Early Fraud Detection

Early fraud detection is a cybersecurity strategy that aims to identify and stop fraudulent activity at the earliest possible stage, often before it can be completed. It's a proactive approach that uses a combination of technology and data analysis to spot suspicious behavior and anomalies in real-time.

Key Components

• Real-time Monitoring: Early detection systems continuously monitor digital channels like transactions, account logins, and network traffic. This allows them to flag potential fraud as it's happening, enabling an immediate response.

• Data Analysis: The process involves analyzing vast amounts of data, including user behavior, device information, and transaction records. By creating a baseline of "normal" behavior, the system can identify deviations that might indicate fraud.

• Machine Learning and AI: Advanced systems utilize machine learning and AI algorithms to analyze data and identify patterns or anomalies that human analysts might overlook. These models can continuously learn from new data, helping them adapt to evolving fraud tactics.

• Risk Scoring: Instead of a simple pass/fail, these systems often assign a risk score to a transaction or activity, indicating the likelihood of it being fraudulent. A high score may trigger an automated block or a request for additional verification, such as multi-factor authentication.

Early fraud detection is a critical component of a comprehensive cybersecurity framework. It helps organizations and individuals minimize financial losses, protect sensitive data, and maintain customer trust by catching fraud before it escalates.

ThreatNG aids in early fraud detection by focusing on the external, publicly accessible digital assets of an organization to identify vulnerabilities and threats before they can be exploited. By providing a continuous, attacker-centric view, it helps organizations find and fix issues that could lead to fraud.

External Discovery and Assessment

ThreatNG's ability to perform external discovery without requiring internal access or connectors enables it to identify an organization's digital assets that could be exploited for fraud. This is the first step in early fraud detection, as it identifies the attack surface that a fraudster would target.

The platform's detailed assessments are crucial for early detection:

• BEC & Phishing Susceptibility: This score is a key indicator of fraud risk. It is derived from Domain Intelligence (including Domain Name Permutations), Email Intelligence, and Dark Web Presence. For example, ThreatNG can detect a newly registered look-alike domain such as mycomany-support.com (a misspelling of mycompany-support.com) and flag it as a potential phishing site, enabling an organization to take action before a scam is launched.

• Mobile App Exposure: This assessment aids in early detection by evaluating an organization's mobile apps across various marketplaces to identify exposed sensitive data. For instance, if an AWS Access Key ID is found in an app, it serves as an early warning that a fraudster could potentially gain unauthorized access to cloud services to commit fraud.

• Data Leak Susceptibility: By checking for compromised credentials on the dark web, ThreatNG can identify potential fraud risks early. This allows a company to force password resets and prevent account takeover fraud before it happens.

• Breach & Ransomware Susceptibility: This assessment, derived from exposed sensitive ports, private IPs, and known vulnerabilities, as well as ransomware gang activity on the dark web, provides an early warning of an organization's susceptibility to these types of attacks.

Reporting and Continuous Monitoring

ThreatNG offers various reports that facilitate early detection. These reports provide risk levels and recommendations for mitigation, enabling security teams to prioritize and effectively respond to threats. For example, a report might highlight a high-risk phishing domain, helping the team to focus on taking it down immediately.

Continuous monitoring is a core component of ThreatNG's early fraud detection capabilities. It constantly watches for new threats and changes in an organization's external attack surface, ensuring that new vulnerabilities or fraudulent domains are detected as they emerge.

Investigation Modules

The investigation modules provide the deep analysis needed to detect fraud early.

• Domain Intelligence: This module is a primary tool for early detection. It identifies domain name permutations, which are variations of a company's domain name, often registered by scammers for phishing and brand impersonation purposes. ThreatNG can uncover a domain like mycompany-login.com, which could be a fake login page, and flag it for a security team to investigate and take down.

• Sensitive Code Exposure: This module scans public code repositories to identify and flag exposed sensitive data, such as API keys and access tokens. For example, discovering a leaked Stripe API Key is an early warning of a potential financial fraud risk, allowing a company to revoke the key before a fraudster can use it.

• Dark Web Presence: This module monitors the dark web for mentions of the organization and associated compromised credentials. This provides an early warning that a credential-stuffing or account-takeover attack is imminent.

Intelligence Repositories

ThreatNG's DarCache repositories provide the foundational intelligence for early fraud detection.

• DarCache Rupture (Compromised Credentials): This repository of compromised credentials helps an organization proactively detect fraud by allowing it to identify exposed employee and customer login details. By checking this data, an organization can force password resets before the credentials are used in a fraudulent act.

• DarCache Vulnerability: This repository provides information on vulnerabilities and their real-world exploitability, including data from EPSS (which estimates the likelihood of exploitation) and KEV (which tracks actively exploited vulnerabilities). This helps an organization focus its resources on patching the most critical vulnerabilities that could be exploited for fraud.

Complementary Solutions

ThreatNG can work with complementary solutions to create a more comprehensive early fraud detection system. For instance, ThreatNG’s Dark Web Presence module can identify compromised credentials, and this intelligence can be fed into a Security Information and Event Management (SIEM) system. The SIEM can then correlate this information with internal login attempts and other network data to detect a potential account takeover in real-time. This enables an automated or rapid manual response before any fraudulent activity is initiated.

Another example is ThreatNG's Domain Intelligence module, which identifies a new phishing domain. This information could be sent to a Security Orchestration, Automation, and Response (SOAR) platform. The SOAR platform could then automatically trigger a playbook to send a takedown request to the domain registrar, effectively stopping the scam before it can reach its targets.