Blog

Insights from the network layer.

Threat analysis, product thinking, and security research from the Personam team.

Detecting Lateral Expansion From Compromised Edge Appliances
AI Threats

Detecting Lateral Expansion From Compromised Edge Appliances

Edge appliances sit under constant targeting. Attackers actively scan the internet for known vulnerabilities in enterprise VPN gateways, remote access portals, and edge firewalls. When…

Chuck Faughnan III · November 12, 2026 Read →
Neutralizing Third-Party and Clinical Supply Chain Risk
Healthcare Security

Neutralizing Third-Party and Clinical Supply Chain Risk

Healthcare delivery systems run on interconnected dependencies. Clinical diagnostic tools, remote radiology reading stations, outsourced billing services, and HVAC controls connect directly to internal hospital…

Chuck Faughnan III · November 5, 2026 Read →
AI-Driven Phishing Ends at the Login. The Attack Doesn’t.
AI Threats

AI-Driven Phishing Ends at the Login. The Attack Doesn’t.

Generative AI has fundamentally changed initial access mechanics. Attackers no longer rely on poorly worded emails or obvious phishing links to harvest credentials. AI-assisted campaigns…

Chuck Faughnan III · October 30, 2026 Read →
Intercepting Ransomware Outages at the Wire Layer
AI Threats

Intercepting Ransomware Outages at the Wire Layer

Ransomware operations across healthcare facilities no longer begin with noisy, immediate file encryption. Modern Ransomware-as-a-Service (RaaS) affiliates operate with calculated restraint. Upon breaching an entry…

Chuck Faughnan III · October 19, 2026 Read →
Healthcare Agentless Behavioral Threat Detection Architecture
Network Data Doesn't Lie

Healthcare Agentless Behavioral Threat Detection Architecture

Agentless behavioral threat detection turns raw network telemetry into actionable intelligence, revealing insider threats and credential misuse across healthcare networks without endpoint software agents.

Chuck Faughnan III · September 4, 2026 Read →
Detecting Living-off-the-Land Lateral Movement | Personam AI
Network Data Doesn't Lie

Detecting Living-off-the-Land Lateral Movement | Personam AI

Adversaries using legitimate administrative tools often bypass legacy EDR and SIEM defenses. Unsupervised network behavioral AI detects subtle cohort anomalies to intercept lateral movement before…

Chuck Faughnan III · September 4, 2026 Read →
Why Log Aggregation Fails: Real-Time Metadata-First NDR
Network Data Doesn't Lie

Why Log Aggregation Fails: Real-Time Metadata-First NDR

Log files are downstream, derivative, and easily cleared by adversaries. Learn how metadata-first NDR operates below log files to detect threats within seconds.

Chuck Faughnan III · September 4, 2026 Read →
Agentless Behavioral Detection | Stop Low & Slow Attacks
Uncategorized

Agentless Behavioral Detection | Stop Low & Slow Attacks

Personam delivers agentless behavioral detection that stops low and slow network attacks and living-off-the-land tradecraft without host software or complex rule tuning.

Chuck Faughnan III · September 4, 2026 Read →
Securing Acquired Regional Clinics Before Domain Integration
Uncategorized

Securing Acquired Regional Clinics Before Domain Integration

Healthcare mergers create immediate cybersecurity exposure across transitional network connections. Learn how agentless behavioral telemetry provides instant visibility and stops cross-domain credential abuse on Day…

Chuck Faughnan III · September 4, 2026 Read →
Beyond Signatures: Credential Exploitation Beneath Log Level
Insider Threat

Beyond Signatures: Credential Exploitation Beneath Log Level

Legacy SIEMs fail when adversaries use valid credentials and native OS tools. Personam provides agentless behavioral intelligence to expose credential exploitation beneath the log level…

Chuck Faughnan III · September 1, 2026 Read →
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