In 2025, cyber threats continue to evolve with increasing sophistication, leveraging AI, automation, and geopolitical tensions. Sharing my overview of key trends:

1. AI-Powered Attacks
2. Deepfake and Social Engineering: AI-generated voice/video scams (e.g., CEO fraud, political disinformation).
3. Adaptive Malware: AI-driven malware evades detection by learning defense patterns.
4. Ransomware 2.0
5. Double and Triple Extortion: Attackers encrypt data, leak it, and disrupt operations (e.g., targeting critical infrastructure).
6. Ransomware-as-a-Service (RaaS): More affiliates using subscription-based attack tools.
7. Supply Chain and Third-Party Risks
8. Attacks on software vendors, cloud providers, and MSPs to breach multiple targets (e.g., SolarWinds-style attacks).
9. Critical Infrastructure Threats
10. OT/ICS Attacks: Energy grids, water systems, and healthcare face disruptive cyber-physical attacks.
11. State-Sponsored Sabotage: Geopolitical conflicts spill into cyberwarfare (e.g., Russia-Ukraine, China-Taiwan tensions).
12. Quantum Computing Risks
13. Harvest Now, Decrypt Later: Attackers steal encrypted data to decrypt later using quantum computers.
14. IoT and 5G Vulnerabilities
15. Exploits in smart cities, connected vehicles, and medical devices due to weak security.
16. Regulatory & Compliance Challenges
17. Stricter laws (e.g., EU’s NIS2, U.S. SEC rules) force organizations to improve cyber resilience.

It is no brainer to say that cyber threats in 2025 are more automated, destructive, and politically motivated, requiring proactive defense strategies. Organizations must prioritize AI-driven security, employee training, and supply chain resilience to mitigate risks.

How to Defend?

Technology itself has limited capabilities, no matter how good or how well-branded it is. If signature-based defense, then one day or another, there will be an attack that can’t be recognized based on its signature, if behavioral where it follows user’s routines and behaving patterns in the system, then it will be tricked, spoofed, or mislead in any way to open a gap for an attacker who intends to sneak into our system and stay there as long as required. The good news is that technology does its job well, especially when supported with AI-based tools. It rarely lets something malicious in, rather sandboxing it until being able to assign a high percentage of certainty that it will do no harm to a system.

On the other hand, there is a human factor that is causing a much bigger threat to a system, such as having inappropriate permissions or performing actions that could cause damage.

Did you ever ask yourself: “Why are humans the weakest link in cybersecurity”? There are many reasons and here are some listed: we tend to use simple passwords, easy to remember and contained in many password cracking dictionaries, we can be tricked by phishing emails, fake login pages, or deceptive phone calls, sometimes we will fail to log out of the system or we will misconfigure it, and in many cases we will be sharing our login credentials with colleagues. These are only some of the “whys”. However, one of the most important and challenging tasks for any IT system is undoubtedly confirming the digital identity of a user.

Minimizing the risk factor of a human activity, the focus of cybersecurity teams who guard our systems should be on:

1. Allowing a user to access the system and perform tasks using the lowest possible set of privileges at any given time.
2. Undoubtedly confirming the user’s identity, no matter if the user is on-premises or anywhere in the world.

Please check number two and think about it. What a challenge this is, right? It is easy when you meet a friend on the street to recognize and know immediately who this person is, but a cybersecurity system must do this within a very limited scope of checks and with an extremely low probability of failure. Not an easy one, agree?

Understanding a User’s Digital Identity

A user’s digital identity is our unique online footprint, a collection of personal data, credentials, and behavioral patterns that verify who we are across digital platforms. It goes beyond basic information like usernames or email addresses to include authentication factors such as passwords, biometric scans, or one-time codes, along with implicit identifiers like device fingerprints, browsing habits, and transaction histories.

This identity enables access to everything from social media accounts and email to banking apps and corporate systems, acting as a virtual key to the digital world. However, unlike a physical ID card, a digital identity is dynamic, constantly evolving with each login, purchase, or interaction, while leaving traces that can be analyzed for security or privacy risks.

The security of a user’s digital identity hinges on robust authentication (like multi-factor verification) and continuous monitoring to detect anomalies, such as logins from unfamiliar locations or unusual spending patterns. As cyber threats grow, technologies like AI-driven behavioral analytics and decentralized identity systems (e.g., blockchain-based IDs) are emerging to give users more control, letting them prove who they are without oversharing personal data.

Ultimately, a well-managed digital identity balances convenience with protection, ensuring users move seamlessly through online spaces while minimizing risks like impersonation, fraud, or data breaches. The future lies in solutions that prioritize both security and user privacy, empowering individuals to own and govern their digital selves.

To undoubtedly confirm the user’s digital identity and provide user access at the right time, to the right resources we usually rely on three technologies:

• IAM – Identity and Access Management
• PAM – Privileged Access Management
• Biometrics

Identity and Access Management

Identity and Access Management (IAM) is a framework of policies, technologies, and processes that ensure only the right people have access to the right resources at the right time and for the right reasons.

IAM Matters for the following benefits:

• Security – Protects sensitive data and systems from unauthorized access
• Compliance – Helps meet legal requirements (e.g., GDPR, HIPAA, NIS2)
• Efficiency – Automates user access and provisioning
• User Experience – With tools like SSO, users access many systems with one login

IAM should be a fundamental part of cybersecurity and data protection in organizations.

How IAM Works – Step-by-Step

1. Identity Creation (Provisioning)

A user (e.g., a new employee) is created in the system. Their identity profile includes:

• Username
• Role (e.g., HR Manager)
• Department
• Permissions or groups
• This process can be manual or automated via HR systems

2. Authentication (Login)

The user tries to log in. IAM verifies who they are using:

• Password
• Multi-Factor Authentication (MFA)
• Biometric verification
• Smart cards or tokens
• If the identity is verified → proceed
• If not → access denied

3. Authorization (Access Check)

Once authenticated, IAM checks what the user is allowed to access. This is based on:

• Role-Based Access Control (RBAC)
• Policies and rules (e.g., time of day, device, location)

Example: An HR manager can access payroll data, but not the source code

4. Access Granted or Denied

• If access is permitted, the user gets into the system, application, or data
• If not, the system denies access and logs the attempt

5. Ongoing Monitoring and Auditing

IAM continuously monitors user behavior. Log access attempts, successful and failed logins, changes in roles, etc. IAM is useful for:

• Security incident detection
• Compliance reports (e.g., GDPR, ISO/IEC 27001)

6. De-provisioning or Revoking Access

When a user leaves the company or changes roles:

• IAM removes or updates access rights.
• Prevents orphan accounts (active accounts without real users).

Example Scenario: John Logs into the Finance System

IAM Components Behind the Scenes

Privileged Access Management

Privileged Access Management (PAM) is a set of tools and processes designed to secure, control, and monitor access to critical systems and sensitive information by users with elevated (privileged) permissions.

Privileged users like system administrators, database admins, and network engineers have access that could cause significant damage if misused, either maliciously or accidentally. PAM helps minimize this risk.

What Does PAM Do?

PAM ensures that:

• Only authorized individuals can access privileged accounts
• Privileged access is granted only when needed, for the shortest time necessary
• All activities are monitored, logged, and auditable for accountability

Key Components of PAM

• Privileged Account Discovery – Automatically scans and identifies privileged accounts across systems, devices, and applications. Help to eliminate “shadow admin” accounts that may be unknown or forgotten.
• Credential Vault (Password Vault) – A secure, encrypted repository for storing privileged credentials. Ensures that passwords are never directly exposed to users – they are injected when needed. Also, it supports password rotation (auto-changing passwords after use or on schedule).
• Session Management – Controls and records privileged sessions (e.g., SSH, RDP) in real time. Session management allows monitoring, recording, and playback of sessions for auditing or forensic analysis.
• Just-in-Time (JIT) Access – Grants temporary access to privileged resources based on need. It significantly reduces the attack surface by limiting how long elevated access is valid.
• Least Privilege Enforcement – Ensures users get only the minimum level of access needed to perform their tasks and helps reduce misuse or exploitation of excessive privileges.
• Multi-Factor Authentication (MFA) Integration Module – Adds an extra layer of security when accessing privileged accounts by preventing unauthorized use even if credentials are compromised.
• Audit and Reporting – Keeps detailed logs of all privileged activity and provides reports for audit and compliance with regulations like NIS2, ISO/IEC 27001, HIPAA, or GDPR.
• Approval Workflows – Requires management approval before privileged access is granted. Approval workflows add accountability and control to high-risk operations.

Summary:

Implementing PAM in an organization must be considered as a core pillar of Zero Trust Architecture and identity-centric security.

IAM vs PAM – Key Differences

In many cases, people are mixing IAM and PAM Let’s see what some differences are:

IAM is like the front gate that manages who you are and what you’re allowed to do. PAM is like the vault door; it protects and controls access to the most sensitive systems. Both are essential, but PAM is a subset of IAM with a focus on managing and securing high-privilege access.

Biometrics

Biometrics in digital identity refers to using unique biological or behavioral characteristics of an individual to verify or authenticate their identity in digital systems. It offers strong, user-friendly security that is difficult to forge or steal compared to passwords or PINs.

What Are Biometrics?

Biometric identifiers can be classified into two main types:

1. Physiological Biometrics (physical traits) like:

• Fingerprint
• Facial recognition
• Iris or retina scan
• Palm veins
• DNA (rare in digital ID due to privacy and complexity)

2. Behavioral Biometrics (patterns of behavior):

• Voice recognition
• Typing rhythm
• Mouse movement

What Is the Technology Behind?

Here’s how biometric systems work in digital identity:

1. Enrollment

• A biometric scanner (camera, fingerprint reader, microphone, etc.) captures the user’s biometric trait (e.g., a fingerprint or facial image)
• The system extracts distinctive features (e.g., fingerprint ridges, facial geometry, voice pitch)
• These features are converted into a mathematical template (not a raw image)
• The template is securely stored in a database, on a device (e.g., smartphone), or in a secure hardware element (e.g., Hardware Security Module)

The biometric template is anonymized, encrypted, and cannot be reversed into the original image.

2. Authentication (Verification)

When the user tries to log in or verify their identity:

• The biometric trait is scanned again
• The system extracts features from the new sample
• The new features are compared to the stored template using an algorithm
• If the similarity score is above a certain matching threshold, access is granted

There are two matching types:

• Verification – Confirms whether the person is who they claim to be (e.g., unlocking your own phone with your fingerprint)
• Identification – Identifies a person by comparing their biometric data to many stored templates (e.g., identifying a person in a crowd)

To understand how well the biometric-based cybersecurity works, some basic matching metrics are mandatory:

• False Acceptance Rate (FAR): Rate at which unauthorized users are accepted
• False Rejection Rate (FRR): Rate at which authorized users are denied
• Equal Error Rate (EER): Point where FAR and FRR are equal – used to measure system accuracy

The advantages of Biometrics in Digital Identity:

• Hard to forge or steal
• No need to remember passwords
• Convenient and fast
• Useful in multi-factor authentication (MFA)

However, there are also some challenges and considerations to evaluate before deploying:

• Privacy Concerns: Biometric data is sensitive and permanent – if stolen, it can’t be changed like a password
• Spoofing Risks: Can be tricked by photos, recordings, or 3D masks (though anti-spoofing measures exist, but they are not 100% secure)
• False Positives/Negatives: Systems must balance accuracy with user convenience
• Regulations: Must comply with GDPR and other privacy laws when storing or processing biometric data

How IAM, PAM, and Biometrics Work in Conjunction?

IAM (Identity and Access Management), PAM (Privileged Access Management), and biometrics work together to enhance security by ensuring that only authorized users can access systems, especially sensitive or high-privilege resources. The technologies combined bring value into the process of confirming the user’s digital identity and ensuring access using the lowest possible rights to the targeted resources.

IAM (Identity and Access Management)

• Manages digital identities (users, roles, permissions)
• Uses authentication (e.g., passwords, MFA) and authorization policies

Example: Employees log in to company apps via IAM with their credentials.

PAM (Privileged Access Management)

• Secures elevated access (admin accounts, root access)
• Enforces strict controls (just-in-time access, session monitoring)

Example: IT admins request temporary access to a server via PAM.

Biometrics

• Provides strong authentication (fingerprint, facial recognition, iris scan)
• Often used as part of MFA (Multi-Factor Authentication)

Example: A user must scan their fingerprint and enter a password to access a PAM-protected system.

Integration Flow

User authenticates via IAM (e.g., username + password + biometric scan). If privileged access is needed, PAM takes over:

• Checks if the user is authorized for elevated rights
• May require additional biometric verification for sensitive actions
• Session is monitored and logged by PAM for audit trails

Pros of Combining IAM, PAM, and Biometrics

• Stronger security
• Biometrics reduce reliance on weak passwords
• PAM ensures least privilege for sensitive accounts
• Reduced insider threats
• PAM limits who can access critical systems and logs all actions
• Biometrics prevent credential sharing
• Compliance and auditability
• Meets regulations (GDPR, HIPAA, SOX) with detailed logs
• Biometrics provide non-repudiation (proof of who accessed what)
• User convenience (if well-implemented)
• Biometrics are faster than typing passwords
• PAM automates approval workflows for access requests

Cons and Challenges

• Storing biometric data raises GDPR or other legal issues if mishandled
• Unlike passwords, biometrics can’t be changed if compromised
• Implementation complexity
• Integrating IAM, PAM, and biometrics requires careful planning
• Legacy systems may not support modern authentication
• False positives or negatives in biometrics
• Facial recognition may fail under poor lighting
• False rejections can frustrate users
• Biometric scanners and PAM solutions can be expensive
• Requires ongoing updates to prevent spoofing (e.g., fake fingerprints)

What Does My Organization Need?

Finally, let’s walk through a structured decision tree to help determine whether your organization needs IAM, PAM, biometrics, or a combination based on security requirements, compliance needs, and risk profile.

Step 1: Does your organization manage user identities and access controls?

No → It’s enough to have IAM (Basic user authentication and role-based access)

Yes → Proceed to Step 2

Step 2: Does your organization have privileged accounts (admins, root access, service accounts)?

No → IAM may suffice (if no high-risk systems exist)

Yes → Proceed to Step 3

Step 3: Is your organization securing privileged access, a compliance or security priority?

No → IAM + Basic MFA (e.g., SMS/email OTP)

Yes → PAM is required for session monitoring and just-in-time access. Proceed to Step 4

Step 4: Does your organization handle sensitive data (financial, healthcare, government)?

No → IAM + PAM (without biometrics may be enough)

Yes → Proceed to Step 5

Step 5: Is password-only authentication a security risk?

No → IAM + PAM + Standard MFA (e.g., hardware tokens or SW authenticator)

Yes → Biometrics for high-assurance authentication is required

Step 6: Is your organization subject to strict compliance (GDPR, HIPAA, NIST)?

No → Optional biometrics (but recommended for PAM access)

Yes → Mandatory biometrics + IAM + PAM (for audit trails and non-repudiation)

IAM + PAM + Biometrics create a layered defense, but success depends on; proper integration (avoiding silos), balancing security with usability, ensuring biometric data is stored securely (e.g., hashed, decentralized).

Choosing the right cybersecurity solution involves balancing three critical factors:

• Cost (Budget constraints, licensing, scalability)
• Ease of Use (Deployment complexity, user experience, maintenance)
• Security Level (Threat protection, compliance, risk mitigation)

Conclusion

Bear in mind that artificial intelligence is revolutionizing cybersecurity, particularly in Identity and Access Management, Privileged Access Management, and Biometrics. AI is transforming them by introducing intelligent automation, real-time threat detection, and adaptive security measures. From behavioral biometrics to just-in-time privilege access, AI enhances protection while reducing friction for legitimate users. As cyber threats evolve, AI-driven solutions will become indispensable for maintaining robust identity and access security. Organizations that embrace these advancements will not only strengthen their defenses but also streamline compliance and operational efficiency. The future of cybersecurity lies in AI’s ability to anticipate risks and respond faster than ever before.