OSINT or OSINF?

Open-source intelligence (OSINT) is increasingly looking like open-source information (OSINF). The difference? OSINT should be analysed intelligence, but the industry is becoming obsessed with collection—and it’s leading to unintended consequences.

The Rise of OSINT Tool Fetishisation

Tools have revolutionised collection, enabling faster and broader data gathering. But instead of freeing up time for deeper analysis, we’ve become locked in a race against the sheer velocity of digital data. The more we collect, the less time we have to evaluate it properly. Social media has only amplified this, making disinformation, misinformation, and malinformation (yes, they’re different) harder to distinguish.

Commercial OSINT platforms are becoming increasingly dominant. While they provide incredible efficiencies, they also create financial barriers for smaller teams. The cost of access, often driven by licensing and API restrictions; risks sidelining independent researchers and investigative journalists who have been instrumental in holding power to account.

The Analysis Deficit

The real power of OSINT isn’t just in collection but in evaluation. Disinformation thrives in environments where speed is prioritised over scrutiny.

Steve Bannon, former chief strategist for President Donald Trump and ex-executive chairman of Breitbart News, articulated a media strategy aimed at undermining traditional outlets. In an interview with journalist Michael Lewis in 2018, Bannon stated: "The Democrats don't matter. The real opposition is the media. And the way to deal with them is to flood the zone with shit."

This approach involves overwhelming the information landscape with a barrage of misleading or false information, creating confusion and making it challenging for the public to discern truth from falsehood. The tactic has been linked to the spread of misinformation and the erosion of public trust in media institutions.

Bannon's strategy has influenced various political and media operations, contributing to a media environment where sensationalism and misinformation can thrive. We need to be better at tackling this tactic.

So should OSINT tools be embedding evaluation matrices into workflows?

Or do we focus on prebunking (proactively countering false narratives before they spread) has shown to be more effective than debunking, yet few tools focus on this.

The Remote Working Factor

Remote work has changed how teams collaborate. Analysis benefits from shared scrutiny, discussing findings, testing hypotheses, and even arguing over a whiteboard. Without these interactions, are we losing something fundamental in intelligence work? Dissemination has become a race in a world of breaking news and billable hours, but are we sacrificing depth for speed?

The Future of OSINT

Instead of chasing the next OSINT tool, should we focus more on teaching analytical techniques? If automated efficiencies aren’t giving analysts more time to think, then what’s the point?

So how do we reintroduce deep analysis into OSINT workflows?

Should OSINT tools include built-in critical evaluation features?