Comparison
ballerine vs Awesome-LLMSecOps
Verdict
Pick ballerine if ballerine is an open-source infrastructure and data orchestration platform for risk decisioning that supports areas such as compliance, fraud detection and identity verification; pick Awesome-LLMSecOps if awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models.
Markdown twin · ballerine alternatives · Awesome-LLMSecOps alternatives
GraphCanon updated Sep 20, 2026
9views this month
vs
Trust & integrity
| Signal | ballerine | Awesome-LLMSecOps |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 19, 2026 · github_public_v1 | Active (19d since push) As of Sep 12, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 19, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 12, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- ballerine
- Open-source infrastructure and data orchestration platform for risk decisioning
- Awesome-LLMSecOps
- Curated security resources for LLM operations
Stars
- ballerine
- 2.4k
- Awesome-LLMSecOps
- 155
Forks
- ballerine
- 311
- Awesome-LLMSecOps
- 76
Open issues
- ballerine
- 20
- Awesome-LLMSecOps
- 20
Language
- ballerine
- TypeScript
- Awesome-LLMSecOps
- HTML
Adopt for
- ballerine
- Ballerine is an open-source infrastructure and data orchestration platform for risk decisioning that supports areas such as compliance, fraud detection and identity verification.
- Awesome-LLMSecOps
- Awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models.
Persona
- ballerine
- -
- Awesome-LLMSecOps
- -
Runtime
- ballerine
- -
- Awesome-LLMSecOps
- -
License
- ballerine
- The platform is under Other license, which means specific terms are provided beyond the information publicly available.
- Awesome-LLMSecOps
- -
Last pushed
- ballerine
- Sep 17, 2026
- Awesome-LLMSecOps
- Aug 23, 2026
Categories
- ballerine
- Evaluation & Observability
- Awesome-LLMSecOps
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- ballerine
- Very active (96%)
- Awesome-LLMSecOps
- Active (82%)
Days since push
- ballerine
- 1d
- Awesome-LLMSecOps
- 19d
Stars delta
- ballerine
- +13 (30d)
- Awesome-LLMSecOps
- +5 (30d)
Open issues delta
- ballerine
- +11 (30d)
- Awesome-LLMSecOps
- +9 (30d)
Owner type
- ballerine
- Organization
- Awesome-LLMSecOps
- User
Full report
- ballerine
- Trust report
- Awesome-LLMSecOps
- Trust report
Choose ballerine if…
- ballerine is primarily TypeScript; Awesome-LLMSecOps is HTML.
- Pricing: While Ballerine has an open-source repository that is not currently supported, commercial SaaS options may be available for a fee..
- Tags unique to ballerine: back-office, compliance, data-orchestration, fraud-detection.
- When you are working in the payment sector or run a Fintech company and need tools to automate decisions during the customer lifecycle.
When NOT to use ballerine
- If you require immediate support or are unable to wait as Ballerine is currently undergoing a major rebuild and is not actively supported at this time.
- When your risk management needs do not align with automated workflows, rule engines, or third-party plugin systems, suggesting a more traditional approach might be better.
Choose Awesome-LLMSecOps if…
- Awesome-LLMSecOps is primarily HTML; ballerine is TypeScript.
- Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection.
- Also covers AI Agents.
- Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation
When NOT to use Awesome-LLMSecOps
- Looking for extensive academic references or ArXiv papers in descriptions
- Require real-time interactive tools rather than curated static lists of resources
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ballerine-io/ballerine) · observed Sep 20, 2026
- GitHub forks (ballerine-io/ballerine) · observed Sep 20, 2026
- Last push (ballerine-io/ballerine) · observed Sep 17, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (wearetyomsmnv/Awesome-LLMSecOps) · observed Sep 20, 2026
- GitHub forks (wearetyomsmnv/Awesome-LLMSecOps) · observed Sep 20, 2026
- Last push (wearetyomsmnv/Awesome-LLMSecOps) · observed Aug 23, 2026
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: ballerine 2.4k · Awesome-LLMSecOps 155 (synced Sep 20, 2026).
Common questions
- What is the difference between ballerine and Awesome-LLMSecOps?
- ballerine: Open-source infrastructure and data orchestration platform for risk decisioning. Awesome-LLMSecOps: Curated security resources for LLM operations. See the comparison table for live GitHub stats and shared categories.
- When should I choose ballerine over Awesome-LLMSecOps?
- Choose ballerine over Awesome-LLMSecOps when ballerine is primarily TypeScript; Awesome-LLMSecOps is HTML; Pricing: While Ballerine has an open-source repository that is not currently supported, commercial SaaS options may be available for a fee.; Tags unique to ballerine: back-office, compliance, data-orchestration, fraud-detection; When you are working in the payment sector or run a Fintech company and need tools to automate decisions during the customer lifecycle.
- When should I choose Awesome-LLMSecOps over ballerine?
- Choose Awesome-LLMSecOps over ballerine when Awesome-LLMSecOps is primarily HTML; ballerine is TypeScript; Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection; Also covers AI Agents; Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation.
- When should I avoid ballerine?
- If you require immediate support or are unable to wait as Ballerine is currently undergoing a major rebuild and is not actively supported at this time. When your risk management needs do not align with automated workflows, rule engines, or third-party plugin systems, suggesting a more traditional approach might be better.
- When should I avoid Awesome-LLMSecOps?
- Looking for extensive academic references or ArXiv papers in descriptions Require real-time interactive tools rather than curated static lists of resources
- Is ballerine or Awesome-LLMSecOps more popular on GitHub?
- ballerine has more GitHub stars (2,434 vs 155). Stars measure visibility, not whether either tool fits your constraints.
- Are ballerine and Awesome-LLMSecOps open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to ballerine or Awesome-LLMSecOps?
- GraphCanon lists graph-backed alternatives at ballerine alternatives and Awesome-LLMSecOps alternatives (ballerine markdown twin, Awesome-LLMSecOps markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, ballerine or Awesome-LLMSecOps?
- ballerine: Very active. Awesome-LLMSecOps: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for ballerine and Awesome-LLMSecOps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ballerine trust report; Awesome-LLMSecOps trust report.