Hey folks! Been tinkering with Tenable Cloud Security for a few months now, mostly for vulnerability scanning in our AWS accounts. Recently, our team got the "fun" task of preparing for a SOC2 audit, and I figured I could use it to help build a basic compliance workflow. It's not a silver bullet, but it gave us a great starting point for continuous monitoring of our cloud posture.
The core idea was to map a few critical SOC2 criteria (like CC6.1 for logical access) to specific Tenable policies, then get alerts into our normal ops channels. We started by enabling the built-in "CIS Foundations" and "AWS Foundational Security Best Practices" policy templates. Those cover a ton of the basic security controls. Then, I created a custom policy group just for our SOC2-related checks to keep things focused.
Here's a snippet of the Terraform I used to set up a CloudWatch Events rule that triggers a Lambda whenever Tenable finds a "FAIL" on one of our high-severity SOC2 checks. The Lambda formats the finding and posts it to our security Slack channel.
```hcl
resource "aws_cloudwatch_event_rule" "tenable_soc2_findings" {
name = "tenable-soc2-findings"
description = "Capture FAIL events from Tenable for our SOC2 policy group"
event_pattern = jsonencode({
source = ["aws.securityhub"]
detail-type = ["Security Hub Findings - Imported"]
detail = {
findings = {
ProductArn = [{ prefix = "arn:aws:securityhub:us-east-1::product/tenable/tenable-cs" }]
GeneratorId = [{ prefix = "tenable-soc2-policy-group" }]
Compliance = {
Status = ["FAILED"]
}
}
}
})
}
```
The real win was the visibility. Instead of a frantic scramble before the audit, we now have a weekly digest of compliance posture. We paired this with some custom SQL queries in Tenable's export data to track trends over time. It's not a full GRC platform, but for a small team, it automates the evidence collection for a chunk of the technical requirements.
Has anyone else tried something similar? I'm curious if you've integrated the findings further, maybe into Jira for automated ticket creation, or how you handle the false positives for managed services.
cost first, then scale
Mapping specific SOC2 criteria to policies is clever. I've been trying to figure out where to even start with that.
How do you decide which checks are "high-severity" for your alerts? Is that just based on the Tenable finding, or do you have your own internal ranking?
Still learning.
Great question. For us, the Tenable severity is just the starting point. We overlay our own business impact ranking.
For example, a "Critical" finding for an unused security group in a dev account might get downgraded to a low-priority ticket. But a "Medium" finding for public read access on an S3 bucket holding customer logs? That's an immediate page, because of the data sensitivity. Our internal ranking looks at data classification, which team owns it, and if it's in a production environment.
It means maintaining a small internal mapping table, but it stops alert fatigue. The Tenable score tells you the technical risk, but you need your own context to know the actual business risk.
Integrate or die
Exactly this. We did the same mapping and cut our pager alerts by over 70% overnight. The tool's risk score is a generic benchmark, but your business context is the actual cost center.
Our twist was tying the internal ranking directly to cost. That public S3 bucket example? We also calculated the hypothetical blast-radius cost of a breach, based on data egress fees and support hours. A "medium" finding with a potential five-figure price tag jumps the queue.
It becomes a FinOps-SecOps hybrid ticket. Teams respond faster when you can say "ignoring this risks a $15k bill" versus just "this is a security medium."
Cloud costs are not destiny.