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In the world of large language models (LLMs), the battle against "bad characters" is a lot more nuanced than it first appears. While early efforts focused on rooting out obvious troublemakers—like rogue control characters or malformed encodings—the real challenge now is about perception, context, and trust.
This post breaks down how the industry is evolving, why the problem is far from solved, and what it means for anyone building with or relying on LLMs today.
In Short
Modern LLMs have made huge strides in eliminating hidden or dangerous characters from their outputs. Providers like Google (Gemini), OpenAI, and Anthropic have implemented sophisticated pipelines that catch nearly all of the classic issues. But as the surface area shrinks, attackers and researchers alike are probing new frontiers: homoglyphs, visual spoofing, and context-aware attacks that exploit how humans, not just machines, interpret text.
The "bad character" problem is no longer just about code points—it's about what users actually see and trust.
Getting rid of all the "bad" or hidden characters in LLM output is a long process, not a quick one. While tools like Google's Gemini family have been able mosltly remove errors in standard tests, new attacks that trick the eye are making text security more difficult. The truth is that only a few users are actuly testing able to make sure that the code is completely free of bad characters.
Key Points
- Architecture Refinement – Advanced tokenization and multi-stage filtering pipelines dramatically reduce corruption.
- Prompt & Output Handling – Unicode normalization and context-aware validation stop most injection attempts.
- Homoglyph Threat – Visually confusable characters (e.g., Cyrillic “а” vs Latin “a”) evade naïve filters and human sight alike.
- Roadmap – 2025-2026 will see aggressive R&D on visual similarity detection and risk scoring.
What’s Next?
Stakeholders must shift focus from plain-text control characters to perceptual attacks that exploit human vision. Early adopters of homoglyph protection will command the competitive advantage.
Disclaimer: This article is for informational purposes only and does not constitute legal or security advice.