Christopher Dikesa @dikesa_dev
Founder & CEO đ@cerbereag @luviaplace cerbereag.site Joined September 2026-
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@dantegaleazzi @X Currently I am building @CerbereAg, security and observability runtime for AI agent. And I would need a star or an observation from you Here is my GitHub: github.com/chrismsmr-celcâŚ
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@Shrey_0709 Happy birthday đđ
@Ritanshu347 @github @X Thanks đ
@ArdenBuilds Hello, thank you for your return I am building @CerbereAg an AI Observability and Security Agent and I would like you to see the source code because it is open source and if you can deposit a star it will reward my work, thank you đ GitHub: github.com/chrismsmr-celcâŚ
âMy LLM already has a regex, it will block dangerous promptsâ A developer can actually think that, and on the dangerous prompts that arrive, he is not wrong. But the real risk is elsewhere: ⢠The agentâs actions. The problem is not the prompt, it is the agent who sends an email to a personal address, deletes a baseline or spends money. A regex on the entrance doesnât see that. ⢠Indirect injection. It comes through a document, a web page or a tool response, not through the userâs prompt. ⢠The LLM cannot monitor itself. There is no independent trace, no human approval, no evidence to show to a client or an auditor. So @CerbereAg is not a âprompts filterâ. Itâs the control of actions, traceability and human approval cerbereag.site
AI agents donât just generate text. They read files. They access APIs. They send emails. They execute actions. They interact with other systems. That changes the security problem. A prompt filter can detect a suspicious instruction. But what if the instruction looks harmless by itself, while the agentâs trajectory becomes dangerous? The real question is not only: âWhat did the agent receive?â It is: âWhat did the agent actually do?â Thatâs why Iâm building @CerbereAg A security and observability runtime for AI agents that helps teams observe behavior, detect risky activity, enforce policies, and keep evidence of what happened. AI agents need freedom to act. But production systems need boundaries.
Exactly. Thatâs the balance weâre building with @CerbereAg : give agents the freedom to act, while enforcing boundaries and keeping evidence of what happened.
@dikesa_dev AI agents need freedom with the right boundaries.
@benz__002 @CerbereAg Thanks đ
@benz__002 Hello, thank you for your return I am building @CerbereAg an AI Observability and Security Agent and I would like you to see the source code because it is open source and if you can deposit a star it will reward my work, thank you đ GitHub: github.com/chrismsmr-celcâŚ
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