Outtake Cybersecurity Agents powered by OpenAI
Outtake has developed a system of AI agents powered by GPT-4.1 and OpenAI o3 that automates the detection and resolution of cybersecurity attacks, reducing takedown timelines from 60 days to a few hours. This agentic approach allows enterprise security teams to resolve threats in hours rather than weeks by automating the investigation and enforcement process.
Automated Threat Detection and Classification
Outtake utilizes customizable AI agents to continuously scan millions of surface areas—including app stores, websites, social platforms, and advertisements—to map trustworthy and suspicious entities. These agents are configured using natural language based on customer-defined whitelists, brand guidelines, and intellectual property policies.
Multimodal Signal Processing
GPT-4.1 is used to process multimodal inputs, such as screenshots, transcripts, and embedded visuals. This capability allows the system to identify potential threats even when signals are hidden within images or videos, ensuring that threats are not missed due to format limitations.
Risk Classification and Pattern Recognition
Outtake employs a dual-model strategy to classify risk and identify coordinated attacks:
- GPT-4.1 classifies the specific type of abuse, such as copyright violations, impersonation, or phishing, and determines if action is required.
- OpenAI o3 is used for higher-order reasoning to connect signals across different platforms. This allows thetake system to identify larger abuse campaigns where a spoofed domain, a fake social account, and a lookalike app are all linked to the same threat actor.
Automated Enforcement via Function Calling
When a detected case meets predefined enforcement criteria, Outtake uses function calling to automate the resolution process. The agents automatically compile evidence and draft and file resolution notices. These actions are logged and auditable to ensure they meet the compliance requirements of various platforms.
Security and legal teams maintain control over the decision-making logic. While agents follow predefined rules, human experts can intervene in edge cases, override decisions, and provide real-time feedback to adapt the agents to new threats without requiring engineering changes or retraining.
Performance and Model Evaluation
Outtake has implemented an in-house system to evaluate models against cybersecurity-specific KPIs. According to Outtake CEO Alex Dhillon, OpenAI models consistently outperform alternatives in reasoning accuracy and reliability, particularly when reasoning through convoluted, multimodal signals across disparate surface areas.
"Consistently, none come close to the reliability we get from OpenAI at current price points, especially when the agent has to reason through convoluted, multimodal signals. That kind of multi-step reasoning across disparate surface areas is what makes the product viable."
By automating the investigative "grunt work," Outtake enables security analysts to focus on final reviews and the emergence of new threats, helping enterprise customers avoid millions in fraud losses.