Comparison
awesome-evals vs awesome-llm-security
Verdict
Pick awesome-evals if curated resources for AI agent evaluation with BenchFlow backing its maintenance; pick awesome-llm-security if awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and.
Markdown twin · awesome-evals alternatives · awesome-llm-security alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | awesome-evals | awesome-llm-security |
|---|---|---|
| Maintenance | Active (26d since push) As of 3w · github_public_v1 | Slowing (351d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- awesome-evals
- A curated library of resources for building and evaluating AI agents
- awesome-llm-security
- A curation of tools, documents and projects about LLM Security
Stars
- awesome-evals
- 761
- awesome-llm-security
- 1.7k
Forks
- awesome-evals
- 71
- awesome-llm-security
- 312
Open issues
- awesome-evals
- 21
- awesome-llm-security
- 173
Language
- awesome-evals
- -
- awesome-llm-security
- -
Adopt for
- awesome-evals
- Curated resources for AI agent evaluation with BenchFlow backing its maintenance
- awesome-llm-security
- Awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and
Persona
- awesome-evals
- -
- awesome-llm-security
- -
Runtime
- awesome-evals
- -
- awesome-llm-security
- -
License
- awesome-evals
- Other
- awesome-llm-security
- -
Last pushed
- awesome-evals
- Jul 1, 2026
- awesome-llm-security
- Aug 20, 2025
Categories
- awesome-evals
- AI Agents, Evaluation & Observability
- awesome-llm-security
- Evaluation & Observability
Trust and health
Maintenance
- awesome-evals
- Active (82%)
- awesome-llm-security
- Slowing (36%)
Days since push
- awesome-evals
- 26d
- awesome-llm-security
- 351d
Open issues (now)
- awesome-evals
- 21
- awesome-llm-security
- 173
Full report
- awesome-evals
- Trust report
- awesome-llm-security
- Trust report
Choose awesome-evals if…
- Tags unique to awesome-evals: agent-evaluation, ai-agents, benchmarks, llm-evaluation.
- Also covers AI Agents.
- Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation
When NOT to use awesome-evals
- Require real-time interactive support or direct tool integrations not covered by a static resource list
- Seeking proprietary tools from specific vendors rather than open resources and community content
Choose awesome-llm-security if…
- Pricing: As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided)..
- Tags unique to awesome-llm-security: llm, security.
- When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.
When NOT to use awesome-llm-security
- When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs.
- If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (benchflow-ai/awesome-evals) · observed Jul 28, 2026
- GitHub forks (benchflow-ai/awesome-evals) · observed Jul 28, 2026
- Last push (benchflow-ai/awesome-evals) · observed Jul 1, 2026
- License file (Other) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (corca-ai/awesome-llm-security) · observed Aug 6, 2026
- GitHub forks (corca-ai/awesome-llm-security) · observed Aug 6, 2026
- Last push (corca-ai/awesome-llm-security) · observed Aug 20, 2025
- License file (unknown) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-evals 761 · awesome-llm-security 1.7k (synced Jul 28, 2026).
Common questions
- What is the difference between awesome-evals and awesome-llm-security?
- awesome-evals: A curated library of resources for building and evaluating AI agents. awesome-llm-security: A curation of tools, documents and projects about LLM Security. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-evals over awesome-llm-security?
- Choose awesome-evals over awesome-llm-security when Tags unique to awesome-evals: agent-evaluation, ai-agents, benchmarks, llm-evaluation; Also covers AI Agents; Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation.
- When should I choose awesome-llm-security over awesome-evals?
- Choose awesome-llm-security over awesome-evals when Pricing: As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided).; Tags unique to awesome-llm-security: llm, security; When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.
- When should I avoid awesome-evals?
- Require real-time interactive support or direct tool integrations not covered by a static resource list Seeking proprietary tools from specific vendors rather than open resources and community content
- When should I avoid awesome-llm-security?
- When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs. If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.
- Is awesome-evals or awesome-llm-security more popular on GitHub?
- awesome-llm-security has more GitHub stars (1,672 vs 761). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-evals and awesome-llm-security open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to awesome-evals or awesome-llm-security?
- GraphCanon lists graph-backed alternatives at awesome-evals alternatives and awesome-llm-security alternatives (awesome-evals markdown twin, awesome-llm-security 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, awesome-evals or awesome-llm-security?
- awesome-evals: Active. awesome-llm-security: Slowing. 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 awesome-evals and awesome-llm-security?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-evals trust report; awesome-llm-security trust report.