When a cybersecurity analyst searches an underground forum for the words "credit card" or "bank account," he may find nothing—not because the threats don't exist, but because criminals have long since written 💳 and 🏦. This is exactly what researchers at Flashpoint documented in a new report on the language of illegal online communities.

What's happening on underground platforms

The activity of cybercriminals is increasingly concentrated on fast, informal platforms—Telegram, Discord, and closed forums. There, speed and brevity matter more than traditional secrecy. Emojis allow participants to instantly scan messages, understand the essence, and respond without lengthy text explanations.

According to Flashpoint, symbols substitute key concepts related to fraud, financial transactions, and specific platforms or services. For example, 💳 instead of "credit card," 🏦 instead of "bank." Standard filters configured to search for text triggers simply don't "see" these symbols.

"The replacement of words with emojis combined with slang, abbreviations, and multilingual phrases creates a multi-layered form of obfuscation that complicates large-scale monitoring."

Flashpoint, report "The Language of Emojis in Threat Intelligence"

Two dimensions of one scheme

Researchers identify two parallel vectors of emoji use in the criminal environment:

• Bypassing automated moderation. Security systems oriented toward ASCII text and keywords do not recognize Unicode symbols as a threat. This applies to both platform filters and corporate threat monitoring solutions.
• International coordination. As Flashpoint notes, not all participants in illegal communities speak English well. Emojis function as a borderless language—allowing participants from different countries to quickly convey meaning without translation.

Deeper than word substitution

A separate level is so-called emoji smuggling. This is a more technical attack: malicious actors embed malicious code or commands within Unicode sequences that accompany emojis. The result looks like an ordinary symbol but carries hidden payload.

Researchers at Mindgard and FireTail found that such techniques—encoding through emojis and zero-width characters—allow bypassing protective filters of large language models with success rates approaching 100%. This means: even AI systems that corporations rely on for content filtering are vulnerable.

Additionally, according to Flashpoint, criminals use consistent patterns in choosing emojis—this allows analysts to identify specific actors over time, even if they change nicknames. The signature in symbols is more persistent than they themselves believe.

The blind spot in defense

The problem is not just with large corporations. Cybersecurity solutions for small and medium businesses—antivirus software, email filters, intrusion detection systems—were designed for known threats in text form. For emoji smuggling, attack signatures simply don't exist yet. Protection is looking in the wrong place.

Flashpoint recommends analysts transition to Unicode-aware search: their platform already allows searching for emojis alongside keywords to capture conversations that would otherwise remain invisible.

The question is different: if criminals have already developed stable "emoji dictionaries" for specific communities, will monitoring systems be able to keep up with their evolution—or does each new wave of slang reset the count to zero?