To build an unbreakable fortress, you must first learn every way to tear it down. This is the central tenet of Red Teaming, a practice that feels modern and technical but whose DNA is forged in the crucible of military history. Before we ever applied it to algorithms and networks, we applied it to battle plans and national strategy.
Understanding these origins is not an academic exercise. The principles developed over centuries of conflict—challenging assumptions, thinking like an unconstrained adversary, and identifying catastrophic blind spots—are the very same principles you will use to test the security and safety of artificial intelligence systems.
From Wargames to War Rooms
The formal concept of Red Teaming began in the 19th century with the Prussian military’s development of Kriegsspiel, or “wargame.” This wasn’t a simple board game; it was a rigorous, rules-based simulation where officers were divided into two teams. One team, the “Blue” force (representing their own army), would develop a plan of attack. The other, the “Red” force, was tasked with a single, critical objective: to think and act like the enemy and defeat the Blue team’s plan.
The results were revolutionary. Plans that seemed perfect on paper crumbled when subjected to the scrutiny of an active, intelligent opponent. The Red team wasn’t just checking for errors; they were exploiting weaknesses in logic, timing, and resource allocation that the planners, trapped in their own perspective, could not see.
This “Red vs. Blue” paradigm was formalized and expanded during the Cold War. Military and intelligence agencies in the West designated “Red Teams” to simulate the tactics, doctrine, and political motivations of the Soviet Union and its allies. The goal was to move beyond caricature and develop a genuine understanding of the adversary’s decision-making process. This prevented “mirror-imaging”—the dangerous assumption that your opponent thinks and acts just like you do.
The Philosophy: Beyond Finding Flaws
A common misconception is that a Red Team’s job is simply to “break things.” While finding vulnerabilities is an outcome, it is not the primary purpose. The true value of military-derived Red Teaming lies in its ability to force a fundamental shift in perspective.
The core philosophy rests on three pillars:
- Challenging Assumptions: Every strategic plan is built on a foundation of assumptions. The Red Team’s job is to identify and stress-test every single one. What if the enemy doesn’t attack where we expect? What if they have a capability we’ve underestimated? What if our intelligence is wrong?
- Breaking Groupthink: When a team works together on a plan, a powerful consensus can form, making it difficult for internal members to voice dissent or point out flaws. The Red Team is an external, sanctioned force of disruption, empowered to challenge that consensus without fear of reprisal.
- Adversarial Empathy: A great Red Team doesn’t just simulate an enemy; it *becomes* the enemy. It adopts their goals, their risk tolerance, and their unique worldview. This empathetic approach uncovers strategies that would be unimaginable from the Blue team’s perspective.
Following the intelligence failures preceding the 9/11 attacks, the U.S. intelligence community formally adopted this methodology. The CIA created a “Red Cell” specifically to author alternative analyses and challenge the mainstream conclusions of intelligence reports, ensuring that dominant theories were always rigorously questioned.
The Bridge to the Digital Battlefield
The transition from military strategy to cybersecurity was a natural one. The concepts mapped almost perfectly. The “battlefield” became corporate and government networks, the “enemy” became hackers and malicious actors, and the “plan” became the defensive security posture. The core need—to challenge assumptions and see the system through an attacker’s eyes—remained unchanged.
As you will see throughout this handbook, AI Red Teaming is the next logical step in this evolution. The principles forged in Kriegsspiel are directly applicable to testing the logic and safety of a large language model. The following table illustrates how the core concepts have evolved while retaining their fundamental essence.
| Concept | Military Red Teaming (Origin) | Cybersecurity Red Teaming | AI Red Teaming (Modern Application) |
|---|---|---|---|
| The “Blue” Asset | A battle plan, a military strategy, a national policy. | A computer network, a software application, a company’s security posture. | An AI model, a data pipeline, an AI-powered product, an autonomous system. |
| The “Red” Adversary | An enemy nation-state, an insurgent group, a terrorist cell. | A black-hat hacker, a state-sponsored actor, a malicious insider, a script kiddie. | A sophisticated attacker, a curious user, a misaligned sub-system, or the model’s own emergent behaviors. |
| The Battlefield | Physical terrain, political landscape, logistical supply chains. | Digital infrastructure, network protocols, human users (social engineering). | Model parameters, training data, inference logic, user prompts, API endpoints, safety filters. |
| Core Objective | Ensure the plan is robust, identify fatal flaws before lives are lost, and understand the enemy’s likely course of action. | Identify exploitable vulnerabilities before they are found by real attackers, test incident response, and improve overall security. | Discover harmful capabilities, security vulnerabilities, ethical biases, and unforeseen failure modes before the AI system causes real-world harm. |
By rooting our modern practice in this rich history, we equip ourselves with a time-tested mindset. You are not just a tester; you are the adversary’s advocate, tasked with bringing a necessary and uncomfortable truth to light. That is the legacy of Red Teaming.