The Internal Threat Is Greater Than You Think
External hackers represent only part of the threat landscape. Security statistics indicate that insider threats — the actions of employees, contractors, and partners with system access — account for more than half of costly incidents. Some of these are deliberate actions by disloyal employees. The majority are mistakes — someone sent a file to the wrong mailbox, copied data to a personal drive, or clicked a phishing link from an account with broad privileges.
In both cases, the consequences can be catastrophic: loss of customer data, GDPR violations, financial penalties, reputational damage, and legal proceedings. PAM (Privileged Access Management) and DLP (Data Loss Prevention) are the technological answers to these threats.
PAM — Control Over Privileged Accounts
Privileged accounts — system administrators, DBAs, DevOps engineers, service accounts — have access to everything. Compromising such an account means compromising the entire environment. PAM implements the principle of least privilege and full control over every privileged session.
Key PAM mechanisms include:
- Password Vault — passwords for privileged accounts are stored in an encrypted vault. Users never know the actual password — the system rotates it automatically after every session.
- Session Recording — every privileged session is recorded (video and keystrokes). In the event of an incident, you have a complete record of what was done, when, and by whom.
- Just-in-Time Access — privileges are granted for the duration of a specific task and automatically revoked upon completion. No one walks around with permanent production access.
- Multi-Factor Authentication — every login to a privileged account requires MFA, without exception.
DLP — Protecting Data from Leakage
Data Loss Prevention is a system that monitors data flow within the organization and blocks unauthorized transfer of confidential information. DLP operates at three levels:
- Data in Use — monitoring user actions on workstations: clipboard copying, print attempts, screenshots, file transfers to unauthorized applications.
- Data in Motion — network traffic inspection: email, HTTP, FTP, cloud. The system recognizes patterns of confidential data (national ID numbers, payment card data, NDA clauses) and blocks or warns.
- Data at Rest — scanning drives and repositories for confidential data stored outside authorized locations.
UEBA — Behavioral Anomaly Detection
User and Entity Behavior Analytics (UEBA) is the AI layer on top of PAM and DLP. The system builds a baseline of normal behavior for every user — when they log in, which systems they access, how much data they process, from where. When deviations from the norm appear — a login at 3 AM, mass data downloads, access from an unknown country — the system generates an alert and can automatically block the session pending verification.
UEBA detects attacks that bypassed perimeter systems. A stolen password is only half the battle for an attacker — if their behavior deviates from that of the legitimate user, UEBA will identify the threat.
Implementing PAM/DLP in Compliance with NIS2 and GDPR
The NIS2 Directive and GDPR require organizations to implement appropriate technical and organizational data protection measures. PAM and DLP are recognized as industry standards in this regard. Properly implemented, they significantly reduce the risk of breach and serve as evidence of due diligence in the event of an incident. ESKOM.AI implements PAM and DLP with complete security policy documentation, employee training, and regular compliance audits.