Context packaging is the practice of assembling the right instructions, background data, examples, and constraints for an AI tool before it acts. In AI-assisted coding, that can include repository notes, task boundaries, security rules, file snippets, and a description of what must not change. Good packaging helps the model produce relevant output instead of guessing from incomplete prompts.
In cyber security, context packaging matters because model behavior is only as safe as the context it receives. Weak packaging can lead to insecure code, overlooked edge cases, or prompt injection where malicious text inside documents or code tries to redirect the assistant. Defenders use careful context packaging to limit tool permissions, filter untrusted input, and separate system instructions from user-provided content. Attackers, meanwhile, may try to reshape the context so the model reveals secrets, skips checks, or follows harmful instructions.