--- title: "awesome-llm-security vs Anthropic-Cybersecurity-Skills" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/corca-ai-awesome-llm-security-vs-mukul975-anthropic-cybersecurity-skills" tools: ["corca-ai-awesome-llm-security", "mukul975-anthropic-cybersecurity-skills"] --- # awesome-llm-security vs Anthropic-Cybersecurity-Skills *GraphCanon updated Jul 12, 2026* ## Verdict 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; 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. [awesome-llm-security](https://github.com/corca-ai/awesome-llm-security) reports 1.6k GitHub stars, 294 forks, and 161 open issues, last pushed Aug 20, 2025. [Anthropic-Cybersecurity-Skills](https://mahipal.engineer/Anthropic-Cybersecurity-Skills/) has 25k stars, 3.1k forks, and 35 open issues, last pushed Jun 26, 2026. Figures are from public GitHub metadata via [awesome-llm-security's repository](https://github.com/corca-ai/awesome-llm-security) and [Anthropic-Cybersecurity-Skills's repository](https://github.com/mukul975/Anthropic-Cybersecurity-Skills). | | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [Anthropic-Cybersecurity-Skills](/tools/mukul975-anthropic-cybersecurity-skills.md) | | --- | --- | --- | | Tagline | A curation of tools, documents and projects about LLM Security | 817 structured cybersecurity skills for AI agents | | Stars | 1,637 | 25,282 | | Forks | 294 | 3,060 | | Open issues | 161 | 35 | | Language | - | Python | | Adopt for | 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 | 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. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [Anthropic-Cybersecurity-Skills](/tools/mukul975-anthropic-cybersecurity-skills.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 325d | 14d | | Open issues (now) | 161 | 35 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/corca-ai-awesome-llm-security/trust.md) | [trust report](/tools/mukul975-anthropic-cybersecurity-skills/trust.md) | ## Decision facts: awesome-llm-security - **Hosting:** unknown - **Pricing:** freemium - 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). - **Adopt for:** 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 ## Decision facts: Anthropic-Cybersecurity-Skills - **Pricing:** freemium - 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 - **Adopt for:** 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. ## Choose when ### 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, awesome-list. - 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. ### Choose Anthropic-Cybersecurity-Skills if… - 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: threat-hunting, cybersecurity, mitre-attack, nist-csf. - Also covers AI Agents. - - 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 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. ## 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. ## Common questions ### What is the difference between awesome-llm-security and Anthropic-Cybersecurity-Skills? awesome-llm-security: A curation of tools, documents and projects about LLM Security. Anthropic-Cybersecurity-Skills: 817 structured cybersecurity skills for AI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-llm-security over Anthropic-Cybersecurity-Skills? Choose awesome-llm-security over Anthropic-Cybersecurity-Skills 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, awesome-list; 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 choose Anthropic-Cybersecurity-Skills over awesome-llm-security? Choose Anthropic-Cybersecurity-Skills over awesome-llm-security when 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: threat-hunting, cybersecurity, mitre-attack, nist-csf; Also covers AI Agents; - 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 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. ### 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. ### Is awesome-llm-security or Anthropic-Cybersecurity-Skills more popular on GitHub? Anthropic-Cybersecurity-Skills has more GitHub stars (25,282 vs 1,637). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-llm-security and Anthropic-Cybersecurity-Skills open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-llm-security or Anthropic-Cybersecurity-Skills? GraphCanon lists graph-backed alternatives at [awesome-llm-security alternatives](/tools/corca-ai-awesome-llm-security/alternatives) and [Anthropic-Cybersecurity-Skills alternatives](/tools/mukul975-anthropic-cybersecurity-skills/alternatives) ([awesome-llm-security markdown twin](/tools/corca-ai-awesome-llm-security/alternatives.md), [Anthropic-Cybersecurity-Skills markdown twin](/tools/mukul975-anthropic-cybersecurity-skills/alternatives.md)), 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](/compare/corca-ai-awesome-llm-security-vs-mukul975-anthropic-cybersecurity-skills.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-llm-security or Anthropic-Cybersecurity-Skills? awesome-llm-security: Slowing. Anthropic-Cybersecurity-Skills: 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 awesome-llm-security and Anthropic-Cybersecurity-Skills? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-llm-security trust report](/tools/corca-ai-awesome-llm-security/trust); [Anthropic-Cybersecurity-Skills trust report](/tools/mukul975-anthropic-cybersecurity-skills/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=corca-ai-awesome-llm-security`](/api/graphcanon/graph?tool=corca-ai-awesome-llm-security) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_