prompt-injection
Prompt Injection
📂 ai-red-teaming
AI RED TEAMING TECHNIQUES#
Prompt Injection
Techniques to manipulate AI responses through malicious prompts
Available Techniques#
Basic Prompt Injection#
Fundamental techniques to inject malicious instructions into AI prompts to bypass intended behavior.
KEY FEATURES
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• Simple instruction override
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• Context manipulation
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• Role confusion attacks
PRIMARY DEFENSES
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• Input sanitization and validation
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• Prompt template isolation
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• Context boundaries enforcement
KEY RISKS
Indirect Prompt Injection#
Advanced technique where malicious instructions are embedded in external content that the AI processes.
KEY FEATURES
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• Hidden instruction embedding
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• Content-based manipulation
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• Cross-context attacks
PRIMARY DEFENSES
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• Content preprocessing and sanitization
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• Source validation and verification
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• Context isolation mechanisms
KEY RISKS
Many-Shot Jailbreaking#
Advanced technique using large number of harmful question-answer pairs to gradually shift model behavior through in-context learning.
KEY FEATURES
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• In-context learning exploitation
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• Gradual behavior modification
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• 128+ shot examples
PRIMARY DEFENSES
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• Context window limitations
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• Few-shot example filtering
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• Constitutional AI training
KEY RISKS
Indirect Prompt Injection via External Content#
Embedding malicious instructions in external content that AI systems process, causing unintended behaviors when the content is ingested.
KEY FEATURES
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• Hidden instruction embedding
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• Cross-system contamination
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• Persistent attack vectors
PRIMARY DEFENSES
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• Content preprocessing and sanitization
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• Instruction filtering from external sources
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• Context isolation between user and external content
KEY RISKS
Copy-Paste Injection Attack#
Embedding hidden malicious prompts in copyable text that execute when pasted into AI systems, exploiting user trust in copied content.
KEY FEATURES
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• Hidden instruction embedding
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• Clipboard exploitation
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• User behavior manipulation
PRIMARY DEFENSES
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• Unicode normalization and filtering
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• Character set validation
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• Hidden content detection
KEY RISKS
System Prompt Leakage Attacks#
Techniques to extract hidden system prompts, instructions, and configuration details from AI systems.
KEY FEATURES
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• System instruction extraction
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• Configuration revelation
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• Hidden prompt discovery
PRIMARY DEFENSES
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• System prompt isolation techniques
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• Instruction filtering and detection
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• Response content filtering
KEY RISKS
Policy Puppetry Configuration Attack#
Formatting prompts as configuration files (XML, JSON, INI) to bypass content policies by disguising harmful requests as system configurations.
KEY FEATURES
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• Configuration file mimicry
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• Policy circumvention
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• Format-based deception
PRIMARY DEFENSES
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• Configuration format detection and blocking
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• Structured input validation
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• Content-agnostic policy enforcement
KEY RISKS
ASCII Art Injection Attack#
Using ASCII art and visual text manipulation to bypass AI content filters that may not properly parse visual or artistic text representations.
KEY FEATURES
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• Visual obfuscation techniques
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• ASCII art exploitation
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• Character pattern manipulation
PRIMARY DEFENSES
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• ASCII art pattern recognition
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• Character sequence normalization
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• Visual text parsing and analysis
KEY RISKS
Ethical Guidelines for Prompt Injection#
When working with prompt injection techniques, always follow these ethical guidelines:
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• Only test on systems you own or have explicit written permission to test
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• Focus on building better defenses, not conducting attacks
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• Follow responsible disclosure practices for any vulnerabilities found
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• Document and report findings to improve security for everyone
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• Consider the potential impact on users and society
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• Ensure compliance with all applicable laws and regulations
FROM THE ENGINEER BEHIND THIS CATALOG
Get your agent system red-teamed#
The attacks documented here work on production agent systems every day. Have yours tested before someone else does: prompt injection, jailbreaks, tool misuse and data exfiltration, with every finding written up next to its fix.
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