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Agent Compass by Future AGI vs Agentic Security

Creates a truth graph for agents; does not perform automated attack testing
Agent Compass by Future AGIYour AI Agent's Truth GraphAgentic SecurityAgentic LLM Vulnerability Scanner / AI red teaming kit 🧪

Side by side

What it is
Agent Compass by Future AGI:Agent Compass turns AI agent traces into reliability insights, auto-clusters failures, detects hallucinations and tracks performance.
Agentic Security:Agentic Security is an open-source scanner that tests LLMs and AI agents for jailbreaks, multimodal attacks and other vulnerabilities.
Best for
Agent Compass by Future AGI:AI agent reliability and hallucination detection
Agentic Security:LLM vulnerability scanning and red-team testing
Who it’s for
Agent Compass by Future AGI:Teams building and operating AI agents who need debugging and safety monitoring.
Agentic Security:LLM developers, AI security researchers and DevOps teams building AI agents
Pricing
Agent Compass by Future AGI:Freemium
Agentic Security:Open source
Open source
Agent Compass by Future AGI:—
Agentic Security:Yes, 2,009 GitHub stars
DevHunt upvotes
Agent Compass by Future AGI:17
Agentic Security:3
Launched on DevHunt
Agent Compass by Future AGI:Nov 2025
Agentic Security:Feb 2025

Agent Compass by Future AGI features

  • Guardrails. Blocks AI hallucinations in real-time with configurable guardrails.
  • Evaluations. Runs comprehensive evaluations using 20+ metrics.
  • Error Feed. Provides Sentry-style error tracking for AI agents.
  • Simulations. Simulates thousands of multi-turn conversations for testing.
  • Synthetic Data. Generates diverse, realistic test data for agents.
  • Tracing. End-to-end request tracing across agent calls.
  • Dashboards. Custom drag-and-drop dashboards for performance monitoring.
  • Alerting. AI-powered alerts for anomalies and hallucination spikes.
Agent Compass by Future AGI on DevHunt →Alternatives

Agentic Security features

  • Multimodal Attacks. Test text, image and audio inputs to find cross-modal weaknesses.
  • Multi-Step Jailbreaks. Run iterative attack sequences that simulate sophisticated jailbreaks.
  • Comprehensive Fuzzing. Generate random inputs to stress-test LLMs and expose edge-case failures.
  • API Integration & Stress Testing. Connect to any LLM API and perform high-volume, real-world attack scenarios.
  • RL-Based Attacks. Use reinforcement-learning probes that adapt to the model’s defenses.
Agentic Security on DevHunt →Alternatives

Based on each tool's website and DevHunt data. Details may change; check the official sites.