The three metric groups that are needed to calculate CVSS scores are Base, Temporal, and Environmental. The Base metrics represent the intrinsic characteristics of a vulnerability that are constant over time and across user environments. The Temporal metrics represent the characteristics of a vulnerability that may change over time but not across user environments. The Environmental metrics represent the characteristics of a vulnerability that are relevant and unique to a particular user’s environment. Verified References:

https://nvd.nist.gov/vuln-metrics/cvss

https://www.first.org/cvss/specification-document

DMARC (Domain-based Message Authentication, Reporting and Conformance) and SPF (Sender Policy Framework) are two mechanisms that can help detect and prevent email spoofing, which is the creation of email messages with a forged sender address. DMARC allows a domain owner to publish a policy that specifies how receivers should handle messages that fail authentication tests, such as SPF or DKIM (DomainKeys Identified Mail). SPF allows a domain owner to specify which mail servers are authorized to send email on behalf of their domain. By checking the DMARC and SPF records of the sender’s domain, a receiver can verify if the email is from a legitimate source or not. Verified References:

https://en.wikipedia.org/wiki/Email_spoofing

https://en.wikipedia.org/wiki/DMARC

https://en.wikipedia.org/wiki/Sender_Policy_Framework

Implementing an ongoing, third-party software and library review and regression testing is the best way to maximize risk reduction from vulnerabilities introduced by OpenSSL. Third-party software and libraries are often used by developers to save time and resources, but they may also introduce security risks if they are not properly maintained and updated. By reviewing and testing the third-party softwareand library regularly, the company can ensure that they are using the latest and most secure version of OpenSSL, and that their proprietary software is compatible and functional with it.

A static code analyzer is a tool that analyzes computer software without actually running the software. A static code analyzer can help developers find and fix vulnerabilities, bugs, and security risks in their new applications while the source code is in its ‘static’ state. A static code analyzer can help ensure that the code has close to zero defects and zero vulnerabilities by checking the code against a set of coding rules, standards, and best practices. A static code analyzer can also help improve the code quality, performance, and maintainability.

A. An open-source automation server is not a tool that can help ensure that the code has close to zero defects and zero vulnerabilities. An open-source automation server is a tool that automates various tasks related to software development and delivery, such as building, testing, deploying, and monitoring. An open-source automation server can help speed up the CI/CD pipeline, but it does not analyze or improve the code itself.

C. Trusted open-source libraries are not tools that can help ensure that the code has close to zero defects and zero vulnerabilities. Trusted open-source libraries are collections of reusable code that developers can use to implement common or complex functionalities in their applications. Trusted open-source libraries can help save time and effort for developers, but they do not guarantee that the code is free of defects or vulnerabilities.

D. A single code repository for all developers is not a tool that can help ensure that the code has close to zero defects and zero vulnerabilities. A single code repository for all developers is a centralized storage location where developers can access and manage their source code files. A single code repository for all developers can help facilitate collaboration and version control, but it does not analyze or improve the code itself.

https://www.comparitech.com/net-admin/best-static-code-analysis-tools/

https://www.perforce.com/blog/sca/what-static-analysis

The indicator that shows when a company might not be viable after a disaster is the maximum tolerable downtime (MTD). MTD is the maximum amount of time that a business process or function can be disrupted without causing unacceptable consequences for the organization. MTD is a key metric for business continuity planning and disaster recovery, as it helps determine the recovery time objective (RTO) and the recovery point objective (RPO) for each process or function. If the actual downtime exceeds the MTD, the organization may face severe losses, reputational damage, regulatory penalties, or even bankruptcy. Verified References:

https://www.techtarget.com/searchdisasterrecovery/definition/maximum-tolerable-downtime

https://www.techtarget.com/searchdisasterrecovery/definition/recovery-time-objective

https://www.techtarget.com/searchdisasterrecovery/definition/recovery-point-objective