# classification
標記為「classification」的 26 篇文章
AI Incident Classification Framework
Framework for classifying AI security incidents by type, severity, and response priority.
Label Flipping Attacks
Using label flipping to subtly alter model classification behavior during supervised fine-tuning.
AI Attack Taxonomy
A comprehensive classification of AI attacks organized by target, technique, and impact — providing a shared vocabulary for red team planning and reporting.
Injection Detection Research
State-of-the-art research in injection detection including perplexity-based methods, classifier approaches, and ensemble techniques.
Injection Attack Taxonomy 2025
Updated taxonomy of injection attacks against LLMs covering all known attack classes.
Novel Injection Classes
Exploring emerging injection classes that don't fit traditional taxonomies, including structural, temporal, and cross-system injection vectors.
Lab: Injection Detection Tool
Build a basic prompt injection detection tool using pattern matching, heuristics, and LLM-based classification to identify malicious inputs before they reach the target model.
Finding Severity Classification
Standardized framework for classifying AI security findings by severity, including risk scoring methodology and business impact assessment.
Prompt Injection Taxonomy
A comprehensive classification framework for prompt injection attacks, covering direct and indirect vectors, delivery mechanisms, target layers, and severity assessment for systematic red team testing.
Attack Technique Taxonomy Reference
Comprehensive attack technique taxonomy cross-referencing MITRE ATLAS, OWASP LLM Top 10, and custom classification schemes for AI security.
AI Vulnerability Classification System
Structured system for classifying AI-specific vulnerabilities by type, impact, and exploitability.
Classifying AI Vulnerability Severity
Framework for consistently classifying the severity of AI and LLM vulnerabilities, with scoring criteria, impact assessment, and examples across common finding categories.
Mapping Findings to OWASP LLM Top 10
Walkthrough for mapping AI red team findings to the OWASP Top 10 for LLM Applications, with classification guidance, reporting templates, and remediation mapping.
AI Incident Classification Framework
Framework for classifying AI security incidents by type, severity, and response priority.
實驗室el Flipping 攻擊s
Using label flipping to subtly alter model classification behavior during supervised fine-tuning.
AI 攻擊分類
依目標、技術與影響組織之 AI 攻擊完整分類——為紅隊規劃與報告提供共享詞彙。
Injection Detection Research
State-of-the-art research in injection detection including perplexity-based methods, classifier approaches, and ensemble techniques.
Injection 攻擊 Taxonomy 2025
Updated taxonomy of injection attacks against LLMs covering all known attack classes.
Novel Injection Classes
Exploring emerging injection classes that don't fit traditional taxonomies, including structural, temporal, and cross-system injection vectors.
實驗室: Injection Detection 工具
Build a basic prompt injection detection tool using pattern matching, heuristics, and LLM-based classification to identify malicious inputs before they reach the target model.
Finding Severity Classification
Standardized framework for classifying AI security findings by severity, including risk scoring methodology and business impact assessment.
提示詞注入 Taxonomy
A comprehensive classification framework for prompt injection attacks, covering direct and indirect vectors, delivery mechanisms, target layers, and severity assessment for systematic red team testing.
攻擊 Technique Taxonomy Reference
Comprehensive attack technique taxonomy cross-referencing MITRE ATLAS, OWASP LLM Top 10, and custom classification schemes for AI security.
AI 漏洞 Classification System
Structured system for classifying AI-specific vulnerabilities by type, impact, and exploitability.
Classifying AI 漏洞 Severity
Framework for consistently classifying the severity of AI and LLM vulnerabilities, with scoring criteria, impact assessment, and examples across common finding categories.
Mapping Findings to OWASP LLM Top 10
導覽 for mapping AI red team findings to the OWASP Top 10 for LLM Applications, with classification guidance, reporting templates, and remediation mapping.