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On this page
  • Overview
  • Techniques for Generating Hypotheses
  • Defining and Prioritizing Hypotheses
  • Hypothesis Example: Financial Institution
  1. Threat Hunting
  2. Threat Hunting in Azure
  3. Threat Hunting Process

Hypothesis Generation

Overview

Hypothesis generation is the foundational stage of the threat hunting process, focusing on creating and prioritizing potential threat scenarios based on intelligence, data analysis, and security trends.

Techniques for Generating Hypotheses

  1. Threat Intelligence: Use global and industry-specific reports to identify relevant threats.

  2. Historical Data Analysis: Analyze past incidents to find patterns and recurring vulnerabilities.

  3. Security Trends: Monitor recent security developments to anticipate emerging threats.

Defining and Prioritizing Hypotheses

  • Risk Assessment: Evaluate the impact and likelihood of threats, prioritizing those with the highest risk to the organization.

  • Organizational Impact: Tailor hypotheses to address critical vulnerabilities specific to your organization's assets and operations.

Hypothesis Example: Financial Institution

Objective: Develop a realistic hypothesis for a threat scenario in a specified network environment.

Scenario Description

Environment: A financial services company with extensive trading operations, utilizing high-speed trading platforms and significant data storage for transaction records.

Hypothesis: "A malicious actor could exploit vulnerabilities in the trading platform software to manipulate market transactions, leading to financial gain and potential market destabilization."

Steps to Develop the Scenario

  1. Identify Vulnerabilities: The reliance on high-speed trading platforms, which often prioritize speed over security, creates potential entry points for attackers. Vulnerabilities might include outdated software components or insufficient input validation mechanisms.

  2. Define Threat Actors: Focus on external cybercriminals with advanced technical skills and a deep understanding of financial markets, who could exploit these vulnerabilities.

  3. Develop Attack Methods: The attack could involve injecting malicious code into the trading platform to initiate unauthorized transactions, alter trading data, or disrupt trading activities.

  4. Anticipate Actions Upon Success: Successful exploitation could lead to significant financial gains for the attacker, manipulation of market prices, and loss of confidence in the financial markets.

  5. Plan Detection and Response: Consider how anomalies in trading patterns could be detected through anomaly detection systems and what the immediate response should be, such as isolating affected systems, reversing fraudulent transactions, and notifying regulatory bodies.

Discussion Points

  • Plausibility of the Hypothesis: Evaluate the likelihood and potential methods of such an attack, considering the current security measures in place.

  • Potential Impact: Discuss the direct financial impact, along with broader market effects and reputational damage.

  • Improvements in Preparedness: Explore strengthening security measures on the trading platform, improving detection capabilities, and conducting regular security audits to mitigate risks associated with software vulnerabilities.

Last updated 9 months ago