Best Free AI Agent Security Platforms of 2026

Mindgard, the leading cybersecurity platform for AI, specialises in securing AI/ML models, encompassing LLMs and GenAI for both in-house and third-party solutions. Rooted in the academic prowess of Lancaster University and launched in 2022, Mindgard has rapidly become a key player in the field by tackling the complex vulnerabilities associated with AI technologies. Our flagship service, Mindgard AI Security Labs, reflects our dedication to innovation, automating AI security testing and threat assessments to identify and remedy adversarial threats that traditional methods might miss due to their complexity. Our platform is supported by the largest, commercially available AI threat library, enabling organizations to proactively protect their AI assets across their entire lifecycle. Mindgard seamlessly integrates with existing security ecosystem platforms, enabling Security Operations Centers (SOCs) to rapidly onboard AI/ML solutions and manage AI-specific vulnerabilities and hence risk.

Akto is an open source, instant API security platform that takes only 60 secs to get started. Akto is used by security teams to maintain a continuous inventory of APIs, test APIs for vulnerabilities and find runtime issues. Akto offers tests for all OWASP top 10 and HackerOne Top 10 categories including BOLA, authentication, SSRF, XSS, security configurations, etc. Akto's powerful testing engine runs variety of business logic tests by reading traffic data to understand API traffic pattern leading to reduced false positives. Akto can integrate with multiple traffic sources - Burpsuite, AWS, postman, GCP, gateways, etc.

Flint AI serves as a local-first and framework-agnostic AgentOps command-line interface designed to assist developers in assessing the reliability of AI agents prior to their deployment in production environments. By executing the command flintai scan, users can evaluate Python source code for various issues such as security flaws, misconfigurations, and inadequate safety measures, while also employing AI reasoning to filter out potential false positives. Additionally, the command flintai eval tests a running agent by sending both functional and adversarial prompts, grading its responses against over 35 established criteria, which encompass aspects like factual accuracy, adherence to instructions, and resilience against prompt injections and jailbreak attempts. Each evaluated agent is assigned a reliability score, with the results linked to the OWASP Agentic Security Initiative risk categories ASI01 through ASI10 and severity assessed via CVSS v4.0 metrics. Flint AI is compatible with several agent frameworks and SDKs, including Claude Agents SDK, LangChain, CrewAI, Anthropic SDK, OpenAI SDK, MCP servers, and AutoGen, ensuring a broad range of applications in the development ecosystem. Furthermore, this versatile tool not only enhances the security and quality of AI agents but also streamlines the evaluation process, ultimately fostering greater confidence in AI deployment.