Binarly Description
Identify and address both recognized and unrecognized vulnerabilities throughout all stages of the device and software supply chain. Instead of simply aligning binaries with a catalog of known vulnerabilities, our method delves deeper into the execution of code, which allows for the detection of defects beyond just the binaries themselves. This innovative strategy enables Binarly to uncover a wide range of defect categories, surpassing the scope of known issues, and facilitates a quicker identification process with minimal false positives. We focus on recognizing both established and previously unidentified vulnerabilities, along with malicious activities, rather than relying solely on hash values or signature comparisons. Our approach expands insights past the Common Vulnerabilities and Exposures (CVE), revealing which vulnerabilities are present at the binary level. Additionally, by leveraging machine learning, we significantly reduce alert fatigue, achieving near-zero false positives, ensuring that our clients can focus on genuine security threats. Together, these strategies provide a comprehensive view of potential security risks in the supply chain.
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