CrowdStrike Secures the Growing AI Attack Surface with Falcon AI Detection and Response

In classical security architectures, control is focused on executable code, network traffic, and identities. In the case of AI, the focus shifts to prompt-based interactions, the context of model responses, and agent actions that can issue requests or alter system states without direct human intervention.

Falcon AIDR focuses precisely on this layer. The solution analyzes the entire chain of “prompt, response, agent action” and applies security policies at runtime. For organizations, this represents a shift from reactive control of consequences to proactive management of AI interactions before they impact data or business logic.

To ensure AI control and security in corporate environments, Falcon AIDR uses a multi-layer architecture that covers the full lifecycle of AI interactions — from prompt requests and model operations to autonomous agent actions and integration with SOC processes.

The solution is natively integrated into the Falcon platform and processes AI telemetry as systematically as data from endpoints, identities, and cloud environments.

Below is a generalized diagram of the Falcon AIDR architecture, illustrating how a unified visibility, detection, and response loop for AI threats is established.

The AI attack surface encompasses threats associated with prompt injections, model exploitation, and risks related to autonomous agents. All interactions with AI, including prompt queries, model responses, and agent actions, generate unified AI telemetry ingested by Falcon AIDR.

Within the core Falcon AIDR layer, the following capabilities are implemented:

• detection of AI-specific threats;

• real-time enforcement of security policies;

• automated incident response actions.

Analysis results are delivered to the SOC console, where AI incidents, activity logs, and investigation artifacts are generated. In parallel, these events are correlated with other Falcon platform domains, including identity protection, cloud security, and network detection. This enables AI risks to be assessed within a unified cybersecurity context.

This approach enables AI security to be integrated into existing SOC processes without introducing separate control planes. For organizations, this means AI adoption can scale alongside the business while remaining transparent and manageable from a security perspective.

CrowdStrike tracks more than 180 known prompt injection techniques, jailbreak manipulations, and model restriction bypass scenarios. Falcon AIDR leverages this knowledge to detect abnormal or potentially dangerous prompt inputs in real time.

The system analyzes the structure and content of prompt messages, the context of prior interactions, as well as behavioral anomalies in models and agents. This helps reduce the risk of situations in which AI could become a source of data leakage or perform actions that contradict business logic.

Falcon AIDR ensures control over which data is sent to AI models, including the detection of confidential information, personal data, and other sensitive categories. Security policies are enforced at runtime, enabling dangerous scenarios to be blocked or restricted before data leaves the controlled environment.

For businesses, this enables the use of AI without compromising compliance and without the need to restrict tools that enhance employee productivity.

Falcon AIDR places particular emphasis on protecting autonomous agents that can perform actions on behalf of users or systems. The solution monitors agent behavior, integrations, and interactions with other services, detecting anomalies and deviations from expected logic.

This is critical for organizations planning to scale AI automation across operational and mission-critical business processes.

Falcon AIDR does not operate in isolation from other components of the Falcon platform. AI security–related events are correlated with endpoint, identity, and cloud environment data, forming a comprehensive view of incidents.

This approach enables AI risks to be integrated into the overall cybersecurity strategy and treated as an integral part of the security architecture.

Falcon AIDR demonstrates a systematic approach to securing AI interactions, with control enforced at the level of logic, agent actions, and usage context. For organizations, this enables AI adoption to scale as a business capability while maintaining transparency, control, and compliance without adding operational complexity.

As AI transitions from an experimental capability to an operational one, security concerns shift toward continuous monitoring and response. Falcon AIDR integrates AI-related events into standard SOC processes, providing correlation, context, and automated response across the platform. This allows AI security to be embedded into the existing cybersecurity operating model without introducing separate operational silos.