Another week, another "revolutionary" cloud security tool that floods my team with hundreds of alerts, 80% of which are noise. Tenable Cloud Security (or whatever they're calling it this quarter) is no different, especially when it comes to IAM policy findings.
Everyone talks about tuning, but I've yet to see a coherent strategy that doesn't just shift the problem or create a blind spot. The vendor's default answer is "adjust the severity" or "create an exception rule," which is just a polite way of saying "ignore it." That doesn't work for audit trails or actual risk management.
So, let's get specific. I'm looking at a recurring finding for "IAM policy allows *:* action." Sure, in a vacuum, that's bad. But it's on a break-glass emergency role used by three people, with conditional MFA and only in our SSO maintenance window. Tenable flags it as "Critical." My CISO's dashboard is permanently red.
What's the *actual* best practice here?
* Creating resource-based exclusions in Tenable for specific ARNs? That seems fragile.
* Modifying the scan policy to ignore certain policy patterns? That feels like we're just turning off the headlights.
* Or is the answer to feed it more context from our CI/CD pipeline or Terraform state, to differentiate between a deployed test policy and a production one?
I'm skeptical that any tool can do this well without becoming a full-time job to manage. Prove me wrong. What's your workflow for taming the IAM false positive beast, specifically with this platform? Show me the data or the process, not the marketing slides.
- cost_observer_42
cost_observer_42
I'm a staff SRE at a 800-person fintech, running our AWS estate and incident response. We've dealt with this exact alert fatigue across Tenable, Wiz, and in-house tooling.
* **Exception Strategy**: Resource-based exclusions (ARN wildcards) are indeed fragile. We moved to tagging every resource with a `security_justification` and feeding that into our scanner's context. Tenable can't ingest tags for logic natively, so we had to pipe findings to a Lambda that filtered them pre-dashboard. Added about 20 hours of engineering.
* **Policy Tuning Scope**: Modifying scan policy to ignore `*:*` on roles with `Condition` blocks is possible if you fork the rule pack. That's a full-time job to maintain. Vendor updates overwrite custom packs, so you re-apply diffs quarterly. At my last shop, this created a 3-day delay before new critical findings were reviewed.
* **Real Cost of "Noise"**: A "Critical" false positive isn't free. For us, each one triggered a mandated 30-minute ticket triage by a cloud engineer costing ~$40 per alert. At 100 false positives a week, that's a $200k/year drain. The tool's license was $85k.
* **Integration Depth**: The best practice is feeding more context (like SSO logs, actual usage) into the decision. Tenable's API is batchy and slow. We built a small service to correlate CloudTrail `AssumeRole` events with the flagged policies; if no usage in 90 days, it *is* critical. If used only in maintenance windows, we downgrade to "Low". This cut noise by 70%.
My pick is the custom correlation service, but only if you have a platform team to own it. If you don't, tell us your team size and whether your CISO mandates a single vendor's severity scale.
Five nines? Prove it.