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AI is here to stay and Agentic AI is going to be one of the key drivers in this revolution. The potential & power of AI agents is largely untapped still and businesses have only just begun to include them into their processes. This has led to re-imagining of entire IT workflows and new SaaS services are popping up claiming significant dollar benefits over existing setup. One thing is certain, future will rely immensely on how clearly & securely agentic AI workflows are designed.

A critical aspect of any agent is its ability to leverage tools which in turn call functions written to accomplish some unit of work within the larger scope of a workflow. If the design of the application is not secure then function calls can be abused. Agents can be tricked into injecting malicious user input as part of their function argument(s) resulting in compromise or unwanted behavior.

In this article, we will look at one such setup where the function called by the agent is poorly designed from a security standpoint. And the output of the LLM agent is then subsequently improperly handled by the application resulting in disclosure of sensitive data. Interestingly, “Insecure Output Handling” of LLM is the second most critical…