pluginagentmarketplace/custom-plugin-ai-red-teaming

automated-testing

CI/CD integration and automation frameworks for continuous AI security testing

原文の言語: 英語

benchmark-datasets

Standard datasets and benchmarks for evaluating AI security, robustness, and safety

原文の言語: 英語

certifications-training

Professional certifications, CTF competitions, and training resources for AI security practitioners

原文の言語: 英語

red-team-frameworks

Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation

原文の言語: 英語

responsible-disclosure

Ethical vulnerability reporting, coordinated disclosure, and bug bounty participation for AI systems

原文の言語: 英語

testing-methodologies

Structured approaches for AI security testing including threat modeling, penetration testing, and red team operations

原文の言語: 英語

adversarial-examples

Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness

原文の言語: 英語

adversarial-training

Defensive techniques using adversarial examples to improve model robustness and security

原文の言語: 英語

code-injection

Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation

原文の言語: 英語

continuous-monitoring

Real-time monitoring and detection of adversarial attacks and model drift in production

原文の言語: 英語

data-poisoning

Test AI training pipelines for data poisoning vulnerabilities and backdoor injection

原文の言語: 英語

defense-implementation

Implement mitigations, create input filters, design output guards, and build defensive prompting for LLM security

原文の言語: 英語

infrastructure-security

Securing AI/ML infrastructure including model storage, API endpoints, and compute resources

原文の言語: 英語

input-output-guardrails

Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs

原文の言語: 英語

llm-jailbreaking

Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods

原文の言語: 英語

model-extraction

Techniques to extract model weights, architecture, and training data through API queries

原文の言語: 英語

model-inversion

Privacy attacks to extract training data and sensitive information from AI models

原文の言語: 英語

prompt-hacking

Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation

原文の言語: 英語

prompt-injection-testing

Master prompt injection attacks, jailbreak techniques, input manipulation, and payload crafting for LLM security testing

原文の言語: 英語

rag-exploitation

Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning

原文の言語: 英語

red-team-reporting

Professional security report generation, executive summaries, finding documentation, and remediation tracking

原文の言語: 英語

safety-filter-bypass

Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment

原文の言語: 英語

secure-deployment

Security best practices for deploying AI/ML models to production environments

原文の言語: 英語

security-testing

Comprehensive security testing automation for AI/ML systems with CI/CD integration

原文の言語: 英語

vulnerability-discovery

Systematic vulnerability finding, threat modeling, and attack surface analysis for AI/LLM security assessments

原文の言語: 英語