What factors are contributing to the increased false positive rate in Orca Security's agentless vulnerability assessment scans during the last quarter?

Introduction

The increased false positive rate in Orca Security's agentless vulnerability assessment scans during the last quarter is a critical issue that requires immediate attention. This problem could significantly impact customer trust, product efficacy, and overall business performance. To address this complex challenge, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent product update. Has there been any significant change to the scanning algorithm or vulnerability database in the last quarter?

Why it matters: Recent changes could directly impact scan accuracy. Expected answer: Yes, there was an update to the vulnerability database. Impact on approach: If confirmed, we'd focus on the database update as a primary factor.

• Considering the nature of false positives, I'm curious about the types of vulnerabilities being flagged incorrectly. Are these false positives concentrated in specific vulnerability categories or spread across all types?

Why it matters: This helps identify if the issue is systemic or specific to certain vulnerability types. Expected answer: False positives are primarily in newly added vulnerability categories. Impact on approach: We'd investigate the process for adding and validating new vulnerability categories.

• Given the agentless nature of the scans, I'm wondering about any changes in the environments being scanned. Have there been any significant shifts in the types of systems or cloud environments our customers are using?

Why it matters: Environmental changes could affect scan accuracy without any internal changes. Expected answer: There's been an increase in containerized and serverless environments. Impact on approach: We'd focus on how our scanning technology adapts to these newer environments.

• Thinking about our measurement processes, I'm curious if there have been any changes in how we define or measure false positives. Has the methodology for identifying and classifying false positives remained consistent?

Why it matters: Changes in measurement could artificially inflate the false positive rate. Expected answer: The measurement process has remained consistent. Impact on approach: We'd rule out measurement issues and focus on actual scan performance.