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Vol. 1 · Ed. 2026
CyberGlossary
日本語
Entry № 037

AI Red Teamer

AI Red Teamer とは何ですか?

AI Red TeamerA specialist who probes AI systems — LLMs, agents, multimodal models — for harmful behaviors, jailbreaks, safety failures, and security vulnerabilities, blending traditional offensive security with ML-specific adversarial techniques.

An AI red teamer (sometimes called LLM red teamer or model red teamer) is a newer role created by the rise of large language models and agentic AI. The work blends traditional offensive-security skills with ML-specific adversarial techniques and policy reasoning. Concrete activities include crafting prompt-injection and jailbreak prompts that bypass model safety training; building automated red-team harnesses that scale single-prompt probes into structured eval suites (TextAttack, garak, PyRIT, MAR, Anthropic's HHH evals); probing for harmful-content failures across the operator's policy (dangerous instructions, CSAM, weapons uplift, election interference); testing tool-use agents for tool-use injection, excessive agency, and unintended actions; testing multimodal models for image-, audio-, and video-based prompt injection; probing for training-data extraction and membership inference; and writing the reports that drive both model-level fine-tuning and system-level guardrails. The discipline is codified in frameworks such as the NIST AI RMF GenAI Profile, OWASP LLM Top 10, and MITRE ATLAS. Backgrounds vary widely; many AI red teamers come from offensive security, applied ML, or policy research, and the field is rapidly professionalizing through 2024–2026.

● 例

  1. 01

    An AI red teamer writes a structured suite of 1,000 adversarial prompts for a new code-assistant model, scoring each for safety, jailbreak resistance, and unintended tool-use.

  2. 02

    A red-team report convinces the model team to add a guardrail against a specific multi-turn jailbreak that no static eval had caught.

● よくある質問

AI Red Teamer とは何ですか?

A specialist who probes AI systems — LLMs, agents, multimodal models — for harmful behaviors, jailbreaks, safety failures, and security vulnerabilities, blending traditional offensive security with ML-specific adversarial techniques. サイバーセキュリティの 役割とキャリア カテゴリに属します。

AI Red Teamer とはどういう意味ですか?

A specialist who probes AI systems — LLMs, agents, multimodal models — for harmful behaviors, jailbreaks, safety failures, and security vulnerabilities, blending traditional offensive security with ML-specific adversarial techniques.

AI Red Teamer はどのように機能しますか?

An AI red teamer (sometimes called LLM red teamer or model red teamer) is a newer role created by the rise of large language models and agentic AI. The work blends traditional offensive-security skills with ML-specific adversarial techniques and policy reasoning. Concrete activities include crafting prompt-injection and jailbreak prompts that bypass model safety training; building automated red-team harnesses that scale single-prompt probes into structured eval suites (TextAttack, garak, PyRIT, MAR, Anthropic's HHH evals); probing for harmful-content failures across the operator's policy (dangerous instructions, CSAM, weapons uplift, election interference); testing tool-use agents for tool-use injection, excessive agency, and unintended actions; testing multimodal models for image-, audio-, and video-based prompt injection; probing for training-data extraction and membership inference; and writing the reports that drive both model-level fine-tuning and system-level guardrails. The discipline is codified in frameworks such as the NIST AI RMF GenAI Profile, OWASP LLM Top 10, and MITRE ATLAS. Backgrounds vary widely; many AI red teamers come from offensive security, applied ML, or policy research, and the field is rapidly professionalizing through 2024–2026.

AI Red Teamer からどのように防御しますか?

AI Red Teamer に対する防御は通常、上記の定義で述べたとおり、技術的統制と運用上の実践を組み合わせます。

AI Red Teamer の別名は何ですか?

一般的な別名: LLM red teamer, Model red teamer。

● 関連用語