Prompt Obfuscation

Prompt obfuscation is a tactic used to disguise the true intent of a prompt submitted to a language model. Attackers encode or modify prompts in ways that bypass safety filters or content moderation systems—tricking the model into generating disallowed or harmful responses.

Common obfuscation techniques include:

• Leetspeak or character substitution (e.g., “k1ll” instead of “kill”).
• Spacing and punctuation tricks (e.g., “.k i l l.”).
• Encoding with symbols or emojis.
• Layered prompts that unfold malicious instructions over multiple inputs.
• Embedding attacks where harmful content is hidden in file metadata or vector embeddings.

Prompt obfuscation is used in:

• Jailbreaking attacks on chatbots and virtual assistants.
• Circumventing keyword-based filters in AI content platforms.
• Triggering specific behavior in agentic or multi-tool systems.

This tactic undermines trust in AI safety systems, especially in public or customer-facing applications. It can also serve as a precursor to prompt injection or system leakage attacks.

Mitigating prompt obfuscation requires:

• Pattern and context-based filtering, not just keyword detection.
• Prompt normalization and decoding pipelines.
• Real-time behavioral analysis of outputs.
• Continuous updating of threat models and detection signatures.

How PointGuard AI Addresses This:
PointGuard AI detects prompt obfuscation in real time by analyzing input patterns and comparing outputs against policy expectations. It blocks obfuscated prompts before they reach the model or can trigger risky responses—ensuring content filters and behavior policies remain enforceable even against evasive attacks.

Resources:

OWASP LLM01:2025 Prompt Injection

MITRE ATRLAS