It suits application teams that want to inspect LLM requests before they reach a provider, including for prompt injection, PII, or data leakage risks.
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Best AI Security Testing Tools 2026
When you’re evaluating safeguards for AI systems, compare what each tool lets you test: custom cases, data leakage, jailbreaks, prompt injection, and unsafe outputs. Deployment mode, API-independent access details such as a free plan, and paid-from pricing can help narrow options to fit your environment and budget. Among the named tools are F5 BIG-IP APM, Project Moonshot, and AgentScan, with OpenSecureAI Scanner, PromptGuard, Augustus, Basilisk, and Giskard also represented. Consider which threat behaviors you need to examine and whether the available deployment and pricing details suit your development workflow.
AIRTA Red Team
It is aimed at red teams, whitehat testers, pentesters, and AppSec or MLsec teams assessing LLM behavior.
WebWindowsMac+3OpenSecureAI Scanner
It suits AI application teams, agent and MCP developers, security and compliance reviewers, learners, and red-teamers.
WebWindowsMac+3Promptfoo
Promptfoo is for developers and enterprises building AI applications who need prompt evaluation or red-team testing.
WebWindowsMac+3Giskard
It suits teams assessing conversational AI agents for safety and quality issues before production.
WebLinuxAPI+1CyberSecEval suits people evaluating cybersecurity risks or defensive behavior in large language models.
Moonshot is intended for AI developers and compliance teams evaluating LLMs and LLM-based applications.
It may suit teams that need API-based security scans for LLMs, RAG pipelines, or autonomous agents.
Augustus is intended for security professionals assessing LLM vulnerabilities.
It suits security researchers, AI developers, and academic users conducting authorized LLM assessments.
PyRIT suits teams assessing generative AI systems through structured red-team exercises, as well as developers building custom assessment workflows.
RedForge suits security teams and developers authorized to test LLM applications.
It is relevant to teams that want to validate agent behavior and track risks as systems change.
It suits individual builders, open-source projects, and teams shipping AI agents.