Imagine a world where everything you read, see, and hear online could be a lie. A world where fake accounts, computer-generated media, and carefully crafted stories twist what’s real, making it nearly impossible to know who or what to trust. This isn’t science fiction; it’s the challenge that global businesses and governments face every single day with online misinformation. It’s a problem so pervasive that it can sway elections, tank company reputations, and even incite real-world violence. But how do we cut through the noise and find the truth in this digital jungle? That’s where people like Dan Brahmy and his company, Cyabra, come in. Dan shared his insights with Digital Journal, offering a peek behind the curtain at how they’re fighting back against the tide of digital deceit.
Dan Brahmy, a man who has spent years immersed in the digital world, co-founded Cyabra in 2018. Before that, he sharpened his skills at heavyweights like Deloitte Digital and Google, getting a front-row seat to how quickly online stories can spiral and impact everything from business outcomes to public opinion. He saw a gaping hole: organizations simply weren’t equipped to truly understand the digital landscape. Cyabra was born from this realization, built on the idea of bringing solid, transparent, and evidence-based analysis to online conversations. Think of them as digital detectives, but instead of solving crimes, they’re uncovering who’s real, who’s fake, and who’s pulling the strings online. Their goal is to provide a clear picture of what’s happening so that businesses, governments, and other institutions can make smart decisions when online activity starts to have real-world consequences. It’s so vital that Cyabra is now a publicly traded company on Nasdaq, a testament to the growing importance of their mission.
So, how do these digital detectives work their magic? Cyabra uses what Dan calls an “authenticity model,” which acts like a highly sophisticated radar, picking up on hidden signals that reveal coordination and manipulation. They’ve spent eight years analyzing public data, understanding the subtle cues that indicate whether online activity is genuine or orchestrated. This isn’t just about spotting individual fake profiles; it’s about seeing how entire networks of accounts, both real and fake, move together. Cyabra scrutinizes the “ABCs” of online discourse: Actors, Behavior, and Content. “Actors” refers to the authenticity of the profiles themselves – are they real people or bots? “Behavior” examines their actions: how often they post, with whom they interact, and whether their content is original or copied. Finally, “Content” delves into the narratives being spread, checking for things like AI-generated images, deepfakes, or other manipulated media. By combining these three crucial elements, Cyabra can distinguish between a genuine surge of public opinion and a carefully orchestrated campaign designed to mislead. It’s about seeing the forest for the trees, understanding not just what’s being said, but who’s saying it and why.
This approach sets Cyabra apart from typical social listening tools or cybersecurity solutions. Imagine social listening tools as a giant ear, hearing every whisper and shout online, and cybersecurity tools as a fortress, protecting networks from direct attacks. Cyabra operates in a different dimension. They don’t just tell you what people are saying or if your network is secure; they tell you if the people talking are real and if their opinions are genuinely their own, or if they’re part of a coordinated effort to influence. As Dan explains, other social listening companies often partner with Cyabra because they answer entirely different questions. While social listening might tell you the general mood or popular trends, Cyabra digs deeper, determining the validity and coordination behind that discourse. Two seemingly identical conversations, with the same volume and sentiment, could be vastly different: one organic, driven by real people, and the other a smokescreen, fueled by coordinated networks. Cyabra provides the crucial insights to tell the difference, empowering organizations to react based on facts, not just noise.
The reason disinformation security has become such a hot topic for businesses and governments today boils down to two critical factors: the rise of accessible AI and the increasingly tangible impact of digital narratives. AI has made it incredibly easy and cheap for anyone to create convincing fake accounts and generate believable, albeit false, narratives. This means manipulation can happen faster, on a larger scale, and is much harder to detect with traditional methods. At the same time, what happens online no longer stays online. A fabricated rumor can cripple a brand’s reputation, erode investor confidence, or even spark social unrest. Organizations are realizing that disinformation isn’t just a PR headache; it’s a significant enterprise risk with real financial and strategic consequences. Because of this, it’s no longer enough to simply monitor for mentions; institutions need a rigorous, evidence-based way to understand what’s organic, what’s coordinated, and when they absolutely must respond.
So, what should a company do if it suddenly finds itself under siege by a large-scale manipulation campaign? Dan’s advice is clear: don’t panic, get clarity first. A sudden spike in online activity doesn’t automatically demand an immediate response. Acting rashly, without fully understanding the situation, can accidentally amplify the very problem you’re trying to solve. The crucial first step is to use tools like Cyabra to assess whether the activity is organic or orchestrated, to understand how the false narratives are spreading, and to determine if the scale of coordination poses a genuine threat to public perception or crucial decision-making. Historically, detecting these issues sometimes led to paralysis. Cyabra, however, has evolved to include an “operational layer” that provides recommended actions directly tied to the evidence they uncover. This shift allows companies to move beyond simply reacting to every bit of noise and instead make proportionate, evidence-based decisions that align with the actual level of risk, rather than getting swept up in the artificial storm. It’s about taking control, not just being controlled by the chaos.