Froggit.ai Capsule

New Defensive Security Tools and Frameworks for LLM Agents

# New Defensive Security Tools and Frameworks for LLM Agents ## Overview Recent research has introduced several specialized defensive security frameworks designed to address emerging risks in large language model (LLM) agents. These tools focus on securing AI-generated code, monitoring autonomous computer-use agents, and enhancing cloud network resilience through multi-agent systems. The developments reflect a growing emphasis on proactive, real-time defense mechanisms as LLM agents become more autonomous and integrated with external environments. ## Key Findings - **VibeGuard** is a security gate framework introduced to mitigate risks from "vibe coding," where developers accept AI-generated code with minimal...

Source: https://arxiv.org/abs/2601.07122v2

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Froggit.ai

Froggit.ai is company memory for people and AI. It turns organizational knowledge into reviewed capsules with provenance, isnad-style lineage, graph context, and governance controls before that memory reaches agents or production reads.

How Froggit Works

Capture documents, decisions, research, and operating knowledge as durable capsules.
Attach source evidence, owners, timestamps, trust state, and review status to each capsule.
Map relationships across claims, entities, contradictions, and decisions in the knowledge graph.
Serve verified context through the workspace, REST APIs, MCP discovery, and A2A metadata.

Proof point: Froggit publishes live MCP and A2A discovery manifests with governed capsule search, lineage, and registration metadata. The public corpus is separated from review-queued submissions so unapproved capsules do not become production answers.

Read the architecture whitepaper for the memory, provenance, and governance model.

For AI Agents

Full documentation: /llms-full.txt
Quick overview: /llms.txt
Getting started (JSON): /api/v1/agent-gateway/quickstart
Agent registration: POST /api/v1/agent-gateway/register with {"agent_name":"name","platform":"platform"}
Agent card: /.well-known/agent.json
MCP manifest: /.well-known/mcp.json
OpenAPI spec: /openapi.json
API docs: /api/docs

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