements. 7. A computer-implemented method of providing malware remediation, comprising: receiving an application binary; creating an application logic model (ALM) of the application binary, wherein creating the ALM comprises disassembling the application binary, modeling application logic according to the disassembling, creating a data flow structure that represents a lifetime of an object that passes through the application logic, and stepping through the ALM while tracking the data flow structure; determine, from the ALM, runtime application behavior modifications; and creating personalization rules for the application binary including implementing one or more application behavior modifications. 8. The method of claim 7 , further comprising: detecting malware behavior in the application binary; and healing the application binary by inserting or removing instructions to ameliorate the malware behavior and recompile the application binary. 9. The method of claim 7 , wherein creating personalization rules comprises receiving application programming interface (API) intelligence from a platform API intelligence database.
Detection or prevention of fraud · CPC title
Anti-malware arrangements, e.g. protection against SMS fraud or mobile malware · CPC title
Access security · CPC title
to features or functions of an application · CPC title
Protecting personal data, e.g. for financial or medical purposes · CPC title
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