AI Security Resources for Developers

Large Language Models (LLMs) are rapidly integrating into enterprise applications, creating new attack surfaces and security challenges that traditional cybersecurity approaches weren't designed to address. Red teaming has emerged as the primary method for proactively identifying vulnerabilities in these AI systems, helping developers build more secure and resilient applications.​

This comprehensive resource guide compiles the most valuable tools, frameworks, and educational materials for developers interested in AI security and red teaming practices. Whether you're a beginner looking to understand prompt injection attacks or an advanced practitioner implementing automated security testing pipelines, these resources span from open-source tools to commercial solutions, covering both Python and TypeScript implementations.​

Beginner-Friendly Hubs

AI Security Lab Hub
Interactive AI security challenge platform with progressive difficulty levels. Test your skills in prompt injection, jailbreaking, and AI manipulation techniques across multiple scenarios.​

Open-Source Tools and Frameworks

Promptfoo
Open-source LLM testing and red teaming framework for evaluating prompt quality, catching regressions, and identifying vulnerabilities. Test your prompts, agents, and RAG applications for security, quality, and performance issues.​

Microsoft PyRIT
The Python Risk Identification Tool for generative AI, an open-source automation framework designed to empower security professionals and ML engineers to proactively identify risks in AI systems through automated red teaming.​

NVIDIA Garak
NVIDIA's comprehensive LLM vulnerability scanner that probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses in Large Language Models. Think of it as "nmap for LLMs."​

Confident AI DeepTeam
A simple-to-use, open-source LLM red teaming framework for penetration testing and safeguarding LLM systems. Integrates with the DeepEval evaluation platform for comprehensive testing workflows.​

Here's an improved, developer-focused list covering the top red-teaming, evaluation, and AI security tools for LLMs and AI-native apps. "Gaming" or CTF-style competition links have been removed in favor of practical tools and evaluators. Snyk-specific solutions are also highlighted.

🌟 Leading AI Red Teaming & Security Tools

Snyk Evo & Snyk Labs Red Teaming Toolkit

• Overview: Snyk’s new LLM/AI red teaming prototype specifically targets prompt injection, data leaks, unauthorized code execution, and agent abuse for LLM-powered systems. It simulates adversarial prompts and tool misuse to catch issues before production. The engine is purpose-built for LLMs and agent systems and integrates directly into developer workflows for fast, repeatable security assurance.

• Evo by Snyk: The world's first agentic security orchestration system for AI-native applications. Runs autonomous adversarial testing (“red teaming agents”) on models, agents, and apps and incorporates the results into a continuous security platform.

  • News on Evo launch

• General Snyk Platform: Offers ML and AI code analysis (SAST), dependency scanning, container testing, and now LLM-specific red teaming and evaluation tools for CI/CD, IDE, and Git integration.

  • Snyk Platform Home

🛡️ Open Source Red Teaming & Evaluation Tools

1. Promptfoo

• Dev-first framework for LLM red teaming and evals (with flexible YAML/JSON config, CI/CD, Python/JS integrations).

• Features agent tracing, multi-turn testing, compliance mapping (OWASP, NIST, MITRE, EU AI Act), and plugins for testing agent misuse with Model Context Protocol (MCP).

• Comparison and documentation

2. PyRIT (Python Risk Identification Tool)

• Microsoft’s open automation framework for adversarial campaigns and safety evaluation, supports sophisticated attack chains and research-grade scoring.

• Works programmatically, now integrated into Azure AI Foundry.

3. NVIDIA Garak

• Flexible, adversarial LLM vulnerability scanner covering 100+ attack vectors—prompt injection, jailbreaks, toxicity, and more.

• Strong reporting, supports 20+ AI platforms (OpenAI, Hugging Face, Cohere, NVIDIA NIMs, etc.).

• Provides AVID report generation and HTML/scoring exports.

4. FuzzyAI

• Automatic AI fuzzing tool focusing on jailbreak discovery through advanced mutation/genetic algorithm-based prompt modification.

• CLI and web UI available.

5. OpenAI Evals

• Framework for structured evaluation and benchmarking of LLM behavior.

• Pros: Well-documented, excellent for compliance use.

• Cons: Not adversarial—intended as an eval/QA toolkit more than a red team tool.

6. ARTKIT

• Framework for simulating complex, multi-turn adversarial scenarios with attacker–target chaining.

7. promptmap2

• Specialized prompt injection scanner for app/system prompt vulnerabilities (supports dynamic testing, JSON output for integration).

8. SecEval

• Academic-grade, structured security evaluation datasets and benchmarks (by Stanford), strong for compliance auditing and reporting.

🛠️ Additional Red Teaming & Penetration Testing Platforms

• Protect AI Recon: Scalable commercial platform for rigorous, automated red teaming of AI applications.

• Mindgard: Automated AI red teaming and security evaluation solution with broad vulnerability coverage.

• CrowdStrike AI Red Team Services: Professional/enterprise adversarial testing services for large orgs.

🏆 How to Select the Right Tools

📚 Further Reading & Documentation

• Snyk AI Red Teaming & Security Labs:

  • LLM Red Teaming Prototype

  • Evo Agentic Security Orchestration News

  • General Platform

• Promptfoo: Top 5 Open Source AI Red Teaming Tools 2025

• OnSecurity: Best Open Source LLM Red Teaming Tools (2025)

• Microsoft Azure PyRIT Documentation

• NVIDIA Garak Documentation

Specialized Security Tools

Vigil LLM
Python library and REST API to detect and mitigate security threats in LLM prompts and responses. Features prompt injection detection, modular scanners, canary tokens, and customizable security signatures.​

P4RS3LT0NGV3
Advanced prompt injection payload generator with 30+ text transformation techniques for LLM security testing and red teaming. Extended version offers additional payload generation techniques.​

AI Penetration Testing Toolkit
A comprehensive toolkit for AI/ML/LLM Penetration Testing. Provides structured approaches for discovering and exploiting vulnerabilities in AI systems.​

Community Resources

Awesome LLM Security
A curated list of awesome tools, documents, and projects about LLM Security. Regularly updated collection of the latest research, tools, and best practices.​

LLM Security Repository
Focuses on new vulnerabilities and impacts stemming from indirect prompt injection affecting LLMs integrated with applications. Essential reading for understanding real-world attack vectors.​

Comprehensive Red Teaming Guides

Microsoft AI Red Team Guidelines
Guidance and best practices from the industry-leading Microsoft AI Red Team. Covers planning red teaming for large language models and responsible AI risks.​

OWASP GenAI Red Teaming Guide
Emphasizes a holistic approach to Red Teaming across model evaluation, implementation testing, infrastructure assessment, and more. Part of the OWASP GenAI Security Project.​

NVIDIA LLM Red Teaming Technical Blog
Decomposes LLM red teaming strategies into different approaches for conversational attacks. Provides technical depth on attack methodologies and defense strategies.​

Industry Best Practices

Mindgard Red Teaming Techniques
Covers 8 key techniques and mitigation strategies for simulating adversarial attacks to uncover vulnerabilities. Includes real-world case studies and implementation guidance.​

Confident AI Step-by-Step Guide
A comprehensive guide on building an LLM red teaming pipeline. Covers everything from initial setup to advanced automation techniques.​

Checkmarx AppSec Testing Strategies
Learn AI security testing strategies to red team your LLMs for prompt injection, data leakage, and agent misuse. Includes tools, prompts, and CI/CD integration tips.​

Standards and Frameworks

Security Standards

OWASP LLM Security Verification Standard
Provides a basis for designing, building, and testing robust LLM-backed applications. Essential framework for establishing security baselines.​

NIST AI Risk Management Framework
For voluntary use to manage AI risks and improve trustworthiness in AI design, development, use, and evaluation. Comprehensive approach to AI governance and risk management.​

Assessment Frameworks

AI Vulnerability Assessment Framework
Open-source checklist designed to guide GenAI developers through the process of assessing vulnerabilities in AI systems. Structured approach for identifying, analyzing, and mitigating security risks.​

Arcanum Prompt Injection Taxonomy
Comprehensive taxonomy and classification system for prompt injection attacks developed by Arcanum Security. Structured framework for understanding and categorizing different attack vectors.​

Commercial Solutions and Services

Enterprise Security Platforms

CrowdStrike AI Red Team Services
Offers services to simulate real-world attacks against unique AI environments. Professional red teaming with expert analysis and reporting.​

Mindgard AI Security Platform
Provides automated AI red teaming and security testing solutions. Continuous monitoring and vulnerability assessment for production AI systems.​

Protect AI Recon
Scalable Red Teaming for AI, systematically testing AI apps with an attack library. Enterprise-grade security testing platform with comprehensive reporting.​

Evaluation and Monitoring Platforms

Confident AI - DeepEval Platform
A platform to test, benchmark, safeguard, and improve LLM application performance. Unified environment for security testing and performance evaluation.​

Arize AI Observability Platform
Unified LLM Observability and Agent Evaluation Platform for AI Applications. Real-time monitoring and security assessment capabilities.​

SplxAI
Continuous Red Teaming for AI Assistants and Agentic Systems. Automated security testing specifically designed for autonomous AI agents.​

Technical Resources and Research

Academic and Research Papers

MITRE AI Red Teaming Report
Emphasizes recurring AI red teaming to counter adversarial attacks. Comprehensive analysis of current threats and future challenges.​

UNESCO Red Teaming Playbook
A playbook introducing Red Teaming as an accessible tool for testing and evaluating AI systems for social good. International perspective on responsible AI testing.​

Technical Blog Posts and Case Studies

Lakera AI: Building Superhuman Red Teamers
A blog series on building an AI red teaming agent for LLMs. Deep dive into automated red teaming techniques and implementation details.​

Salesforce Automated Red Teaming
Discusses Salesforce's automated red teaming framework, fuzzai, for enhancing AI security. Enterprise-scale automation approaches and lessons learned.​

Pillar Security: Red Teaming AI Agents
Explores threats posed by agentic AI systems and details advanced red-teaming methodologies. Focus on autonomous agent security challenges.​

This comprehensive resource collection provides developers with everything needed to implement robust AI security testing practices. From hands-on training platforms to enterprise-grade tools, these resources support the full spectrum of AI red teaming activities, helping build more secure and resilient LLM-integrated applications.​

1. https://www.ayadata.ai/what-ai-red-teaming-actually-looks-like-methods-process-and-real-examples/

2. https://www.securitymagazine.com/blogs/14-security-blog/post/101566-why-red-teaming-matters-even-more-when-ai-starts-setting-its-own-agenda

3. https://www.zwillgen.com/artificial-intelligence/emerging-trends-regulating-generative-ai-red-teaming/

4. https://levelblue.com/blogs/security-essentials/red-teaming-for-generative-ai-a-practical-approach-to-ai-security

5. https://www.pynt.io/learning-hub/llm-security/10-llm-security-tools-to-know

6. https://www.lakera.ai/blog/llm-security-tools

7. https://arcanum-sec.github.io/ai-sec-resources/

8. https://www.breachcraft.io/blog/ai-security-risks-comprehensive-assessment-framework

9. https://github.com/Arcanum-Sec

10. https://owasp.org/www-project-top-10-for-large-language-model-applications/

11. https://mindgard.ai/blog/what-is-ai-red-teaming

12. https://www.enkryptai.com/blog/what-is-ai-red-teaming-how-to-red-team-llms-2025

13. https://checkmarx.com/learn/how-to-red-team-your-llms-appsec-testing-strategies-for-prompt-injection-and-beyond/

14. https://www.nist.gov/itl/ai-risk-management-framework

15. https://github.com/TrustAI-laboratory/AI-Vulnerability-Assessment-Framework

16. https://www.isaca.org/resources/news-and-trends/isaca-now-blog/2025/the-rise-of-the-agentic-ai-defender

17. https://www.sentinelone.com/cybersecurity-101/cybersecurity/ai-vulnerability-management/

18. https://www.practical-devsecops.com/best-ai-security-frameworks-for-enterprises/

19. https://www.scribd.com/document/893806484/7-25pass4

20. https://www.linkedin.com/posts/sgarai701_llmsecurity-appsec-promptinjection-activity-7314648559235055616-IUDP

21. https://www.sei.cmu.edu/documents/6301/What_Can_Generative_AI_Red-Teaming_Learn_from_Cyber_Red-Teaming.pdf

22. https://www.mend.io/blog/best-ai-red-teaming-services-top-6-services/

23. https://www.promptfoo.dev/blog/top-5-open-source-ai-red-teaming-tools-2025/

24. https://www.cycognito.com/learn/red-teaming/red-teaming-tools.php

25. https://onsecurity.io/article/best-open-source-llm-red-teaming-tools-2025/

26. https://mindgard.ai/blog/best-tools-for-red-teaming

27. https://relevanceai.com/agent-templates-software/snyk

28. https://labs.snyk.io/resources/red-team-your-llm-agents-before-attackers-do/

29. https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-red-teaming-agent

30. https://paelladoc.com/blog/securing-ai-code-with-snyk/

31. https://pureai.com/webcasts/2025/10/snyk-model-red-teaming-dynamic-security-analysis-for-llms.aspx

32. https://witness.ai/blog/ai-red-teaming/

33. https://snyk.io

34. https://snyk.io/articles/what-is-ai-jailbreaking-strategies-to-mitigate-llm-jailbreaking/

35. https://bishopfox.com/blog/2025-red-team-tools-c2-frameworks-active-directory-network-exploitation

36. https://www.techzine.eu/news/security/135661/snyk-launches-evo-for-securing-ai-native-applications/

37. https://www.linkedin.com/posts/praveenparihar_whats-your-model-hiding-preview-the-snyk-activity-7337109641295708160-nMem

38. https://cset.georgetown.edu/article/how-to-improve-ai-red-teaming-challenges-and-recommendations/

39. https://labs.snyk.io

40. https://protectai.com/recon

41. https://www.globenewswire.com/news-release/2025/10/22/3171061/0/en/Evo-by-Snyk-The-World-s-First-Agentic-Security-Orchestration-System.html