Comparison
Anthropic-Cybersecurity-Skills vs Awesome-LLMSecOps
Verdict
Pick Anthropic-Cybersecurity-Skills if anthropic-Cybersecurity-Skills is a comprehensive repository of 817 structured cybersecurity skills mapped across six industry frameworks, making it highly versatile for various AI platforms and security needs; pick Awesome-LLMSecOps if awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models.
Markdown twin · Anthropic-Cybersecurity-Skills alternatives · Awesome-LLMSecOps alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | Anthropic-Cybersecurity-Skills | Awesome-LLMSecOps |
|---|---|---|
| Maintenance | Active (8d since push) As of 2d · github_public_v1 | Very active (4d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2d · github_public_v1 | Not a fork · Personal account As of 1w · 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
- Anthropic-Cybersecurity-Skills
- 817 structured cybersecurity skills for AI agents
- Awesome-LLMSecOps
- Curated security resources for LLM operations
Stars
- Anthropic-Cybersecurity-Skills
- 28k
- Awesome-LLMSecOps
- 150
Forks
- Anthropic-Cybersecurity-Skills
- 3.4k
- Awesome-LLMSecOps
- 63
Open issues
- Anthropic-Cybersecurity-Skills
- 46
- Awesome-LLMSecOps
- 11
Language
- Anthropic-Cybersecurity-Skills
- Python
- Awesome-LLMSecOps
- HTML
Adopt for
- Anthropic-Cybersecurity-Skills
- Anthropic-Cybersecurity-Skills is a comprehensive repository of 817 structured cybersecurity skills mapped across six industry frameworks, making it highly versatile for various AI platforms and security needs.
- Awesome-LLMSecOps
- Awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models.
Persona
- Anthropic-Cybersecurity-Skills
- -
- Awesome-LLMSecOps
- -
Runtime
- Anthropic-Cybersecurity-Skills
- -
- Awesome-LLMSecOps
- -
License
- Anthropic-Cybersecurity-Skills
- Apache-2.0
- Awesome-LLMSecOps
- -
Last pushed
- Anthropic-Cybersecurity-Skills
- Aug 8, 2026
- Awesome-LLMSecOps
- Aug 4, 2026
Categories
- Anthropic-Cybersecurity-Skills
- AI Agents, Evaluation & Observability
- Awesome-LLMSecOps
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- Anthropic-Cybersecurity-Skills
- Active (82%)
- Awesome-LLMSecOps
- Very active (96%)
Days since push
- Anthropic-Cybersecurity-Skills
- 8d
- Awesome-LLMSecOps
- 4d
Open issues (now)
- Anthropic-Cybersecurity-Skills
- 46
- Awesome-LLMSecOps
- 11
Stars delta
- Anthropic-Cybersecurity-Skills
- +2.3k (30d)
- Awesome-LLMSecOps
- Unknown
Open issues delta
- Anthropic-Cybersecurity-Skills
- +6 (30d)
- Awesome-LLMSecOps
- Unknown
Full report
- Anthropic-Cybersecurity-Skills
- Trust report
- Awesome-LLMSecOps
- Trust report
Choose Anthropic-Cybersecurity-Skills if…
- Anthropic-Cybersecurity-Skills is primarily Python; Awesome-LLMSecOps is HTML.
- Pricing: Available under the Apache 2.0 license, ensuring free access and modification but without guaranteeing commercial support..
- Requirements: Min 4 GB RAM; Supports integration with over 20 platforms including Claude Code and GitHub Copilot; Requires basic understanding of cybersecurity frameworks for optimal use.
- Tags unique to Anthropic-Cybersecurity-Skills: ai-agents, cybersecurity, mitre-attack, nist-csf.
- - Use when you require integration with multiple cybersecurity frameworks like MITRE ATT&CK, NIST CSF 2.0, and others, providing a robust foundation for skill-based operations.
When NOT to use Anthropic-Cybersecurity-Skills
- - Avoid if your project specifically requires skills mapped exclusively to a single framework not among the six supported by Anthropic-Cybersecurity-Skills.
- - Not suitable for projects that do not align with or benefit from the agentskills.io standard implementation, as it might limit customization options.
Choose Awesome-LLMSecOps if…
- Awesome-LLMSecOps is primarily HTML; Anthropic-Cybersecurity-Skills is Python.
- Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection.
- 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 (mukul975/Anthropic-Cybersecurity-Skills) · observed Aug 16, 2026
- GitHub forks (mukul975/Anthropic-Cybersecurity-Skills) · observed Aug 16, 2026
- Last push (mukul975/Anthropic-Cybersecurity-Skills) · observed Aug 8, 2026
- License file (Apache-2.0) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (wearetyomsmnv/Awesome-LLMSecOps) · observed Aug 9, 2026
- GitHub forks (wearetyomsmnv/Awesome-LLMSecOps) · observed Aug 9, 2026
- Last push (wearetyomsmnv/Awesome-LLMSecOps) · observed Aug 4, 2026
- License file (unknown) · observed Aug 9, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: Anthropic-Cybersecurity-Skills 28k · Awesome-LLMSecOps 150 (synced Aug 16, 2026).
Common questions
- What is the difference between Anthropic-Cybersecurity-Skills and Awesome-LLMSecOps?
- Anthropic-Cybersecurity-Skills: 817 structured cybersecurity skills for AI agents. Awesome-LLMSecOps: Curated security resources for LLM operations. See the comparison table for live GitHub stats and shared categories.
- When should I choose Anthropic-Cybersecurity-Skills over Awesome-LLMSecOps?
- Choose Anthropic-Cybersecurity-Skills over Awesome-LLMSecOps when Anthropic-Cybersecurity-Skills is primarily Python; Awesome-LLMSecOps is HTML; Pricing: Available under the Apache 2.0 license, ensuring free access and modification but without guaranteeing commercial support.; Requirements: Min 4 GB RAM; Supports integration with over 20 platforms including Claude Code and GitHub Copilot; Requires basic understanding of cybersecurity frameworks for optimal use; Tags unique to Anthropic-Cybersecurity-Skills: ai-agents, cybersecurity, mitre-attack, nist-csf; - Use when you require integration with multiple cybersecurity frameworks like MITRE ATT&CK, NIST CSF 2.0, and others, providing a robust foundation for skill-based operations.
- When should I choose Awesome-LLMSecOps over Anthropic-Cybersecurity-Skills?
- Choose Awesome-LLMSecOps over Anthropic-Cybersecurity-Skills when Awesome-LLMSecOps is primarily HTML; Anthropic-Cybersecurity-Skills is Python; Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection; Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation.
- When should I avoid Anthropic-Cybersecurity-Skills?
- - Avoid if your project specifically requires skills mapped exclusively to a single framework not among the six supported by Anthropic-Cybersecurity-Skills. - Not suitable for projects that do not align with or benefit from the agentskills.io standard implementation, as it might limit customization options.
- 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 Anthropic-Cybersecurity-Skills or Awesome-LLMSecOps more popular on GitHub?
- Anthropic-Cybersecurity-Skills has more GitHub stars (27,958 vs 150). Stars measure visibility, not whether either tool fits your constraints.
- Are Anthropic-Cybersecurity-Skills and Awesome-LLMSecOps open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Anthropic-Cybersecurity-Skills or Awesome-LLMSecOps?
- GraphCanon lists graph-backed alternatives at Anthropic-Cybersecurity-Skills alternatives and Awesome-LLMSecOps alternatives (Anthropic-Cybersecurity-Skills 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, Anthropic-Cybersecurity-Skills or Awesome-LLMSecOps?
- Anthropic-Cybersecurity-Skills: Active. Awesome-LLMSecOps: Very 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 Anthropic-Cybersecurity-Skills and Awesome-LLMSecOps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Anthropic-Cybersecurity-Skills trust report; Awesome-LLMSecOps trust report.