Prompt injection vectors: how to test and harden AI systems
The post gathers prompt injection vectors and strategies with examples, useful for assessing and hardening the security of applications built on language models.
Source: Coleção de vetores e estratégias de prompt injection (x.com). Text prepared with AI from this source.
What happened and what to do
The post, published on 23 December 2025, presents a collection of prompt injection vectors and strategies accompanied by examples. The material is aimed at engineers who need to identify these techniques when assessing or strengthening the security of systems.
For a company, the content is a starting point for an adversarial test suite: direct and indirect prompt injection cases, such as instructions hidden in retrieved documents or in tool responses, run automatically in continuous integration pipelines before every change to prompts or agents. In parallel, it is worth separating tool permissions and sensitive data from the free-text flow, filtering outputs and logging every tool call in a monitoring dashboard, so that injection attempts are detected and reviewed. When data cannot leave the organization, the tests can run on private inference within the client's own infrastructure.
How the consultancy can help
Diagnosis of the prompt injection attack surface in your assistants, agents and integrations, followed by an adversarial test suite, tool permission policies and continuous monitoring, implemented on your own infrastructure.
Next step
If your company uses language models in products or internal processes, send a short description of the case, the data involved and the connected tools. We will reply with a scoped proposal for diagnosis and implementation.
Let's assess your project
I reply with scope and a proposal.