Machine learned model for generating opinionated threat assessments of security vulnerabilities
US-2024411898-A1 · Dec 12, 2024 · US
US8990930B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-8990930-B2 |
| Application number | US-36666609-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 6, 2009 |
| Priority date | Feb 6, 2009 |
| Publication date | Mar 24, 2015 |
| Grant date | Mar 24, 2015 |
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Attempts to make code secure often are associated with performance penalties. To facilitate striking an acceptable balance between performance and security, vulnerable areas of source code are identified. The vulnerable areas are examined for areas that are actually safe and the safe areas are filtered from the universe of code that receives security mitigations. The remaining code receives security mitigations appropriate to the level of risk of the code.
Opening claim text (preview).
What is claimed: 1. A system for mitigating security risks in computer program code comprising: a processor and a memory including a risk analysis module configured to cause the processor to: identify vulnerable areas of a source code, wherein the vulnerable areas of the source code are vulnerable to unauthorized exploitation; identify safe areas of the source code within the vulnerable areas of the source code for which security mitigation code will not be inserted; filter o…
Physics · mapped topic
Physics · mapped topic
Physics · mapped topic
Physics · mapped topic
Physics · mapped topic
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