Full Analysis of AI Agent Security Tools: Onecli, Sigcli, Agent Vault, Ren AI Proxy, and FakeKey

Background: An Emerging Security Need

The rise of AI agents and coding assistants (such as Claude Code, Cursor) is bringing brand‑new security challenges to developers. Your project directory may quietly contain a .env file storing various API keys for OpenAI, Anthropic, Alibaba Cloud, Feishu – many of which are linked to credit cards.

The recent LiteLLM Axios supply‑chain attack has made the issue acute: when your development environment can be scanned by malicious dependencies at any time, storing API keys in plaintext is like walking around naked.

Hence, a new category of tools has emerged – credential security tools for AI agents. These tools share a highly consistent goal: enabling AI agents to securely access external services without needing (and being unable) to see the real API keys.

Below is a comprehensive overview of five representative products.

Product Definitions at a Glance

Detailed Product Descriptions

1. Onecli

• Website: https://www.onecli.sh/
• Positioning: Open‑source credential vault

Onecli is a general‑purpose credential management tool, specifically optimised for AI agent scenarios. It acts as a secure “middleman” – the AI agent requests credentials from Onecli, and Onecli handles the interaction with the real service. Throughout the process, the original API key remains completely invisible to the agent.

2. Sigcli

• Website: https://sigcli.ai/
• Positioning: Authentication CLI & proxy for AI agents

The name Sigcli hints at its core capability – authentication. It is more than a credential proxy; it is a complete identity verification solution. Its design philosophy is “grant the agent access, not your credentials” – meaning you can finely control what the agent can and cannot do without handing over your keys.

3. Agent Vault

• Documentation: https://docs.agent-vault.dev/
• Positioning: HTTP credential proxy and vault

Agent Vault’s product name directly reflects its functionality: it is a proxy plus a vault. The AI agent sends HTTP requests to it, and Agent Vault dynamically replaces fake credentials with real keys before the request reaches the target API.

4. Ren AI Proxy

• Website: https://ren.im
• Positioning: LLM API sharing proxy

Ren AI Proxy has the most unique positioning in this category. Its goal is not “protect my own keys from leakage” but rather “share my API quota with others without exposing my keys”. For example, if you have unused quota from a Coding Plan, you can share it with your team or friends via Ren AI Proxy. It supports:

• LAN sharing
• Internet sharing (using intranet penetration tools such as Tunelo)

5. FakeKey

• GitHub: https://github.com/happyvibing/fakekey
• Positioning: Rust‑based API key security proxy – replace real keys with fake ones

FakeKey has the most radical and direct idea: “make leaks meaningless”.

How it works

Client Agent (uses fake key sk-xxx_fk) 
    → FakeKey Proxy (TLS decryption, identify replacement rules) 
        → External API (uses real key sk-xxx)

• The AI agent and all dependencies only ever see fake keys (e.g., sk-xxx_fk).
• Real keys are encrypted and stored in the system’s built‑in key manager (e.g., macOS Keychain).
• Only when an HTTP/HTTPS request is made does the FakeKey proxy replace the fake key with the real one in real time.
• If any dependency is compromised, the attacker can at most steal meaningless fake strings.

Quick Start

# One‑line installation
curl -fsSL https://raw.githubusercontent.com/happyvibing/fakekey/main/install.sh | bash

# Initialisation and onboarding
fakekey onboard

# Run your favourite tool (leak‑free)
fakekey run claude
fakekey run pi

FakeKey is written entirely in Rust, requires no Docker, and emphasises being lightweight, fast, and deeply integrated with the system’s native key management.

Technical Route Comparison

The products above can be divided into two technical schools:

School 1: Proxy + Dynamic Replacement (Onecli, Sigcli, Agent Vault, FakeKey)

• Core idea: Place a local proxy between the AI agent and the target API. The agent uses fake credentials; the proxy swaps them for real ones just before sending the request.
• Problems solved: Credential leakage from dependency poisoning, log leaks, environment variable scanning, etc.
• Differences among representatives:
  • FakeKey: Most radical – “fake‑key replacement” is in its name and core.
  • Agent Vault: Emphasises being an HTTP credential proxy.
  • Onecli / Sigcli: Naming highlights “credential vault” and “authentication” concepts.

School 2: Permission Sharing (Ren AI Proxy)

• Core idea: Still a proxy model, but the goal shifts from “protecting yourself” to “securely sharing quota”.
• Problems solved: How to authorise access without handing over keys in multi‑user / multi‑machine environments.
• Unique value: It addresses “trust transfer” rather than just “leak prevention”.

Selection Recommendations

Conclusion: A New Security Category Taking Shape

These five products together reflect a trend: as AI agents become part of developers’ daily toolchains, credential security in agent environments is emerging as an independent and important sub‑domain of security.

Their core insight is: in a runtime environment where absolute trust is impossible, instead of trying to “prevent poisoning”, it may be better to design a mechanism that makes leakage itself worthless.

Onecli, Sigcli, Agent Vault, Ren AI Proxy, and FakeKey each approach this problem from different angles. The tooling landscape in this area is still evolving rapidly, but the direction and value are becoming increasingly clear.