[Research] Unvalidated Trust: Cross-Stage Failure Modes in LLM/agent pipelines arXiv

AI-suggested

European organizations should implement multi-layered mitigations tailored to LLM pipeline architectures: 1) Enforce stage-wise validation of all intermediate outputs using semantic analysis and policy compliance checks before passing data to subsequent stages, preventing propagation of unsafe instructions. 2) Normalize and explicitly label data formats to avoid accidental interpretation of formatting or structure as commands, employing strict schema validation and format hygiene. 3) Implement explicit session scoping with defined lifetimes for latent rules and memory states to prevent persistent or delayed activation of harmful behaviors. 4) Separate data and command inputs rigorously using schema-aware guards to ensure configuration fields cannot be misinterpreted as executable directives. 5) Conduct thorough testing and red-teaming of LLM pipelines focusing on implicit command injection via structure or format manipulation. 6) Monitor model outputs continuously for anomalous code generation or unexpected behaviors, integrating human-in-the-loop review for high-risk outputs. 7) Collaborate with LLM vendors to understand model-specific behaviors and incorporate vendor-provided safety mechanisms. 8) Maintain up-to-date documentation and training for developers and operators on architectural risks and mitigation strategies. These measures go beyond generic advice by focusing on architectural trust boundaries, format hygiene, and session management specific to LLM pipelines.