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The Disinformation Dilemma: How Falsehoods Undermine Open Source Intelligence (OSINT) in the Digital Age

The Disinformation Dilemma: How Falsehoods Undermine Open Source Intelligence (OSINT) in the Digital Age

Evarist Chahali's avatar
Evarist Chahali
Jun 18, 2025
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The Disinformation Dilemma: How Falsehoods Undermine Open Source Intelligence (OSINT) in the Digital Age
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Ujasusi Blog’s OSINT Desk | 18 June 2025 | 0215 BST


The Rise of OSINT and the Age of Digital Deception

Open Source Intelligence (OSINT) has emerged as a powerful tool for intelligence agencies, private security firms, journalists, and researchers. With the vast amount of publicly available data on the internet, OSINT provides timely, cost-effective, and actionable insights. However, the very openness that empowers OSINT also renders it uniquely vulnerable. Among its most significant adversaries is disinformation—the deliberate spread of false information designed to mislead and manipulate.

In a world where state and non-state actors actively engage in information warfare, disinformation has become both a strategic asset and a tactical weapon. As the digital information ecosystem expands, so too do the threats to its integrity. For OSINT practitioners, separating signal from noise has never been more critical—or more difficult.

Understanding the OSINT Workflow: Collection, Processing, Analysis, and Reporting

Before examining the impact of disinformation, it is essential to understand how OSINT works. The standard OSINT workflow typically includes the following phases:

  1. Collection – Gathering data from open sources such as news outlets, blogs, social media, satellite imagery, government databases, and forums.

  2. Processing – Converting raw data into a usable format by filtering, structuring, and storing it.

  3. Analysis – Interpreting the processed data to derive meaningful intelligence.

  4. Reporting – Presenting findings in a format suitable for decision-making by stakeholders.

Disinformation can poison each of these stages, introducing contaminated data, misleading narratives, or false conclusions.

Disinformation vs. Misinformation: Definitions and Impact

Although the terms are often used interchangeably, understanding the distinction between misinformation and disinformation is vital:

  • Misinformation: False information spread unintentionally, often by individuals unaware that the data is inaccurate.

  • Disinformation: False information shared deliberately, usually with malicious intent to deceive, confuse, or manipulate.

In the OSINT context, disinformation is the more pernicious threat because it is often designed specifically to exploit open-source tools and methodologies. Misinformation can be corrected through proper vetting, but disinformation, especially when part of coordinated campaigns, is more resistant to exposure.

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