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The hijack stage is where the attack becomes active. Malicious inputs, successfully placed in the poison stage, are ingested by the model, hijacking its output to serve attacker objectives. Common hijack patterns include: Attacker-controlled tool use: Forcing the model to call specific tools with attacker-defined parameters. Data exfiltration: Encoding sensitive data from the model’s context into outputs (e.g., URLs, CSS, file writes). Misinformation generation: Crafting responses that are deliberately false or misleading. Context-specific payloads: Triggering malicious behavior only in tar

Agent customization techniques span from simple prompt changes to advanced techniques like reinforcement learning (RL), each with tradeoffs in cost, complexity, and capability. The best approach depends on whether you need better information, instructions, or fundamentally more reliable behavior. The following sections cover the main approaches.