Online Brand Protection Software

Detect coordinated smear campaigns before they reach mainstream media

Online brand protection software detects, attributes and tracks organised attacks on a company's reputation across social platforms, messengers and fringe media. Osavul's Nebula module works at the layer most tools skip: coordination. It reads 150,000+ sources in 30 languages and 100 countries, then tells you whether a spike in negative mentions is a thousand angry customers or forty accounts posting on the same schedule.

That distinction decides your response. Social listening counts mentions and scores sentiment — useful for campaign measurement, close to useless when a competitor-funded network seeds a product-safety rumour on Telegram at 3 a.m. In our tracking of narrative attacks on consumer and energy brands, the gap between first coordinated post and mainstream pickup runs 48 to 96 hours.

Nebula closes that window. Detection, coordination analysis and attribution evidence sit in one online brand protection platform your security and communications teams share.

Key Metrics

150k

data sources monitored

100

countries covered

languages analysed

24/7

narrative attack detection

Coverage of the platforms attacks actually start on

Brand attacks rarely begin where your listening tool is pointed. Nebula pulls from Telegram channels and chats, TikTok, X, YouTube, Reddit, regional forums and fringe news domains — the emerging media where a rumour incubates for days before a journalist picks it up. Our Edelman research on the TOP 100 global brands found the majority of reputational threats surfacing first on exactly these channels, outside standard monitoring

Coordination and bot detection

Coordinated inauthentic behaviour is identified by structure, not content. Nebula clusters accounts by posting cadence, shared phrasing, cross-posting graphs and creation-date patterns, then scores how likely a wave of criticism is manufactured. A dozen accounts publishing near-identical text within a four-minute window is a signature, and it looks nothing like organic backlash. Read more on how bot detection works in practice.

AI narrative clustering

Thousands of hostile posts almost always reduce to three or four narratives. Nebula's models group them, track momentum per narrative, and show which one is gaining velocity — so communications teams answer the story that is spreading rather than the loudest single post. Sentiment scores sit underneath each cluster, per language and per region.

Alerting and API access

Alerts fire on thresholds you set: mention velocity, coordination score, narrative emergence, executive-name spikes. They route into the channels your SOC and comms teams already use, and the full dataset is available programmatically for teams running their own analytics or feeding a threat-intel pipeline.

Catch the attack at hour zero, not day five

Early detection is the entire economics of brand protection. A narrative caught while it is confined to nine Telegram channels costs a few analyst hours; the same narrative caught after a national outlet runs it costs a quarter of crisis budget and a permanent search result. Nebula watches velocity, not volume — a small absolute number of posts growing at an abnormal rate triggers the alert long before raw mention counts move. That is the difference between a correction and a campaign.

Separate real criticism from manufactured outrage

Responding to a botnet as though it were genuine consumer anger is one of the more expensive mistakes we see. Public apologies validate the narrative and hand the operators a headline. The reverse error is worse: dismissing a real product complaint as a smear because the volume looked suspicious. Nebula gives you the coordination score and the account network behind every wave, so the call is evidence-based. The threats brands miss on social media are usually the ones nobody classified correctly.

Executive and asset impersonation monitoring

Impersonation has moved from clumsy fake accounts to synthetic video of named executives promoting investment schemes. Nebula tracks executive names, product names, ticker symbols and support-channel spoofs across the same 150,000 sources, flagging new assets as they appear. Deepfake CEO clips typically launch on a messenger, run paid amplification for 24 hours, then vanish — which is why detection has to sit on Telegram monitoring rather than on takedown requests to a mainstream platform.

Evidence your board and regulators will accept

Attribution is worth nothing if you cannot show your work. Nebula exports the underlying dataset behind every finding: source list, timestamps, network graph, narrative timeline, amplification path. The same methodology sits behind our work with NATO StratCom COE on the Virtual Manipulation Brief, and it holds up when a board, an insurer or a regulator asks how you concluded the campaign was coordinated.

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Online Brand Protection Software

Detect coordinated smear campaigns before they reach mainstream media

Key Metrics