Securing GenAI Beyond the Model: 10 LLM Attacks and the Case for Governance and Recovery
Veeam, Monday, February 9th, 2026
Traditional application security focuses on code paths and APIs. LLM applications, however, add a second, less predictable layer: Natural-language instructions that can be manipulated, sometimes directly by a user, and sometimes indirectly through content the system retrieves (e.g., documents, web pages, tickets, PDFs, wiki pages).
Enterprises are moving beyond chatbots into LLM-powered assistants that can:
- Retrieve information from internal repositories (RAG).
- Summarize sensitive content.
- Create tickets and run workflows.
- And most importantly: Take actions through tool integrations (e.g., email, ITSM, IAM, cloud APIs, DevOps pipelines).
That's where risk changes dramatically.