SYSTEM ACTIVE // PROTOCOL: CONTEXT_AWARE

The Signal Through The Noise

Managing MSSP security for critical hospital infrastructure requires more than vigilance. It requires Context-Aware Logic.

Hardware Spec

Lenovo ThinkEdge SE455 V3 (AMD EPYC 8004, 64 Cores, NVIDIA L4 GPU).
Status: OPTIMAL for High-Compute Logic.

Mission Critical

Objective: Filter benign anomalies (PACS/MRI scans) from genuine threats (Sabotage/Intrusion).

The Hypothesis

The "Benign Anomaly" Paradox

False positives in hospitals often stem from authorized operations that look like attacks.

The Standard SIEM Failure

Wazuh's default ruleset uses "Atomic Alerting". A medical imaging server connecting to 50 workstations looks like a Network Scan.

ALERT: 5710 - Attempt to login as non-existent user
SRC: 192.168.1.50 (Internal PACS)
ACTION: BLOCKED (Critical Failure: Doctor locked out)

The Blackwall Solution

We move from Atomic Alerting to Threshold Alerting. We allow aggressive behavior ONLY if the source is known and the intent is verified.

LIVE LOG STREAM

The Logic Formula

Mathematical logic to eradicate false positives.

θ (Theta)

Threshold Frequency

We define a specific "Rate Limit". 1 failed login is a typo. 50 failed logins in 1 second is an attack.

Δt (Delta t)

Time Window

The specific timeframe to analyze. Allows for "bursty" traffic from hospital machines without triggering immediate alarms.

W (Whitelist)

Contextual Exclusion

Known benign hospital scanners and internal health checks (CDB Lists) are mathematically excluded from alerting.

Wazuh Implementation

From Concept to Code.

Define Variable W (Whitelist)

Create a Constant Database (CDB) list for known safe IPs. Compile using ossec-makelists.

Apply Frequency θ + Time Δt

Create a Child Rule overriding the default ID. Set frequency="8" and timeframe="120".

Silence the Noise (Level 0)

For events matching the Whitelist exactly, set alert level to 0. This effectively "deletes" the noise before it hits the dashboard.

local_rules.xml

<!-- Step 2: Apply the Formula (Frequency + Time) -->
<rule id="100100" level="10" frequency="8" timeframe="120">
  <if_matched_sid>5710</if_matched_sid>
  <same_source_ip />
  <!-- The Whitelist Logic -->
  <list field="srcip" lookup="not_address_match_key">etc/lists/hospital_allowlist</list>
  <description>High frequency of failed logins (Potentially Brute Force).</description>
  <group>authentication_failures,</group>
</rule>

<!-- Step 3: Silence the Noise -->
<rule id="100101" level="0">
  <if_sid>5710</if_sid>
  <srcip>192.168.1.50</srcip> 
  <description>Silence false positives from known Hospital Scanner.</description>
</rule>

Client Briefing Mode

Communicating the "Black Box" value to Hospital Administration.

The Triage Analogy

"Standard security monitoring functions like a basic motion detector. If anything moves, the alarm sounds. In a busy hospital, this creates thousands of false alarms."

Our Approach: ER Triage

Instead of treating every digital 'cough' as a Code Blue, our system applies intelligent criteria:

Is this happening once, or 50 times a second? (Severity)
Is this a known doctor or a stranger? (Identity)

Efficiency Score Simulator

INTERNAL METRIC

Optimization Level

Standard SIEM Blackwall Context-Aware

Total Alerts / Day 10,000

Efficiency Score 10%

Result

Analyst Fatigue: CRITICAL. 90% of time wasted on false alarms.