I've been conducting a detailed evaluation of Orca Security for our cloud security posture management needs, and while reviewing the documentation for a planned proof of concept, I discovered a feature that isn't widely discussed in mainstream reviews: the ability to fully customize the severity scoring rules for their policy-driven findings.
Most CSPM and CNAPP platforms apply a static, vendor-defined CVSS or proprietary severity score to vulnerabilities and misconfigurations. Orca, however, provides administrative access to the underlying rule logic, allowing security teams to adjust the risk scoring based on their specific environment and risk tolerance. This is crucial for reducing alert fatigue and prioritizing remediation based on actual business impact, not just a generic score.
The customization is managed within the Orca Policy Engine. You can modify both the **likelihood** and **impact** parameters for a finding, which in turn recalculates the final severity (Critical, High, Medium, Low, Info). For instance, a finding like "S3 Bucket is Publicly Accessible" might be scored by default as High. In our development environment, where certain buckets are intentionally public for static web hosting, we can lower the impact score, thereby downgrading the overall severity to Low or even informational for those specific, tagged assets.
The configuration is performed via a JSON-like structure within the platform's policy editor. Here is a simplified illustrative example of a rule adjustment targeting AWS resources with a specific `Environment: Dev` tag:
```json
{
"rule_id": "aws_s3_bucket_public_read",
"adjusted_scoring": {
"conditions": [
{
"field": "aws.tags.Environment",
"operator": "equals",
"value": "Dev"
}
],
"override": {
"impact": 2,
"likelihood": 1
}
}
}
```
Key considerations and potential pitfalls from my analysis:
* **Granularity:** Adjustments can be scoped to specific cloud accounts, resource types, tags, or even combinations of attributes. This allows for very precise tuning.
* **Inheritance:** It's vital to document your custom scoring rules, as they become part of your organization's policy baseline. New team members must be aware that the severity they see is already contextualized.
* **Drift Management:** If you manage rules via Infrastructure as Code (IaC) templates (e.g., Terraform), you must ensure your Orca scoring adjustments align. A misconfiguration you've scored down in Orca might still be flagged as a critical drift in your IaC scans.
* **Audit Trail:** Orca maintains a log of who changed a scoring rule and when, which is essential for compliance audits and understanding shifts in your dashboard's risk landscape.
This level of customization significantly alters the value proposition. It shifts Orca from a purely out-of-the-box compliance tool to a tailored risk management platform. For teams with mature, tag-governed cloud environments, this feature alone could justify a deeper integration into the SOC and development workflows, as it directly influences the priority of tickets generated in downstream systems like Jira or ServiceNow.
I'm interested to hear from other long-term users: have you implemented custom severity scoring, and how has it affected your mean time to respond (MTTR) or the signal-to-noise ratio in your security alerts?
— Amanda
Data > opinions
That's a fantastic observation about the Orca Policy Engine. The ability to dial in likelihood and impact parameters is what moves a tool from being a noisy alert generator to a true risk management platform. I've seen too many teams waste cycles on "Critical" findings that, in their specific architectural context, simply aren't.
Your S3 bucket example is perfect. I'd add a caveat from an operational perspective: the real test is whether you can consistently apply these custom rules across your entire asset inventory over time. I've evaluated systems where custom scoring worked well initially, but then a platform update or new service integration introduced findings that bypassed the custom logic, causing a regression in alert quality. The maintenance burden of the rule set becomes a factor.
Does Orca provide any form of version control or audit trail for changes made to these scoring rules? That's become a non-negotiable requirement for us, as any change to severity effectively changes our SLA for remediation.