AgentIndex icon
AgentIndex
guardana logo
guardana
★ 251
vs
assay logo
assay
★ 13

guardana vs assay

guardana: Guardana is an open-source tool for AI security verification, scanning model artifacts, probing live endpoints, and analyzing recorded agent traces. It produces reproducible evidence and a measured verdict, enabling comparison of releases against accepted baselines for continuous security assurance.; assay: Assay provides an open, recomputable evidence profile for privileged AI agent tool actions, enforcing policies deterministically and fail-closed. It records decisions, observations, and unproven claims into tamper-evident bundles for offline verification and security auditing.

01

TL;DR

guardana logo
guardanaSecurity & Safety · ★ 251

Integrate into CI/CD pipelines as a security gate

Read guardana full review →
assay logo
assaySecurity & Safety · ★ 13

Generating small, reviewable CI artifacts for bounded auditability from existing evaluation outputs, runtime decisions, or MCP tool-call tests.

Read assay full review →
02

Side-by-Side Comparison

Field
guardana logoguardana
assay logoassay
Category
Security & Safety
Security & Safety
Stars
★ 251
★ 13
License
Apache-2.0
MIT
Install Command
pip install guardana-cli
curl -fsSL https://getassay.dev/install.sh | sh
Updated
2d ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Security, LLM Security, Software Supply Chain
AI Agent Security, Tool Call Enforcement, Evidence Auditing
03

Features

guardana logoguardana
01Static and offline verification of model and code artifacts
02Active security checks against deployed AI systems and agents
03Analysis of recorded AI agent traces and OpenTelemetry spans
04Continuous monitoring and comparison of security baselines
05Extensible with custom security rules, evaluators, and targets
assay logoassay
01Deterministic, fail-closed policy enforcement for tool calls, including optional kernel-level enforcement on Linux.
02Generates offline-verifiable, tamper-evident evidence bundles for audit and replay, integrated with CI without a hosted backend.
03Classifies claims by their trust basis (verified, self_reported, inferred, absent) to ensure honesty and prevent claims from exceeding observed facts.
04Policy gate (`assay mcp wrap`) for pre-execution allow/deny decisions on privileged tool calls, with clear reasons.
05Integrates with CI/CD pipelines via GitHub Actions and SARIF, enabling policy gates on pull requests and security-tab integration.
04

Use Cases

guardana logoguardana
↳Integrate into CI/CD pipelines as a security gate
↳Generate SARIF reports for GitHub code scanning
↳Use as a pre-commit hook for local development
↳Embed security assertions directly into Python tests
↳Scheduled active probing for continuous production monitoring
assay logoassay
↳Generating small, reviewable CI artifacts for bounded auditability from existing evaluation outputs, runtime decisions, or MCP tool-call tests.
↳Processing Promptfoo JSONL output from CI evaluations to produce evidence receipts and verified bundles.
↳Auditing and enforcing policies on MCP (Multi-Modal Command Protocol) tool calls, providing an allow/deny audit trail and observed-behavior evidence.
↳Implementing GitHub PR gates based on Trust Basis diffs and policy status, with SARIF/JUnit-ready output.
↳Generating inventory receipts and verified bundles from CycloneDX ML-BOM model components for model inventory and provenance.
FAQ

FAQ

What is the difference between guardana and assay?
Both guardana and assay are in the Security & Safety category. guardana has 251 stars, while assay has 13 stars.
Which is better, guardana or assay?
The best choice depends on your use case. Choose guardana if Integrate into CI/CD pipelines as a security gate, and assay if Generating small, reviewable CI artifacts for bounded auditability from existing evaluation outputs, runtime decisions, or MCP tool-call tests..
Is guardana free or open source?
Yes, guardana is open source on GitHub (Apache-2.0).
Is assay free or open source?
Yes, assay is open source on GitHub (MIT).
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