Threat Scenario: A nation-state actor launches a sophisticated cyberattack against a major cloud provider, causing a multi-day outage of core compute and storage services. An AI-powered medical diagnostic tool, hosted on this cloud, becomes unavailable. A hospital relying on the tool for time-sensitive analyses faces critical delays, leading to adverse patient outcomes. The AI provider’s contract contains a standard “force majeure” clause. Does a cyberattack of this scale absolve them of liability?
This scenario cuts to the core of why force majeure clauses—often considered boilerplate legal text—demand scrutiny in the age of AI. A force majeure event is an unforeseeable, external circumstance that prevents a party from fulfilling its contractual obligations. While traditionally covering “acts of God” like earthquakes or floods, the interconnected and fragile nature of the digital infrastructure powering AI systems introduces a new class of potential catastrophic failures.
Redefining “Unforeseeable” for AI Systems
The central pillar of a force majeure defense is that the event was beyond the party’s reasonable control and could not have been anticipated. For AI systems, this definition is fraught with ambiguity. While a volcanic eruption is clearly external, what about a systemic failure caused by an unpredicted emergent behavior in a complex model? Or a widespread data poisoning attack that silently corrupts a foundational model over months?
As a red teamer, your work directly informs this ambiguity. By demonstrating novel attack vectors or cascading failure modes, you challenge the very notion of what is “unforeseeable.” An exploit that your team discovers and documents is, by definition, no longer unforeseeable for the organization.
Force Majeure Event Chain in an AI Context
Expanding the Scope: From Natural Disasters to Digital Catastrophes
Standard force majeure clauses are often ill-equipped for AI-centric risks. Your legal team must work with technical experts—including red teamers—to draft clauses that reflect the operational realities of AI. This means explicitly addressing events that, while not “acts of God,” have a similar crippling effect.
| Traditional Force Majeure Events | AI-Specific Considerations & Additions |
|---|---|
| Earthquake, hurricane, flood, fire | Catastrophic hardware failure at a single-source GPU provider or specialized chip foundry. |
| War, terrorism, civil unrest | State-sponsored cyberattacks on critical infrastructure (e.g., cloud providers, core internet routers) that are qualitatively different from typical DDoS or ransomware attacks. |
| Strikes, labor disputes | Sudden, legally mandated revocation of access to a critical dataset or foundational model due to regulatory changes (e.g., privacy law, national security). |
| Epidemic, pandemic | Unanticipated “model pandemic” where a vulnerability in a widely used open-source library or foundational model leads to cascading, systemic failures across the industry. |
| Governmental action, embargo | An abrupt change in government policy rendering a key algorithm or data source illegal, or a sudden sanction preventing use of a foreign cloud provider. |
Red Team’s Role in Shaping Force Majeure Clauses
Your objective is not to practice law, but to provide the technical evidence needed to draft robust, realistic, and defensible contracts. When testing an AI system, consider the following in the context of force majeure:
- Dependency Mapping: Identify all critical external dependencies—cloud providers, data feeds, open-source models, APIs. A failure in any of these could be a trigger event. Are there redundancies? If not, the risk may be considered foreseeable and thus not covered by force majeure.
- Cascading Failure Simulation: Model what happens if a core dependency fails. Does the system fail gracefully? Does it have a “limp mode”? A system that collapses catastrophically from a single external failure is less likely to be protected by a force majeure clause, as the brittleness of the system itself contributed to the damage.
- Defining “Catastrophic”: Work with legal and business teams to quantify what constitutes a catastrophic cyberattack. Is it defined by duration (e.g., >48 hours of downtime), scope (e.g., affecting multiple geographic regions), or attribution (e.g., officially attributed to a nation-state actor)? Your threat models can provide realistic parameters.
- Testing Mitigation Strategies: If the contract states that the party must take reasonable steps to mitigate the effects of a force majeure event, you should test those mitigation procedures. Do the data backup and recovery plans actually work under duress? Can the system be migrated to an alternate provider in a realistic timeframe?
Ultimately, a well-defined force majeure clause in an AI service agreement acts as a clear line of demarcation for liability. It protects providers from truly uncontrollable events while ensuring they remain accountable for building resilient, secure systems capable of withstanding the foreseeable chaos of the digital world. Your role as a red teamer is to relentlessly probe that line, ensuring it is drawn with technical reality, not legal fiction.