Yuntona is built on practitioner-led continuous intelligence gathering with expert curation — not automated scraping or vendor self-submission.
The AI security tooling landscape moves faster than any automated system can meaningfully evaluate. New tools, frameworks, and attack surfaces emerge weekly. Keeping pace requires continuous immersion in the practitioner community, not periodic desk research.
Every tool in the Yuntona directory has been individually evaluated by a security professional with over a decade of experience spanning SOC/NOC operations, third-party risk management, financial services regulation, and hands-on AI security research. The directory reflects professional judgement informed by real-world operational context — not algorithmic scoring.
Discovery draws from practitioner discourse on LinkedIn and specialist forums, industry conference proceedings, standards body publications, OWASP working group publications, industry intelligence newsletters, and direct engagement with thought leaders in AI security.
Not everything discovered gets listed. Each candidate tool is assessed against the current threat landscape, mapped to OWASP risk categories, and evaluated for genuine operational utility. Tools that duplicate existing coverage without meaningful differentiation are excluded.
The best tools surface in comment threads, conference hallway conversations, and working group discussions — not product launch pages. Following the practitioners who build and break AI systems is how Yuntona finds tools before they reach mainstream awareness.
The directory is updated on a rolling basis as new tools are discovered and evaluated. This is not a quarterly report — it is a living artefact maintained through daily engagement with the AI security ecosystem.
Every tool is mapped against the OWASP LLM Top 10 (2025) and the OWASP Agentic Top 10 (2026) to show which risks it addresses. Mappings are derived from analysis of each tool's documented capabilities, target threat model, and operational scope — assessed against the published risk descriptions in each OWASP standard.
AI-Assisted Execution, Human Design. OWASP risk mappings across 147 tools and 20 risk categories were produced using AI as an analytical engine. The methodology, evaluation schema, and framework inputs were designed by the curator. Every output was reviewed and validated against the published OWASP standards. This is human-directed analysis at scale — not automated classification.
A tool or framework is added to the directory when it meets three criteria: it addresses a genuine security risk in the generative or agentic AI stack, it is operational or near-operational (not vaporware), and it offers meaningful capability that is not already covered by existing entries. Open-source tools, commercial platforms, and frameworks are all eligible. Vendor sponsorship does not influence inclusion or risk ratings.
Transparency note. Yuntona is maintained by a single practitioner. The directory reflects one expert's informed judgement — not committee consensus or crowd-sourced voting. This is a deliberate choice: curation quality depends on accountability, not volume. If you believe a tool should be included or a mapping corrected, submit it for review.