AetherForge is a prompt architecture — a text-based framework used as input to large language models. It does not execute code, access networks, or process data directly. However, there are security considerations users should be aware of.

If AetherForge is used as a system prompt or initial context for an AI agent that has tool access (web browsing, code execution, file system access, API calls), the framework's outputs could influence tool-use decisions. This is not specific to AetherForge but applies to any prompt framework used with agentic systems.

Mitigations:

• Do not use AetherForge as a system prompt for agents with unsandboxed tool access in production environments.
• Review all tool-use actions triggered during AetherForge sessions before execution.
• When using the Enacted Cognition layer (Layer 6), ensure tool permissions are appropriately scoped.

The Distributed Forge mechanism (multi-agent analysis) involves multiple AI agents processing outputs from each other. This creates a prompt injection surface similar to platforms like Moltbook. One agent's output could contain instructions that influence another agent's behavior.

Mitigations:

• Treat all inter-agent outputs as untrusted input.
• Sandbox agents in Distributed Forge sessions.
• Do not grant agents in multi-agent sessions access to sensitive tools or credentials.

AetherForge can produce outputs that feel more rigorous and trustworthy than standard LLM responses due to its structured metacognitive mechanisms. This may lead users to over-trust outputs. AetherForge does not make LLM outputs accurate — it makes the reasoning process more structured and self-aware. Outputs can still be wrong.

Mitigations:

• Always verify critical claims independently.
• Use the Enacted Cognition layer to ground claims empirically when possible.
• Pay attention to confidence markers ({speculative}, {unknown}, {theatrical}).

If you discover a security concern related to AetherForge's design or mechanisms, please open an issue or contact the maintainer directly at aneeshjoseph1091@gmail.com.