Purple Teaming in Cybersecurity: Significance, Roles, Tools, and Challenges

August 17, 2026

Purple Teaming in Cybersecurity: Significance, Roles, Tools, and Challenges

August 17, 2026
Offensive AI Security

Purple teaming is a collaborative cybersecurity approach where red team attackers and blue team defenders work together in a continuous feedback loop to test, identify, and strengthen an organization’s security posture.

Given that attackers today are faster, more automated, and AI-assisted, security operations need to be proactive, validated, and results-driven. Purple teaming is an effective solution to that demand.

This article explores everything you need to know about purple teaming, from how it works to why it is becoming essential for staying ahead of AI-driven threats.

Why Is Purple Teaming Still Relevant in 2026 and Why AI Upskilling Is Essential Now?

Last year, phishing was the most common initial access vector used by attackers to compromise systems, accounting for 16% of all breaches (IBM, 2025). On the other hand, organizations experienced 50% more serious vulnerabilities to patch, and the median time for full resolution increased by almost two weeks this year compared to 2025 (Verizon, 2026). Together, these numbers suggest an increase in common attack paths and the window of exposure after disclosure.

This widening exposure makes continuous purple teaming especially relevant in 2026 and beyond, not as a one-time exercise but as a structured, continuous mechanism. More than finding vulnerabilities, purple teams build institutional knowledge between red and blue teams by documenting attacker TTPs, gaps in telemetry, and the remediation decision rationale, enabling teams to ensure a stronger alignment of defensive capabilities with the current threat environment.

However, the threat landscape is not just growing but also changing in nature. Attackers are now leveraging AI to automate reconnaissance, generate more convincing phishing lures, and accelerate exploit development. In fact, 76% of organizations agree it is increasingly difficult to prepare as attackers use AI to adapt and evade defenses (CrowdStrike, 2025). Purple teams are not only dealing with a higher volume of threats but also with adversaries who are faster and more adaptive than before, and traditional exercise cycles are no longer sufficient to keep pace.

This shift makes upskilling in AI an increasingly important consideration for purple teams. A purple teamer who cannot recognize AI-assisted attack patterns, simulate AI-driven adversary behavior, or assess AI-specific attack surfaces risks leaving significant gaps unaddressed. This is where the concept of the AI purple teamer becomes relevant and worth understanding in the context of how the role is evolving.

What a Purple Teamer Does vs. What an AI Purple Teamer Does

Both traditional purple teams and AI purple teams are responsible for translating offensive findings into measurable defensive improvements. The key difference is that AI purple teams extend the same collaborative, adversarial approach to AI systems, introducing new attack surfaces, threat models, and validation techniques. Here’s how these roles differ:

	Purple Teaming	AI Purple Teaming
What Is Covered?	Using frameworks like MITRE ATT&CK to simulate real adversary behavior and test detection and response processes.	Testing AI systems for risks specific to LLM applications by using frameworks like MITRE ATLAS, ATT&CK, and OWASP Top 10 for LLM applications to emulate AI-specific threats, identify vulnerabilities, and validate AI detection and response capabilities.
What Is Done?	Develop attack simulations, write/refine detection rules, find coverage gaps, and strengthen security controls.	Simulate jailbreak attempts and adversarial prompt injections; examine AI pipelines for training-time risks, such as data poisoning and supply-chain vulnerabilities; stress-test models against evasion attacks and unexpected input behavior.
What Is the Aim?	Ensure that offensive findings lead to enhanced defensive controls.	Ensure that AI attack simulations lead to stronger AI security controls and greater resilience.

Purple Teaming: Core Skills and Roles

Purple teaming is a discipline that demands cross-functional skills, built on clearly defined roles and shared responsibilities across both offensive and defensive functions.

What Are the Skills Required of Purple Teamers?

The core skills that every purple teamer must possess are as follows:

Practical expertise with log analysis, endpoint detection and response (EDR) tools, and security information and event management (SIEM) systems
Offensive security and penetration testing techniques
Detection engineering skills (writing, testing, and revising detection rules)
Expertise in threat intelligence analysis and how to use it for simulations
Incident response know-how, to check how blue teams contain simulated attacks
Excellent communication skills to convert technical findings into practical suggestions for stakeholders, both technical and non-technical

Addressing today’s AI-driven threats requires purple teamers to build on the above foundational skills with a newer set of capabilities, which include:

Executing ethical simulations of prompt injection, jailbreaking, and prompt chaining attacks.
Conducting adversarial machine learning (ML) attack simulations, including data poisoning and model extraction.
Simulating adversarial AI kill chains (reconnaissance → mapping → exploitation → manipulation → exfiltration).
Red-teaming AI agents through controlled simulations, including memory corruption, tool misdirection, and checkpoint manipulation.
Conducting AI security assessments aligned to MITRE ATLAS, OWASP Top 10 for LLM Applications, OWASP ML Security Top 10, and NIST AI RMF.
Building detection rules and hardening strategies for AI systems.
Implementing defensive engineering controls, such as filtering, sandboxing, anomaly detection, and drift monitoring.

What Are the Different Roles Within a Purple Team?

Purple Team Lead: Manages all activities, including red and blue teams. They ensure findings are converted into measurable security improvements. As AI introduces new attack surfaces and faster threat cycles, this role now requires familiarity with AI risk frameworks to effectively scope exercises and communicate AI-specific findings to stakeholders.
Threat Emulation Specialist: Creates and executes attack simulations based on actual adversary tactics, techniques, and procedures (TTPs), ensuring every action aligns with the changing threat environment. Today, this increasingly includes simulating AI-assisted attack techniques, such as adversarial prompt injection, AI-driven reconnaissance, and automated exploit chaining.
Detection Engineer: Creates and modifies rules for SIEM and EDR platforms and translates offensive findings into detection logic. The role is expanding to include building detection rules and hardening strategies specific to AI systems, including identifying anomalous model behavior and inference-time attacks.
Threat Intelligence Analyst: Maintains exercises based on timing and relevance by mapping active threat-actor behavior to simulation scenarios. With AI now being actively used by adversaries to accelerate and adapt attacks, this role must also track AI-specific threat-actor behavior and incorporate it into emulation planning.
Incident Response Analyst: Assesses blue team responses during exercises and finds weaknesses in containment speed, escalation workflows, and remediation procedures. As AI-assisted attacks move faster, this role must evaluate whether response workflows are equipped to handle the reduced dwell times and increased complexity that AI-driven incidents introduce.
Security Controls Validator: Checks for configuration issues and evaluates if implemented security tools function as expected under simulated attack scenarios. This now extends to validating AI-specific defensive controls, such as input filtering, sandboxing, and anomaly detection, to ensure they hold up under adversarial conditions.

Frameworks and Tools Used in Purple Teaming

Nearly all mature purple teams build upon the foundational MITRE ATT&CK framework. It makes collaboration structured rather than interpretative by providing red teams, blue teams, and purple teams with a common language for adversarial conducts.

What it does: It organizes real-world TTPs into a matrix, which teams can directly map against their environment. Red teams utilize this resource to create credible trials. Blue teams use it to validate whether detection coverage is present, partial, or completely missing.
Best suited for: Any team, at any maturity level. It serves as a foundational reference for most purple team exercises carried out today.

However, MITRE ATT&CK was built around traditional IT environments and does not account for the attack surfaces introduced by AI systems. As purple teams are increasingly expected to assess AI-specific risks, this gap becomes a practical limitation.

This is where MITRE ATLAS comes in. Modeled on ATT&CK, it maps adversarial tactics and techniques specific to ML systems, covering threats like model evasion, data poisoning, and adversarial prompt injections. Together, ATT&CK and ATLAS give purple teams more complete framework coverage, one that addresses both conventional infrastructure and AI-specific attack surfaces.

What it does: Extends the ATT&CK model to AI systems, giving teams a structured reference for simulating and detecting attacks targeting ML models, LLM applications, and AI pipelines.
Best suited for: Teams operating in environments where AI systems are deployed or being assessed as part of the exercise scope.

While the MITRE ATT&CK framework defines the what, here are the different tools that handle the how:

Tools Used in Purple Teaming	Type	What It Does
Atomic Red Team	Adversary Emulation	An open-source library of attack simulations mapped to the MITRE ATT&CK framework, allowing teams to test specific techniques in their environment.
MITRE CALDERA	Adversary Emulation	An automated adversary emulation platform that enables teams to run attack simulations and assess defensive response.
PurpleSharp	Adversary Simulation	A specialized tool created for purple team exercises to simulate adversary techniques mapped to MITRE ATT&CK in Windows environments.
VECTR	Exercise Management	Findings from the purple team exercise are tracked, recorded, and reported for structured red/blue collaboration.
Cymulate	BAS Platform	Continuous attack simulations are automated across the kill chain to detect and control gaps in real time.
Picus Security	BAS Platform	Continuously tests security controls to strengthen them against real-world attack techniques mapped to MITRE ATT&CK.

Common Purple Teaming Challenges in the Age of AI and How to Address Them

The following are some purple teaming challenges that go beyond traditional operational gaps and how to address them:

Lack of AI-Specific Threat Emulation Capability

Most purple team exercises are still built around traditional TTPs mapped to MITRE ATT&CK. While this is still relevant, it leaves AI-specific attack surfaces, such as prompt injection, model evasion, and adversarial input attacks, largely untested. Teams that cannot simulate these techniques cannot meaningfully validate whether their AI systems are defensible.

Directional fix: Expand exercise scope to include AI-specific TTPs mapped to MITRE ATLAS. Start with the most critical attack surfaces relevant to your environment, such as LLM applications or AI-assisted workflows, and build emulation capability progressively.

No Feedback Loop for AI-Specific Findings

Even when AI-related gaps are identified during exercises, many teams lack a structured process for converting those findings into detection improvements or defensive controls specific to AI systems. Without that loop, the same AI-related gaps resurface in the next engagement.

Directional fix: Assign clear ownership for AI-specific findings, set remediation timelines, and schedule retests. This ensures exercises produce measurable improvements in AI security posture, not just documentation of gaps.

Detection Gaps Around AI-Driven Attacks

Traditional SIEM rules and EDR detections are built to identify known patterns of conventional attacks. AI-assisted attacks, such as those using automated reconnaissance, polymorphic malware, or adversarial inputs, can slip past these controls undetected, leaving blue teams blind to a growing category of threats.

Directional fix: Detection engineers within the purple team need to develop and test detection logic specific to AI-driven attack behavior. This includes monitoring for anomalous model inputs, unexpected API calls to AI endpoints, and inference-time irregularities.

Skill Gap in Offensive AI Testing

Purple teaming requires professionals who can operate credibly on both offensive and defensive sides. As AI becomes a core part of the attack surface, that expectation now extends to AI-specific offensive skills, such as prompt injection, adversarial ML attacks, and AI agent red-teaming, which most traditional purple teamers have not had formal exposure to.

Directional fix: Cross-training existing team members through structured AI security exercises helps build shared competency over time. However, for teams looking to validate and formalize that capability, certifications like COASP, mapped to frameworks like MITRE ATLAS and OWASP Top 10 for LLM Applications, offer a structured path to building and demonstrating offensive AI testing skills.

Upskilling in Purple Teaming: The Role of the COASP Certification

Today’s threat landscape not only highlights the need for continuous purple teaming but also the AI-specific challenges that extend beyond traditional security responsibilities. These challenges make it important for purple teamers to be equipped with AI-focused offensive skills and to translate AI attack findings into defensible controls. The Certified Offensive AI Security Professional (COASP) certification helps purple teamers meet that need by providing verifiable skills to ethically attack AI systems. A few things worth noting about what the certification covers:

Adversarial testing and defensive validation: Trains professionals to perform complete adversarial testing cycles and produce defensive validation evidence directly aligned with what purple teams are expected to deliver.
AI offensive security techniques: Covers 20+ hands-on offensive AI security techniques, addressing the growing need for security professionals who can assess AI-specific attack surfaces.
MITRE ATLAS coverage: Includes 15+ MITRE ATLAS techniques, giving professionals a structured framework for AI threat emulation.
Tooling depth: Covers 20+ tools spanning offensive security, ML testing, fuzzers, and model robustness, building practical, hands-on capability rather than theoretical knowledge.

Every module of COASP is designed to provide comprehensive coverage that supports real-world execution through practical, hands-on training, not just theoretical knowledge.

Final Thoughts

So, what is a purple team in practice? It is not a “red team runs, and blue team defends” process. It is a tighter loop in which attack techniques are used to directly probe detections, and those detection gaps are turned immediately into fixes or new test cases. That only works when someone can operate in both mindsets: when one can think like an attacker while also understanding how the alerting and response logic will behave in production. It is a demanding role that rewards impact more than participation. If you are unable to translate findings into improved detections or stronger attack coverage, the exercise won’t be considered successful. Explore the Certified Offensive AI Security Professional (COASP) certification and see how it maps to where you want to go.

Frequently Asked Questions

What is a purple team in threat intelligence?

In threat intelligence, purple teaming uses real-world adversary tactics, techniques, and procedures (TTPs) to simulate the actual behavior of modern threat actors. It tests whether defensive controls can recognize and react to those actions using real intelligence rather than depending on hypothetical scenarios.

What is a purple team in threat modeling?

Purple teaming is used in threat modeling to verify and test different assumptions made during the modeling process. It puts those scenarios into practice to understand what works, as opposed to merely mapping theoretical threats. It helps verify which risks are relevant, which controls work, and where the model needs to be updated or improved for accuracy.

What is a purple team in cybersecurity?

In cybersecurity, purple teaming is a practice that combines the defensive (blue team) and offensive (red team) responsibilities in real time. They operate in a common cycle rather than treating defense and offense as separate tasks. They test attack methods, observe how defenders react, and close gaps promptly.