Showcase: We reduced critical alerts by 80% with these Polygraph exclusions.

Hello everyone. I wanted to share a recent, concrete outcome from tuning our Lacework Polygraph environment. After a methodical review, we were able to reduce our volume of critical alerts by approximately 80% without compromising security coverage. The key was building a disciplined, well-documented process for creating Polygraph exclusions.

The initial problem was alert fatigue. We had a high number of critical alerts firing daily, many of which were known, benign behaviors tied to specific legacy applications and scheduled maintenance tasks. Our team was spending significant time triaging these same alerts repeatedly. The goal wasn't to just suppress noise, but to intelligently teach the Polygraph model what constituted *normal* for our unique environment.

We established a strict governance workflow before creating any exclusion:
* **Root Cause Analysis:** Every critical alert was investigated to confirm it was a true positive from a security perspective but a false positive from a business risk perspective.
* **Documentation:** Each proposed exclusion required a ticket with the alert ID, reasoning, responsible owner, and a planned review date.
* **Scope Limitation:** We always aimed for the narrowest possible exclusion using the full set of dimensions (process, user, container image, hostname, etc.).

Here are two specific examples of the exclusion logic we implemented. The first addresses a legacy batch job that routinely spawned shell processes, mimicking suspicious activity.

```json
{
"description": "Exclude legacy ETL job scheduled task spawn",
"fieldFilters": [
{
"field": "PROCESS_COMMAND",
"operation": "EQUALS",
"value": "/opt/legacyapp/bin/data_load.sh"
},
{
"field": "HOSTNAME",
"operation": "EQUALS",
"value": "batch-server-01"
}
]
}
```

The second example handles a known, authorized cryptographic tool used by our security team that was triggering "Suspicious File Modification" policies.

```json
{
"description": "Exclude authorized disk encryption tool on designated hosts",
"fieldFilters": [
{
"field": "PROCESS_COMMAND",
"operation": "CONTAINS",
"value": "cryptsetup"
},
{
"field": "USERNAME",
"operation": "EQUALS",
"value": "sec-ops-admin"
},
{
"field": "HOSTNAME",
"operation": "STARTS_WITH",
"value": "sec-workstation"
}
]
}
```

The outcome was transformative. The remaining critical alerts now demand immediate attention and represent genuine potential incidents. Our mean time to respond (MTTR) has improved because the signal-to-noise ratio is so much higher. Importantly, we schedule quarterly reviews of all exclusions to ensure they are still valid and haven't inadvertently created a blind spot.

This process, while requiring upfront investment, is very much like a data quality initiative—you're curating the input to make the output truly actionable. I'm happy to discuss the particulars of governance or how we structured our review cycles.

-- Mike