Roles and Responsibilities in an LLM Red Team

Successfully executing an LLM red teaming engagement, as outlined in the LLM Red Teaming Lifecycle, requires a blend of specialized skills. While a single individual might handle multiple responsibilities in smaller setups, larger or more complex operations benefit from a well-defined team structure. Each role brings a unique perspective and expertise, contributing to a more thorough and impactful assessment. Understanding these roles is important before you start setting objectives for an engagement.

Core Roles and Their Responsibilities

An effective LLM red team often comprises individuals with diverse backgrounds, ranging from AI/ML expertise to traditional cybersecurity and ethics. Here are some common roles you'll encounter or may need to fill:

1. Red Team Lead (or Engagement Manager)

The Red Team Lead is the orchestrator of the entire operation. They are responsible for the overall strategy, planning, and execution of the red teaming engagement.

• Responsibilities:
  • Defining the engagement's high-level goals in collaboration with stakeholders (this will be covered more in "Setting Objectives and Scope").
  • Assembling and managing the red team.
  • Coordinating activities across different team members and phases of the lifecycle.
  • Serving as the primary point of contact for stakeholders or the "Blue Team" (the defenders).
  • Ensuring the engagement stays within legal and ethical boundaries (more on this in "Legal Frameworks and Responsible Disclosure Practices").
  • Overseeing the creation and delivery of the final report and communicating findings.
  • Making critical decisions when unexpected issues or opportunities arise during testing.

This role requires strong leadership, communication, and project management skills, along with a solid understanding of both red teaming principles and LLM technologies.

2. LLM Security Specialist (Adversarial Prompt Engineer)

This role is at the heart of testing the LLM's direct vulnerabilities. These specialists possess a deep understanding of how LLMs process language and where their weaknesses lie.

• Responsibilities:
  • Crafting and executing adversarial prompts designed to test for specific vulnerabilities like prompt injection, jailbreaking, and role-playing attacks.
  • Identifying and attempting to trigger harmful or biased outputs, or to elicit prohibited content.
  • Testing the LLM's ability to retain and leak sensitive information from its training data or conversational context.
  • Analyzing LLM responses to understand failure modes and devise new attack strategies.
  • Staying updated on the latest LLM attack techniques and research.
  • Documenting successful attack vectors and specific prompts used.

This specialist often has a background in natural language processing, AI safety, or creative problem-solving, combined with a knack for thinking like an attacker.

3. Data Scientist / ML Engineer (Red Team Focus)

While some LLM red teaming is black-box, a Data Scientist or ML Engineer on the red team can provide deeper insights, especially in grey-box or white-box scenarios, or when assessing vulnerabilities related to the model's training or architecture.

• Responsibilities:
  • Analyzing model behavior to infer potential architectural weaknesses or training data biases.
  • If model access permits, attempting more sophisticated attacks like membership inference (to check if specific data was in the training set) or model extraction.
  • Assessing susceptibility to data poisoning attacks by understanding how the model might be fine-tuned or updated.
  • Developing custom tools or scripts to automate parts of the attack process or analyze large volumes of output.
  • Collaborating with LLM Security Specialists to refine attack vectors based on model understanding.

This role requires a strong foundation in machine learning, data analysis, and often programming skills in languages like Python.

4. Security Engineer (Traditional Penetration Tester)

LLMs don't exist in a vacuum. They are part of larger systems, with APIs, databases, and network infrastructure. The Security Engineer brings traditional cybersecurity expertise to the team.

• Responsibilities:
  • Assessing the security of APIs and interfaces providing access to the LLM.
  • Testing for common web application vulnerabilities (e.g., OWASP Top 10) in the surrounding application that could indirectly compromise the LLM or its data.
  • Analyzing data flow and storage for security weaknesses related to how user inputs and LLM outputs are handled.
  • Investigating potential vulnerabilities in the deployment environment or underlying infrastructure.
  • Identifying weaknesses in access control mechanisms or session management for LLM-powered applications.

This individual is typically skilled in network security, application security testing, and infrastructure hardening.

5. Ethics and Safety Advisor

Given the potential for LLMs to generate harmful content, exhibit biases, or be misused, the Ethics and Safety Advisor plays an essential part in guiding the red team's activities responsibly.

• Responsibilities:
  • Advising on the ethical implications of planned attack scenarios and potential findings.
  • Helping to define the scope of testing to avoid causing undue harm or violating ethical guidelines.
  • Assessing the model for fairness, bias, and the potential to generate discriminatory or inappropriate content from a societal impact perspective.
  • Providing input on responsible disclosure of vulnerabilities.
  • Ensuring that red teaming activities align with organizational values and AI ethics principles.

This role often requires expertise in AI ethics, responsible AI development, and sometimes legal or policy backgrounds.

6. Technical Writer / Reporter

Clear communication of findings is as important as the discovery itself. While other team members contribute to documentation, a dedicated Technical Writer can ensure the final report is actionable and understandable.

• Responsibilities:
  • Structuring and writing the red team report, detailing vulnerabilities, attack narratives, and impact assessments.
  • Translating technical findings into clear language for various audiences, including developers and management.
  • Ensuring consistency and quality in all documentation produced by the team.
  • Assisting in the creation of remediation guidance.

Strong writing skills and the ability to understand and articulate complex technical issues are necessary for this role.

Visualizing Team Structure

While team composition is flexible, a typical structure might involve a lead coordinating various specialists who focus on different aspects of the LLM system.

A diagram illustrating a common LLM red team structure, highlighting the Red Team Lead's central coordination role and the distinct focus areas of various specialists.

Collaboration and Adaptability

It's important to remember that these roles are not always rigidly separated. In smaller organizations or on projects with limited resources, one person might wear multiple hats. For instance, an LLM Security Specialist might also handle some data science tasks or contribute heavily to report writing.

The key is that the responsibilities associated with these roles are covered. Effective LLM red teaming hinges on a collaborative environment where team members share insights and work together. An LLM Security Specialist might discover an anomaly that requires a Data Scientist's deeper model knowledge to exploit, or a Security Engineer might find an API vulnerability that gives an LLM Specialist a new attack vector.

The specific composition of your LLM red team will depend on:

• The complexity of the LLM system being tested.
• The defined scope and objectives of the engagement.
• The resources and expertise available.
• Whether the testing is black-box, grey-box, or white-box.

As you move through the LLM red teaming lifecycle described earlier, from planning and reconnaissance to exploitation and reporting, individuals in these roles will take the lead on different tasks, but continuous communication and knowledge sharing are essential for success. With a clear understanding of who does what, the team is better prepared to define specific objectives and the scope of the red teaming operation, which we will discuss next.