We have a pile of old internal apps running on VMs. Some are EOL, some the vendor is gone. Prisma Cloud lights them up like a Christmas tree with critical vulns we can't fix.
I need a pragmatic containment strategy, not theoretical "just patch it" advice. We're already segmenting the network.
Looking for concrete steps others have taken, especially around:
* Prisma alert rules to suppress noise for known-unpatchable assets
* Using Prisma's compensating controls tracking effectively
* Runtime protection configurations that actually matter for static legacy apps
* How you document the risk acceptance for auditors
Example of a custom alert rule we're considering to stop the alert spam:
```yaml
- name: "Legacy App - Suppress Known Vulns"
description: "Suppress alerts for approved legacy apps list"
target:
- "account:ProdLegacy"
filters:
- "vulnerability.severity in ['critical', 'high']"
- "resource.id in ['app-server-01', 'app-server-02']"
- "vulnerability.cve in ['CVE-2017-1234', 'CVE-2018-5678']"
enabled: true
action: "dismiss"
```
Is this the right approach, or are we creating a blind spot?
slow pipelines make me cranky
I'm a senior platform engineer at a 3k-person fintech company. We run a mix of modern k8s workloads and a stubborn fleet of about two dozen legacy .NET and Java apps on VMS, so this is a daily reality for my team.
* **Noise Reduction via Asset Tags:** Instead of suppressing by individual resource ID or CVE, we created a Prisma asset tag like `legacy_unpatchable=true`. Our alert rule suppresses critical/high vulns only when that tag is present AND the asset is in a specific, isolated network segment (tag: `network_segment=legacy_dmz`). This creates a two-key approval system that prevents accidental blind spots.
* **Compensating Controls as Code:** We treat Prisma's compensating controls as living documentation. Each control (like "host firewall drops all inbound except LB on port 443") is linked to a ticket ID and validated by a Terraform output or a Wiz-like query. This turns a manual note into an auditable, automated check. We review these quarterly.
* **Runtime Protection Focus:** For static legacy apps, we found the most value in turning on **all** reverse-shell and code-execution defenses, but disabling "credential access" and "persistence" alerts which were mostly noisy failed login attempts. The runtime policy became "only alert on critical severity behavioral events." This cut our legacy app runtime alerts by about 80%, letting us focus on real attack paths.
* **Audit Documentation:** We have a "Legacy Exception" record in our GRC platform (ServiceNow) that links to the Prisma asset, lists the vulns, documents the business reason for no patch, and links to the active compensating controls. The key is that the exception auto-expires every 90 days, forcing a re-review. It's a pain, but auditors accept it as a formal process.
Your YAML approach is a decent start, but it will become unmanageable. Hard-coding CVE and instance IDs means every new server or discovered vuln requires a config change. You'll fall behind. Use tags to dynamically define the asset group, and consider a separate rule that suppresses based on a manually curated, external list of CVEs that you feed into Prisma via API. This keeps the rule static and the list dynamic.
My pick for your scenario is to combine Prisma's native tags and compensating controls with a separate, small script to sync approved exceptions from a CMDB. If your main constraint is *time to implement*, start with tags. If your main constraint is *auditor satisfaction*, start with the compensating controls as code and the expiring exception process. Which of those two pressures is greater?