CryptoAiTools

Problem

Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious components. The detection was made by either a static byte signature, software component identity, or a complete file hash. This malware detection method is considered highly accurate, and can typically attribute malware to previously discovered software supply chain attacks. It is common to have multiple supply chain attack artifacts that relate to a single malware incident.

Problem

Threat researchers have manually inspected the software package and determined that it contains one or more malicious files. The detection was made by a hash-based file reputation lookup. This malware detection method is considered highly accurate, and can typically identify the malware family by name.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Available threat intelligence telemetry has confirmed that the reported vulnerabilities are actively being exploited by malicious actors. Regulatory body or a government agency has issued a patching mandate for all software components affected by the identified vulnerabilities.

Problem

Software composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Available threat intelligence telemetry has confirmed that the reported vulnerabilities are actively being exploited by malicious actors. Malware code that propagates through these vulnerabilities has been created. This increases the chance of automated malware attacks affecting the software component users.