As of 2025, most companies are adopting their own AI systems, but how many are systematically verifying their safety? According to a recent report by MIT Technology Review, 54% of companies still rely on manual evaluation methods, and only 26% have started automated assessments. This is clearly insufficient compared to the growing threats to AI security.

What Is an AI Red Team?

An AI Red Team extends the traditional cybersecurity red team concept to AI systems. According to definitions by MITRE ATLAS and OWASP, it is a “structured approach to identifying vulnerabilities in AI systems and mitigating risks,” representing a comprehensive security strategy that goes beyond simple technical testing.

The Evolution of AI Red Teams

While traditional red teams focus on penetrating and hacking systems, AI red teams address a new dimension of threats, such as:

• Prompt Injection & Jailbreaks: Attacks that bypass the security guardrails of AI models
• Data Poisoning: Manipulating training data to degrade model performance
• Adversarial Attacks: Subtly altering inputs to induce misclassification
• Bias and Toxicity Testing: Verifying ethical issues and discriminatory behavior in AI
• Hallucination Evaluation: Testing the AI’s potential to generate false information

TecAce's Automated AI Red Teaming Process

Step 1: Risk Profiling and Scope Definition

Every effective red team activity begins with thorough planning. Referring to Microsoft’s approach, “the experience, demographic diversity, and expertise in various fields of red team members are important.”

We conduct a comprehensive risk assessment that includes:

• Establishing service-specific threat models
• Analyzing attack vectors based on the MITRE ATLAS framework
• Mapping risks to the OWASP LLM Top 10
• Deriving industry-specific and specialized risk scenarios

Step 2: Scenario Design and Prompt Generation

TecAce’s proprietary AI Supervision platform provides the following advanced features:

Automated Attack Generation

# Automated adversarial testing with AI Supervision
redteam_config = {
	'plugins': [
    'harmful:hate',
    'harmful:bias',
    'harmful:privacy',
    'jailbreak',
    'prompt_injection',
    'pii_leakage'
	],
	'strategies': [
    'base64_obfuscation',
    'multilingual',
    'role_playing'
	],
	'targets': [
    'customer_service_bot',
    'technical_support_ai'
	]
}

# Generate and run the tests
results = await red_team_agent.scan(
	config=redteam_config,
	scan_name='telecom_security_eval_2025',
	concurrency=4
)

# Evaluate results with automated metrics
risk_score = evaluate_results(results)
generate_report(results, risk_score)