A.I.G (AI Infra Guard) vs InsForge: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of A.I.G (AI Infra Guard) and InsForge — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
A.I.G (AI Infra Guard)
Tencent Zhuque Lab
Tencent's open-source AI red teaming platform for scanning agents, agent skills, MCP servers and AI infrastructure, plus LLM jailbreak evaluation.
Key features
- Agent Skills Scan: Audits agent skill packages against a nine-category risk taxonomy aligned with the public SkillTrustBench T01-T09 classification, including detection of .pyc bytecode bypasses and charset smuggling.
- MCP Server Scan: Inspects MCP servers for threats such as tool poisoning, credential exfiltration and command injection, with tool whitelisting to prevent remote code execution during dynamic scanning.
- AI Infrastructure Vulnerability Scanning: Checks deployed AI components against a library that has grown to roughly 130 components and over 2,000 CVE rules, covering frameworks such as llama.cpp.
- Jailbreak Evaluation: Runs single-turn jailbreak operators plus multi-turn attack techniques including Many-Shot, PAIR, GOAT and ActorAttack to measure a model's resistance.
- Agent Scan with OWASP Coverage: Assesses running agents using OWASP-derived skills and web exfiltration detection, with a dedicated agent red team skill for comprehensive assessment.
- Standalone Scanner CLIs: skill-scan, mcp-scan and agent-scan each install as an independent command-line tool so scans can be wired directly into enterprise CI/CD pipelines.
- Docker Deployment with Web UI: Deploy the full platform with Docker on 4GB+ RAM and reach the web interface at localhost:8088, or use a one-click install script or a source build.
- AI Security Skill Market: A catalog of official security scanning skills, with the frontend fully open-sourced and integration available from OpenClaw chat via the aig-scanner skill.
Best for
- Pre-Deployment Agent Audit: Scan an internally built agent and its skill bundle for prompt injection, exfiltration and privilege risks before it is released to staff.
- MCP Supply Chain Review: Vet third-party MCP servers for tool poisoning and credential exfiltration before connecting them to production assistants.
- CI/CD Security Gate: Run skill-scan as a standalone CLI on every pull request so risky agent skills fail the build rather than shipping.
- Model Safety Benchmarking: Measure how a deployed LLM holds up against single and multi-turn jailbreak techniques before and after guardrail changes.
- AI Infrastructure Patch Triage: Inventory AI serving components and match them against the CVE rule library to prioritise which hosts need patching.
- Security Research and Reporting: Use the open scan engines and SkillTrustBench alignment as a reproducible basis for internal or published AI security research.
InsForge
InsForge
Backend platform built for AI-assisted development, providing auth, database, storage, functions, and agent-focused AI integrations.
Key features
- Authentication & Authorization: Managed user auth system to add sign-up, login, and role-based access controls quickly, enabling secure agent and user interactions without custom auth development.
- Managed Database: Hosted relational database capabilities (Supabase-like) designed for agent-driven schemas and operations, allowing agents to read, write, and migrate data programmatically.
- Object Storage: Built-in storage for files and assets with APIs for upload, download, and access control, simplifying how agents handle media and persistent artifacts.
- Serverless Functions: Deployable functions to run custom business logic and glue code, enabling agents to invoke or extend backend behavior with server-side code.
- AI Agent Integrations: Native connectors and integration points to link any AI agent to backend services, allowing agents to orchestrate data, storage, and functions autonomously.
- Agent-Native Tooling: Developer SDKs and APIs optimized for agent workflows, enabling rapid connection of agents to backend resources and simplifying agent-driven app development.
- Rapid Provisioning: Ability to add authentication, database, storage, functions, and AI integrations to apps in seconds, accelerating prototyping and deployments for agent-enabled products.
- Authentication system for user and agent identity management
- Managed database functionality similar to Supabase features
- File/storage management for persistent assets
- Serverless functions for custom backend logic and extensions
- AI integrations and connectors to attach any agent
- Agent-native tooling to enable autonomous agent-driven app creation
- Quick onboarding and signup for rapid prototyping
- Open-source repository and community-driven development
Best for
- Agent-Driven App Development: Enable an AI agent to scaffold, store, and manage a full-stack application by provisioning auth, database, and storage automatically.
- Autonomous Agent Operations: Allow agents to run serverless functions and manage persistent data to complete multi-step tasks or background processes without human intervention.
- Rapid Prototyping: Quickly attach backend services (auth, DB, storage, functions) to proofs-of-concept where AI capabilities are central, reducing boilerplate work.
- Agent-Oriented Product Backends: Build products whose core workflows are driven by AI agents (chat assistants, automation bots) using agent-native integrations and APIs.
- Replacing Supabase for Agent Workloads: Migrate Supabase-style projects to an agent-first backend to enable autonomous agents to perform maintenance, migrations, and feature creation.
- AI-Augmented Team Tools: Provide teams with an agent-connected backend to let internal automation agents manage datasets, handle user onboarding, or process uploads.
- Providing a backend for applications built or managed by AI agents
- Rapid prototyping of full-stack apps with agent-assisted development
- Autonomous agent orchestration and app lifecycle management
- Embedding agent connectors and AI integrations into existing apps
- Replacing or augmenting Supabase-like backends with agent-focused features