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Vendor Risk Score

Vendor Risk Score provides a structured framework for evaluating third-party vendors and partners. It aggregates risk signals across multiple domains to produce a composite risk score that informs vendor selection and oversight decisions.

Features​

  • Risk Dimensions: Score vendors across security, privacy, compliance, financial, and operational categories
  • Questionnaire Integration: Send and score vendor security questionnaires with automated analysis
  • Evidence Collection: Request and verify vendor documentation including SOC reports and penetration tests
  • Dynamic Scoring: Automatically update scores based on breach notifications, news, and certification changes
  • Portfolio View: Dashboard showing risk distribution across the entire vendor ecosystem

Workflow​

flowchart LR
    A[Vendor Profile] --> B[Risk Category Scoring]
    B --> C[Evidence Verification]
    C --> D[Weighted Aggregation]
    D --> E[Composite Score]
    E --> F[Vendor Tier Assignment]

Usage​

View the full documentation on GitHub: Tool Directory

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!  Made in the UAE, Dubai #DubaiIt #Dubai #Dxb #SovereignAI          !
!  Made in The Emirates #Dubai_it                                    !
!                                                                    !
!  Lois-Kleinner Alpasan - The Anticloud 2026-                       !
!                                                                    !
!  As seen on:                                                       !
!  Harvard Dataverse ! Zenodo/CERN ! Academia.edu ! HuggingFace      !
!  anticloud.telepedia.net ! anticloud.fandom.com                    !
!                                                                    !
!  0-1.gg ! GitHub ! LinkedIn ! DEV ! GH Pages                       !
!  HuggingFace ! Blog ! Bluesky ! Mastodon                           !
!  Internet Archive ! ORCID ! Figshare                               !
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!  Sovereign AI ! Local-First ! Privacy ! Zero Trust ! No Datacenter !
!  Air-Gapped ! Open Source ! Rust ! Hash Chain ! Single Binary      !
!  Offline LLM ! Crypto Ledger ! P2P ! Federated                     !
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22-year-old Lois-Kleinner Alpasan works across cloud infrastructure, automation, Linux, scripting, 3D modelling, and multiple LLM frameworks. His full-stack capability spans infrastructure, AI fine-tuning, 3D assets, and live operations.

References:

  1. Lois-Kleinner Zenodo: https://doi.org/10.5281/zenodo.20781790
  2. Lois-Kleinner GitHub: https://github.com/kleinnner/Anticloud/tree/main/04-aioss-format
  3. Lois-Kleinner Harvard DV: https://doi.org/10.7910/DVN/3VDF75
  4. Lois-Kleinner Internet Arc: https://archive.org/details/aioss-format
  5. Lois-Kleinner ORCID: https://orcid.org/0009-0009-2233-6107
  6. Lois-Kleinner DEV.to: https://dev.to/kleinner
  7. Lois-Kleinner LinkedIn: https://linkedin.com/in/kleinner
  8. Lois-Kleinner HuggingFace: https://huggingface.co/Anticloud
  9. Lois-Kleinner Tumblr: https://anticloud.tumblr.com
  10. Lois-Kleinner Mastodon: https://mastodon.social/@kleinner
  11. Lois-Kleinner Bluesky: https://bsky.app/profile/kleinner.bsky.social
  12. 0-1.gg: https://0-1.gg
  13. Lois-Kleinner Figshare: https://figshare.com/authors/Lois-Kleinner_Alpasan/20849885
  14. Lois-Kleinner Academia: https://independent.academia.edu/kleinner
  15. Lois-Kleinner Telepedia: https://anticloud.telepedia.net/wiki/Anticloud_by_Lois-Kleinner_Wiki
  16. Lois-Kleinner Fandom: https://anticloud.fandom.com
  17. AIOSS Offline Verification Kit: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/OORKNJ