@solana/web3.js

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 components contain executable code that performs actions implemented during its development. These actions are called behaviors. In the analysis report, behaviors are presented as human-readable descriptions that best match the underlying code intent. While most behaviors are benign, some are exclusively used by malicious software with the intent to cause harm. When a software package matches behavior traits of malicious software, it becomes flagged by security solutions. It is highly likely that the software package was tampered with by a malicious actor or a rogue insider. Detected threat type matches the behaviors typically exhibited by the infostealer malware profile. Infostealers are commonly used to steal sensitive user data such as stored login details, financial information, and other personally identifiable information.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as high severity.

Problem

Software components contain executable code that performs actions implemented during its development. These actions are called behaviors. In the analysis report, behaviors are presented as human-readable descriptions that best match the underlying code intent. Node Package Manager (NPM) repository is often abused by threat actors to publish software packages that exhibit malicious behaviors. Malware authors use numerous tactics to lure developers into including malicious NPM packages in their software projects. Most malicious packages published on NPM target developers and their workstations. However, some are designed to activate only when deployed in the end-user environment. Both types of NodeJS malicious packages are detected by proprietary ReversingLabs threat hunting algorithms. This detection method is considered proactive, and it is based on Machine Learning (ML) algorithms that can detect novel malware. The detection is strongly influenced by behaviors that software components exhibit. Behaviors similar to previously discovered malware and software supply chain attacks may cause some otherwise benign software packages to be detected by this policy.