Common File Formats Like JSON, CSV, and YAML Pose Prompt Injection Risks for AI Agents

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Security researchers and published CVEs from 2025 have confirmed that standard data formats such as JSON, CSV, and YAML offer no protection against prompt injection attacks targeting AI coding agents. Because large language models process decoded string values rather than raw format structures, malicious instructions embedded in data fields are indistinguishable from legitimate content. Tools including GitHub Copilot, Cursor, and Microsoft 365 Copilot have been found vulnerable, with the AIShellJack framework reporting attack success rates of 41–84% against models like GPT-4o and Claude 3.5 via config file injection. YAML's multiline string support presents an additional risk, as embedded newlines can create false system-message boundaries within the LLM context. Detection rules for structured data injection have been adopted by Microsoft AGT, Cisco AI Defense, and OWASP, and the attack class is now formally catalogued under OWASP LLM01:2025.

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