AI-Driven Threat
Protection

Mentis: Agile AI defense with strategic analytics and robust threat intelligence

Mentis Platform: Understanding the Logic Behind AI

Mentis, our dedicated AI-Driven threat protection module, is at the heart of our advanced cybersecurity approach. Powered by UEBA, deception techniques and integration with and CTI (Cyber Threat Intelligence) data ,Mentis excels in detecting and analyzing security events.

Mentis goes beyond conventional threat detection by assessing the incidents compatibility to cyberattack cycles. Leveraging artificial intelligence, it evaluates user behavior and assigns threat and accuracy scores ranging from low to critical . This categorization aids in swift threat prioritization, enabling proactive security measures

The Preference for Identity Theft: Why Hackers Choose This Path

Identity theft is not only a prevalent issue but also a growing menace in today’s interconnected world. As time progresses, the allure of this cybercrime multiplies, making it the preferred choice for malicious actors.

Password Reuse

The reality is that many individuals use the same or very similar passwords across multiple accounts. When one platform gets compromised, the risk cascades, leaving other accounts equally vulnerable. Hackers understand this and exploit the domino effect, capitalizing on the lax security practices of users.

Browser-Stored Passwords

Another prime target for hackers is the treasure trove of credentials stored in web browsers. Many users allow their browsers to save passwords for convenience. However, if a hacker gains access to your system, they can easily pilfer this information, potentially granting them entry to various accounts without raising immediate suspicion.

Blurred Footprints

Hijacking a user’s account offers cybercriminals a significant advantage. Once they’ve gained access, tracking their activities or distinguishing their actions from the legitimate user’s becomes challenging. This obscurity aids hackers in remaining undetected while conducting malicious operations, including data breaches and financial fraud.

The Imperative of AI-Powered MFA Against Such Attacks

In the face of escalating identity theft and other cyberattacks, the need for AI-powered Multi-Factor Authentication (MFA) has never been more critical.

AI-powered MFA systems have the capacity to adapt and learn. They continuously monitor user behavior, detecting anomalies and suspicious activities that might go unnoticed with traditional MFA. By leveraging machine learning, these systems can swiftly respond to emerging threats, providing real-time protection.

AI-driven MFA can perform dynamic risk assessments, evaluating a user’s risk profile in real-time. It takes into account multiple factors, including user behavior, location, and the device being used, and assigns a risk score accordingly. This dynamic approach ensures that high-risk activities are promptly flagged.

AI-based MFA understands the context of each authentication request. For instance, it recognizes whether a user typically logs in from a particular location or device. If a login request deviates from the user’s normal behavior, the system can trigger additional authentication steps, adding an extra layer of security where it’s needed most.

AI-powered MFA can integrate with threat intelligence sources, enriching its analysis with up-to-date information about emerging threats. This proactive approach enables the system to respond to evolving attack vectors effectively.

By differentiating between legitimate user behavior and potential threats, AI-powered MFA systems minimize false positives. Users can enjoy seamless authentication while remaining protected from unauthorized access attempts.

Mirket Mentis Platform’s integration with MITRE D3FEND and MITRE ATT&CK is a testament to our commitment to robust cybersecurity. This synergy equips us to address and preempt threats comprehensively, adapt to evolving tactics, and fine-tune our defense mechanisms for maximum protection.

Early Detection: A Cornerstone of AI-Powered Threat Protection

In the ever-evolving cybersecurity landscape, early detection is the cornerstone of effective defence against various sophisticated threats. AI-powered Threat Protection stands at the forefront of this paradigm, offering a proactive stance against cyberattacks.

Threats Evolve, So Should Our Defense

Cyber threats are continually mutating and adapting. New tactics and techniques emerge regularly, making it imperative that our security measures evolve in tandem. Early detection mechanisms, enabled by AI, can anticipate these mutations and respond before damage is done.

Recognizing Anomalies

AI-driven MFA excels at recognizing anomalies and patterns that deviate from the norm. Whether it's an unusual login time, an uncharacteristic access location, or a change in device, AI is finely tuned to detect these deviations. Early detection ensures that these outliers are flagged, and potential threats are identified.

Real-Time Response

Traditional MFA often relies on static authentication methods. In contrast, AI-powered MFA operates in real-time, making it more responsive to changes in user behavior. If a user's actions indicate a security concern, the system can trigger additional authentication steps, thwarting potential threats before they escalate.

Proactive Threat Mitigation

The early detection capabilities of AI-powered MFA enable proactive threat mitigation. By identifying threats at their nascent stages, the system can take swift action to contain and neutralize them. This proactive approach can mean the difference between a minor incident and a significant breach.

Minimizing Damage

Early detection goes hand in hand with damage limitation. Identifying threats in their infancy allows for containment, reducing the potential harm to the organization. This is particularly critical in mitigating the financial, reputational, and operational risks associated with security incidents.

Precision Threat Scoring

Precision Scoring for Threat Relevance refines AI Threat Protection by assigning key scores for threat level and accuracy, boosting the system's response to critical threats and account takeover risks.

Step 1

Phishing Attempts: Unauthorized attempts to steal user credentials using disguised communication.
Brute Force: Continuous attempts to gain access by trying multiple password combinations.
Session Hijacking: Unauthorized interception of user session tokens.
Credential Stuffing: Attackers use previously breached username-password pairs to gain unauthorized access.
Compromised Credentials: Use of stolen or leaked credentials to attempt unauthorized access.
Man-in-the-Middle (MitM) Attacks: Attackers secretly intercept and possibly alter the communication between two parties.
API Security Breach: Exploiting vulnerabilities in application programming interfaces to gain unauthorized access.

Step 2

Login Pages: The main entry point for user authentication.
Admin Login: High-level access point that can provide attackers with administrative privileges if breached.
Password Reset Flows: An often-targeted area for account takeover.
Single Sign-On (SSO) Interfaces: Unified access points which, if breached, can give attackers widespread access.
API Endpoints: External and internal interfaces that provide data access and can be exploited if not properly secured.
Two-Factor Authentication (2FA) Systems: While designed for added security, if compromised or improperly implemented, they can be a vector for account breaches.
Business Transactions: Sensitive processes that involve data exchange or financial actions, which can be targeted for interception or fraud.

Step 3

AI Analysis: Utilizes machine learning to detect abnormal behaviors and activities.
CTI Integration: Gathers data from Cyber Threat Intelligence to identify known threats.
Deception Techniques: Our platform’s deception feature denies specific login attempts but checks first logins to expose compromised credentials.
Behavioral Analytics: Monitors and evaluates user activities against historical data to identify deviations, potentially indicating malicious actions.
Heuristic Analysis: Uses predefined algorithms to analyze patterns and sequences, detecting threats that deviate from the norm without relying on signatures.
Botnet Detection: Identifies patterns of command and control (C2) communication, as well as the simultaneous actions of multiple compromised devices, indicative of botnet activities.

Step 4

Info: General user activities with no perceived threat.
Low: Slight deviations from typical behavior, but not immediate threats.
Medium: Activities that slightly resemble known attack patterns.
High: High resemblance to attack patterns, requires immediate attention.
Critical: Direct threats and active attack attempts, necessitating urgent action.

Results

Safe: The activity is categorized as normal.
Suspicious: The activity deviates from the norm but doesn’t represent a direct threat.
Threat Detected: AI and CTI have identified a potential threat based on the analysis.
Immediate Action Required: High or critical threats that need to be addressed immediately.
Deception Detected: Suspicious activities matched with deception techniques, indicating potential deceptive traps being triggered.
Mitigated: Active threats have been successfully neutralized or countered, ensuring system safety.

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AI-Driven ThreatProtection

Mentis: Agile AI defense with strategic analytics and robust threat intelligence

Mentis Platform: Understanding the Logic Behind AI

The Preference for Identity Theft: Why Hackers Choose This Path

Password Reuse

Browser-Stored Passwords

Blurred Footprints

The Imperative of AI-Powered MFA Against Such Attacks

Early Detection: A Cornerstone of AI-Powered Threat Protection

Threats Evolve, So Should Our Defense

Recognizing Anomalies

Real-Time Response

Proactive Threat Mitigation

Minimizing Damage

Precision Threat Scoring

Step 1

Products

Why Mirket

Solutions

By Industry

Platforms

Partners

AI-Driven Threat
Protection