Sixty-seven percent of US enterprises were breached in the past 24 months, according to Pentera’s 2025 State of Pentesting survey of 500 security leaders, and half of security teams now run software-based red team exercises to find weaknesses before attackers do.

In cybersecurity, red teams simulate the creative ways malicious actors gain entry to an organization’s most sensitive systems, and the right exercises let organizations defend against threats proactively. This guide breaks down how red teaming exercises work, three classic examples and six AI-focused exercises worth running in 2026.

What Is a Red Teaming Exercise?

Red teaming exercises are full-scope simulated attacks in which a red team emulates real adversaries to test an organization’s defenses. Red teaming exercises cover phishing simulations, physical intrusion tests, insider threat drills and AI red teaming of models and agents. Red team exercises follow a five-step process: define goals, assemble the red team, execute the attack, debrief and patch.

How Red Teaming Exercises Work

Red teaming exercises are considered the gold standard in cybersecurity testing. They employ experienced, creative testers who emulate real-world adversaries, putting an organization’s defenses to the ultimate test. Red teams try to gain as much unauthorized access as possible to expose weaknesses in an organization’s defenses. 

Red teaming exercises differ by organization, but they often follow a structured process similar to the steps outlined below. 

1. Defining goals: First, a team of decision-makers determines which areas to test. In many cases, this includes testing cyber defenses, physical security, or specific pieces of infrastructure.
2. Assembling a team: If an organization doesn’t already have one, it assembles a red team to execute the attack. It’s also a best practice to set up a blue team, which will attempt to protect the system during the red team’s attacks. 
3. Execution: The exercise starts when the red team researches their target. Once they spot a weakness, they conduct cyber attacks to exploit an organization’s weak points. 
4. Debriefing: After the exercise, the red team meets with management to share their findings. They explain what they gained access to, how they got in, and what the organization can do to prevent future attacks. 
5. Patching: In the final stage of the red team exercise, the organization fixes weak points exploited during the test. That includes patching software, updating procedures, or retraining staff. 

These exercises succeed more often than boards expect. When CISA ran a red team operation against a federal civilian agency, its report noted that "the red team remained undetected by network defenders throughout the first phase" (CISA advisory AA24-193A, July 2024).

The break-in is rarely the hard part. The debrief is where the value shows up.

Three Examples of Red Teaming Exercises

The most common red teaming exercises in 2026 fall into two groups: classic exercises that use various tactics to test people, facilities and networks, and AI-focused red teaming exercises that test models and agents.

Phishing simulations are the most common red team exercise, followed by physical intrusion tests and insider threat simulations.

1. Phishing Simulations

Phishing emails are an age-old problem for organizations. While they aren’t new, these attacks are still highly effective. Phishing was again the most reported cybercrime in the FBI’s 2025 Internet Crime Report, with 191,561 complaints. Red team exercises frequently conduct phishing simulations to test employees’ knowledge of phishing, malicious links and suspicious attachments.

2. Physical Security Breaches

Physical security is a crucial but often overlooked part of cybersecurity. For example, malicious actors sometimes leave USBs containing malicious code in office parking lots, hoping employees will plug them into their machines. 

Other physical security issues, like lock-picking or tailgating, are common red team exercises for identifying security weaknesses.

3. Insider Threats

With insider threats, a red team member acts like a disgruntled employee or compromised contractor. This red team exercise simulates data theft and unauthorized access that malicious insiders use to wreak havoc in an organization. It’s ideal for testing an organization’s existing monitoring and detection systems, which should stop insider threats in their tracks.

Red Team vs Blue Team vs Purple Team

The red team attacks and the blue team defends.

• Red teams emulate adversaries: they run phishing simulations, exploit vulnerabilities and try to move through the network undetected.
• Blue teams are the defenders: they monitor detection systems, investigate alerts and contain the intrusion.
• Purple teaming joins the two, with attackers and defenders sharing findings in real time so every attack technique immediately sharpens a detection rule.

Most red teaming exercises run against an unwitting blue team precisely to measure detection and response under realistic conditions.

Read more about red team vs blue team vs purple team.

How Long Does a Red Team Exercise Take and What Does It Cost?

A typical red team exercise takes a few weeks to a month or more, according to IBM, and full-scope engagements run longer than standard penetration tests: Kroll has documented three-month red team operations against mature environments.

Cost scales with scope. US security teams spend an average of $187,000 per year on penetration testing programs, per Pentera’s 2025 survey, and dedicated red team engagements sit at the top of that range because they involve multiple operators, stealth tradecraft and longer timelines.

‍Continuous automated red teaming (CART) spreads that cost across the year, testing around the clock instead of in a single window.

Which Frameworks Guide Red Team Exercises?

Three frameworks anchor most red team exercises.

1. MITRE ATT&CK catalogs adversary tactics, techniques and procedures (TTPs), giving red teams a common language for planning attack scenarios and mapping coverage.
2. ‍MITRE ATLAS extends that model to attacks on AI systems, from data poisoning to model extraction.
3. NIST guidance rounds out the picture: NIST SP 800-53 defines red team exercise controls for federal systems, and the NIST AI Risk Management Framework directs organizations to test AI systems against adversarial threats before and after deployment.

The OWASP Top 10 for LLM Applications adds a checklist of AI-specific weaknesses, with prompt injection at number one.

6 Red Teaming Exercises for Securing AI Platforms

As generative AI becomes more integrated into business operations, securing these systems against adversarial threats is critical. 13% of organizations have already reported breaches of AI models or applications, and 97% of those lacked proper AI access controls (IBM Cost of a Data Breach Report 2025). Red teaming exercises help identify vulnerabilities in AI models, ensuring they remain resilient against manipulation, bias exploitation and security breaches.

Microsoft’s AI red team, which has tested more than 100 generative AI products, frames the stakes plainly:

"The work of building safe and secure AI systems will never be complete. But by raising the cost of attacks, we believe that the prompt injections of today will eventually become the buffer overflows of the early 2000s – though not eliminated entirely, now largely mitigated through defense-in-depth measures and secure-first design."
- Ram Shankar Siva Kumar and coauthors, Microsoft AI Red Team. Lessons from Red Teaming 100 Generative AI Products, January 2025. Source

That framing is why the six exercises below treat AI security as a discipline of its own rather than a pentest add-on.

While red teaming can be used intermittently to assess the security of AI platforms, red teaming tools that offer continuous automated red teaming (CART) operate 24/7 to provide real-time insights into the platform’s security posture. 

Here are a few examples of red teaming exercises that can be used to test the security of AI platforms. 

1. Data Poisoning Simulations

These tests simulate attacks where malicious or biased data is injected into training databases to skew AI outputs. Red teamers assess the model’s resilience against backdoor attacks and data corruption strategies. 

2. Model Inversion & Data Extraction

Red teams evaluate whether attackers can extract sensitive or proprietary information from an AI model by querying it in specific ways. Exercises include membership inference attacks and model inversion techniques to expose privacy risks.

3. Misinformation & Content Manipulation Tests

Red teams can also simulate scenarios where AI-generated content is misused for spreading misinformation, deepfakes, or harmful narratives. Red teamers evaluate the effectiveness of content moderation, policy enforcement, and automated detection systems. 

4. API Security & Injection Attacks

Red teams want to assess AI APIs for vulnerabilities such as unauthorized access, privilege escalation, and malicious API calls. Red teamers test for injection flaws, API rate-limit bypasses, and improper authentication mechanisms. 

5. Automated Bot Detection Evasion

These exercises simulate adversarial bots attempting to bypass AI-driven fraud detection or authentication mechanisms. Exercises include CAPTCHA bypass tests, automated query flooding, and behavioral mimicry to evade AI security defenses.

6. Secure Prompt Engineering Tests

These tests assess whether AI models can be manipulated into bypassing safety filters through cleverly engineered prompts. Red teams use jailbreaking techniques, context manipulation, and stealthy prompt attacks to evaluate guardrails. 

Organizations that implement these red teaming exercises can proactively identify weaknesses in AI systems and models, enhance their security defenses and build more resilient and trustworthy AI platforms.

The people accountable for frontier AI risk are saying the same thing:

‍"Managing frontier AI risk requires more than internal safeguards. It requires continuous engagement with experts who understand how these systems behave across different technical, linguistic, and cultural contexts."
- Natasha Crampton, Chief Responsible AI Officer, Microsoft. Microsoft Security Blog, July 2026. Source

External, continuous adversarial testing is exactly what the exercises above operationalize.

●MINDGARD Red Team Exercise Planner

Which red teaming exercises should you run?

Pick what you need to test and your program context. The planner maps your answers to the nine exercises covered in this guide and suggests a cadence.

1. What do you need to test?

Employee awareness Physical security Detection & response Insider risk AI models & agents

2. Your context

Program maturity This is our first red team exercise We test once or twice a year We want continuous testing Industry pressure Standard Regulated (finance, healthcare, government) We ship AI features to customers

Your exercise plan

Select at least one area above to build your plan.

How this planner works

Each area you select maps to the matching exercises from this article (phishing simulation, physical breach, insider threat and the six AI-focused exercises). Cadence guidance follows two public data points: most organizations run red teaming exercises once or twice a year and 67% of US enterprises were breached in the past 24 months (Pentera, State of Pentesting 2025), while 13% of organizations have already reported breaches of AI models or applications (IBM, Cost of a Data Breach Report 2025). No answers leave this page.

Proactive Preparedness Starts Here

Whether you need to test your organization’s cybersecurity setup or assess your readiness for specific concerns, like physical security, red team exercises are a helpful tool to have in your corner. They proactively identify vulnerabilities, test defenses and give organizations valuable insights into their weaknesses.

Malicious attackers want access to your data, and they’re getting smarter by the day, with AI platforms squarely in their sights. Mindgard specializes in helping organizations stay ahead of threats with AI red teaming solutions that cover models, agents and applications.

Book a Mindgard demo today to see how red teaming builds resilience in AI models.

Frequently Asked Questions

How often should organizations conduct red teaming exercises? 

Most organizations conduct red teaming exercises once or twice a year. However, because of the increased incidence of attacks, organizations in finance, healthcare and cybersecurity need to perform tests more frequently.

How do red team exercises differ from penetration testing? 

Penetration testing and red team exercises differ in scope and stealth. A penetration test exploits as many vulnerabilities as possible in a defined system and is announced to defenders. A red team exercise simulates a full-scale attack: operators chain phishing, physical access and technical exploits toward a specific objective while staying hidden from the blue team.

Penetration tests measure how many holes exist; red team exercises measure whether your organization can detect and stop a determined adversary.

How long does a red team exercise last?

Most red team exercises run from a few weeks to a month or more, and full-scope engagements against mature environments can stretch to three months. Continuous automated red teaming removes the time cap by testing around the clock between manual engagements.

How do I know if a red teaming exercise was effective? 

The goal of a red teaming exercise is to proactively identify and fix weaknesses. Red teaming exercises are effective if your organization’s overall security posture improves over time. That includes identifying and stopping more threats, reducing employee-related security risks and responding to threats more quickly.

What skills are needed for red teaming?

Red teamers need offensive security skills such as penetration testing, exploit development and social engineering, scripting ability in languages like Python and PowerShell and strong reporting skills, since the debrief is where the exercise pays off. Common red team certifications include OSCP, CRTO and GPEN.

AI red teamers add a second toolkit: prompt engineering, familiarity with model architectures and frameworks like MITRE ATLAS for classifying attacks on machine learning systems.