AI-generated code can introduce security bugs when it is accepted without review, especially around authentication, input validation, dependency choice, secrets handling, and unsafe defaults. It is not automatically more or less secure than human-written code; the risk depends on validation.
The problem is confidence. AI output can look clean while missing threat modeling, edge cases, or project-specific security rules. It may also suggest outdated APIs or packages if the model lacks current context.
The right workflow is defensive. Require secure coding rules, run automated checks, inspect dependencies, and review sensitive paths manually. Verdent's value is that agentic coding can be paired with Plan Mode, isolated workspaces, and review instead of blind merging. For security-sensitive work, the agent can draft and test, but humans should approve architecture, secrets handling, permission logic, and production changes.
