Start Left™'s Security Monitoring Capability:

Toxic Combinations

From the perspective of cloud product security, data analytics illuminates toxic combinations, for example: an app is publicly accessible, it handles sensitive data subject to PCI DSS regulations, it has a large user base, the Product Team has low visibility into their process risks, there are a large number of vulnerabilities present......

High Impact Opportunities

For vulnerability management, our security analytics automatically prioritizes high-impact opportunities, for example, where a Common Vulnerabilities and Exposures (CVE) is a level 7 and is highly exploited, affects 100 products across the entire product portfolio is considered more crucial to fix than a CVE that is a level 10 and only affects 1 product.

Most Improved Product / Team

Our analytics constantly track a variety of indicators on to highlight product teams that have successfully improved their risk management and where they still need to focus their efforts. They pertain to reducing risks over time through monitoring integrations, risk remediation performance, security hygiene, and team performance on each product team.

Risk Scenarios

Security monitoring automatically detects risk scenarios in cloud product security that include the accidental exposure of critical information, IP, or resources, as well as the illegal access of malicious actors, examples include: inadequate access control, segmentation, and cloud security, as well as a code repository that has been accidentally made public.

Risk Combinations

When numerous risk scenarios are present in tandem or correlated over time, it poses a risk combination. For example, supply chain compromise: in September 2022, detection of a team's code private repository changes to public, and in January 2023, detection of build process tampering, both events correlated by Start Left™ and raised as alert.

Threat Predictions

Comprehensive protection is completed with full lifecycle security monitoring and analytics to enhance actions by correlating patterns across all risk data in real time. This technique highlights which high-risk assets are likely to be compromised and direct attention there, especially with an active attacker present and can easily switch targets.