I built an "Immune System" for AI Agents using Textual TUI & FastAPI Middleware (First Post!)
A developer has created an 'Immune System' for AI agents using Textual TUI and FastAPI middleware. The project, named AegisOS, aims to enhance safety and prevent prompt manipulation in autonomous AI agents. It features a real-time monitoring dashboard and various tools to manage and configure AI agent operations.
- ▪AegisOS acts as a middleware proxy between AI agents and their LLM gateways.
- ▪The system includes a TUI dashboard for monitoring and configuring AI agents in real-time.
- ▪It addresses vulnerabilities such as prompt injections and tool abuse in autonomous AI agents.
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Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/noname_242/i-built-an-immune-system-for-ai-agents-using-textual-tui-fastapi-middleware-first-post-1no7 |
| Publication time | Sun, 17 May 2026 16:49:54 +0000 |
| Retrieval time | 2026-05-17T17:03:20.824Z |
| Last seen | 2026-05-17T17:03:20.824Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | fcrrzKVl5Q66 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3936429) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } noname Posted on May 17 I built an "Immune System" for AI Agents using Textual TUI & FastAPI Middleware (First Post!) #python #security #fastapi #antigravity 👋 Hello DEV Community! A real-time prompt monitoring proxy, multi-LLM consensus router, and high-fidelity TUI dashboard built in Python. This is my very first post here, and I'm thrilled to join the community! I recently set out to solve a major issue in the autonomous AI agent space: safety and prompt manipulation.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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