Prompt Injection

OWASP describes prompt injection as a vulnerability affecting LLMs and notes it can lead to data leakage, privilege escalation, and unauthorized execution in multi-step workflows. The page also points to mitigations such as guardrails, monitoring, scoped responses, and training data hygiene.

Report facts: OWASP defines prompt injection as a vulnerability where attackers craft inputs that alter an LLM’s intended behavior, enabling data leakage, privilege escalation, and unauthorized execution in multi-step agent workflows.[1][6] The OWASP material highlights mitigations including strong prompt design, scoped responses, guardrails, monitoring, and keeping system prompts confidential, along with input/output filtering and least-privilege access.[1][5][6] CyberSE.AI analysis: For organizations deploying LLMs and AI agents, prompt injection represents a core architectural risk that can turn seemingly benign natural-language inputs into a path for sensitive data exfiltration or high-impact actions via tool/agent integrations. Controls such as secure agent design, continuous adversarial testing, and business-logic audits of how LLM outputs can trigger downstream tools are critical to prevent an injected prompt from escalating privileges or driving unauthorized workflows.