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 entry has been individually evaluated by a security professional with
over a decade of experience spanning SOC/NOC operations, third-party
risk, financial services regulation, and hands-on AI-security research. The directory
reflects professional judgement informed by real-world operational context — not
algorithmic scoring.
Curation quality depends on accountability, not volume.
Four commitments that shape every decision, from discovery to inclusion to retirement.
P.01
Multi-source intelligence
Discovery draws from practitioner discourse on LinkedIn and specialist forums, conference proceedings, standards body publications, OWASP working groups, industry intelligence newsletters, and direct engagement with AI-security thought leaders.
P.02
Expert signal filtering
Not everything discovered gets listed. Each candidate is assessed against the current threat landscape, mapped to OWASP categories, and evaluated for genuine operational utility. Duplicates without meaningful differentiation are excluded.
P.03
Community-embedded discovery
The best tools surface in comment threads, conference hallway conversations, and working-group Slacks — not product launch pages. Following the people who build and break AI systems is how tools reach us before mainstream awareness.
P.04
Continuous, not periodic
The directory updates on a rolling basis. This is not a quarterly report. It is a living artefact maintained through daily engagement with the AI-security ecosystem.
Where the signal comes from. Five channels feeding one pipeline.
Standards bodies OWASPNISTCSAMITREISO/IEC
Publications + working group output Industry intelligence CB Insightsanalyst reportsmarket research
Vendor-neutral coverage of emerging tech Conferences & events NHIconCSA summitsAI security workshops
Vendor-neutral industry events Practitioner networks OWASP AIUCLinkedIn groupsspecialist forums
Thought-leader commentary Primary research academic papersarXivvendor docsGitHub
First-hand documentation
Every tool is mapped against the OWASP LLM Top 10 (2025) and the
OWASP Agentic Top 10 (2026). Mappings are derived from each tool's
documented capabilities, target threat model, and operational scope — assessed against
the published risk descriptions.
LLM Top 10 · 2025
10 / 10 Full coverage
Agentic Top 10 · 2026
10 / 10 Full coverage
AI-assisted, human-designed
OWASP risk mappings across 161 tools and 20 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 is added when it meets three criteria. All three. No two-out-of-three.
C.1 Addresses a genuine security risk
in the generative or agentic AI stack, mapped to at least one OWASP category
C.2 Operational or near-operational
not vaporware, not a concept paper, not a GitHub readme without code
C.3 Offers meaningful capability
not already covered by existing entries; differentiated in scope, approach, or depth
Open-source tools, commercial platforms, and frameworks are all eligible. Vendor sponsorship does not influence inclusion or risk ratings.
Yuntona is maintained by a single practitioner. The directory reflects one expert's
informed judgement — not committee consensus, not crowd-sourced voting. This is a
deliberate choice.
Affiliation disclosure
Yuntona™ is an independent, open-source project. It is not affiliated with or endorsed by OWASP, NIST, MITRE, or any vendor
listed in the directory.
OWASP risk categories are used under the Creative Commons licence.