Resolving digital threats 100x faster with OpenAI

随着数字威胁变得更加复杂和针对性强，企业安全团队面临着更高频率处理更多警报的压力。

大多数替代方案仍依赖第三方承包商手动审核被标记的内容——这一过程可能缓慢、不一致且成本高昂。Outtake（https://www.outtake.ai/）重新构想了这一系统，采用全天候运行的AI代理，每分钟扫描数百万个表面区域，如网页、应用商店列表和广告，构建可信与可疑实体的地图。该地图帮助安全团队了解事件发生的情况、背后人员，并在数小时内提供专家审核的解决建议。

Outtake系统基于GPT-4o和OpenAI o3，提供全天候威胁覆盖，无需积压工单，使网络安全团队能够以准确和快速的方式领先于快速变化的威胁。

Outtake创始人兼CEO Alex Dhillon表示：“安全威胁现在每小时都会变异，OpenAI的模型使我们的防御能够同样快速应对。借助这些模型，我们能够构建和自动化此前无法实现的工作流程部分，这得益于这一代具备自主性的AI。”

使用GPT-4.1和OpenAI o3更快地检测和分类攻击

Outtake平台的核心是一套可定制的AI代理系统，设计用于调查数字威胁并执行执法决策，所有操作均由GPT-4.1和OpenAI o3协调。客户可以配置经过验证的白名单、品牌指南、知识产权政策和执法偏好，然后通过自然语言训练代理。

部署后，代理持续爬取应用商店、网站、社交平台和广告等表面区域，规模化收集和解读原始信号。

GPT-4.1处理多模态输入，如截图、文字记录和嵌入的视觉内容，即使信号隐藏在图像或视频中，也能发现潜在威胁。

Outtake的验证通信网络：AI代理扫描表面区域，绘制可信与可疑实体的地图。

使用最佳匹配模型进行风险分类

每个发现都会被评分以评估严重性。GPT-4.1对滥用类型进行分类，如网络钓鱼、冒充或版权侵权，并判断系统是否应采取行动。

OpenAI o3跨平台关联信息，揭示更大范围的模式，例如当一个仿冒域名、一个相似应用和一个假社交账号指向同一滥用活动时。Outtake正致力于更高级的推理，帮助代理检测孤立情况下可能被忽视的协调威胁。

Outtake客户可掌控决策逻辑。代理遵循预设规则，但安全和法律团队可介入边缘案例或覆盖决策。客户反馈可实时纳入，使代理无需重新训练或工程改动即可适应新规则和威胁。

Outtake系统架构图展示了由OpenAI模型驱动的多阶段网络攻击解决流程。 （图示链接：https://images.ctfassets.net/kftzwdyauwt9/bJ5ME7EM5YCBsjHYKVHkD/186b98f1ed105df12fc811ed2eeae4ae/oai_Outtake_Architecture_diagram_Lightmode.svg?w=3840&q=90）

通过函数调用实现精准快速的行动

一旦案件符合执法标准，函数调用功能允许代理自动汇总相关证据，起草并提交解决通知。这些操作快速完成，且有日志记录和可审计，输出内容优化以满足各平台的合规要求。

Outtake将下架时间从60天缩短至数小时，帮助企业客户避免数百万美元的欺诈损失。这种速度得益于AI代理承担了调查的繁重工作，释放分析师专注于最终审核和新威胁。

领导Outtake模型的准确性和推理能力评估

Outtake代理在复杂且高风险的环境中运行，跨平台和多格式推理至关重要。驱动它们的模型必须检测细微模式，关联相关信号，并生成经得起审查的输出。

内部评估显示，OpenAI模型在推理准确性方面持续优于其他替代方案。这一表现使Outtake有信心在不牺牲质量的前提下扩展系统，实现具备自主性的AI以快速且一致地处理大量执法任务。

Dhillon表示：“我们建立了内部系统，根据网络安全特定的关键绩效指标评估新模型。始终没有任何模型能在当前价格点上接近OpenAI的可靠性，尤其是在代理需要处理复杂多模态信号的多步骤推理时。这种跨不同表面区域的多步骤推理是产品可行性的关键。”

利用OpenAI智胜下一代攻击

随着数字威胁日益复杂且数量激增，Outtake正在扩展其防御系统，帮助客户加强网络身份认证，促进人机在线更透明的沟通。维护这一不断扩展的数字环境中的信任，需要能够跨上下文、模态和意图进行推理的代理，这也是Outtake持续依赖OpenAI模型作为系统核心的原因。

Dhillon说：“OpenAI模型赋予我们与威胁匹配的速度和推理能力。我们将继续与OpenAI合作，使我们的代理能够像攻击一样快速适应。”

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As digital threats become more sophisticated and targeted, enterprise security teams are under pressure to respond to more alerts at a higher frequency.

Most alternative solutions still rely on third-party contractors to manually review flagged content—a process that can be slow, inconsistent, and expensive. Outtake⁠ reimagines that system with always-on AI agents that scan millions of surface areas, such as webpages, app store listings, and ads, per minute, building a map of trustworthy and suspicious entities. That map helps security teams understand what’s happening, who’s behind it, and route resolution recommendations for expert review in a matter of hours. 

Built with GPT‑4o and OpenAI o3, Outtake’s system offers 24/7 threat coverage with no ticket backlogs, enabling cybersecurity teams to stay ahead of fast-changing threats with accuracy and speed.

“Security threats now mutate every hour, and OpenAI’s models make it possible for our defense to move just as fast,” says Alex Dhillon, Founder and CEO of Outtake. “The models make it possible to build and automate parts of this workflow that weren’t feasible before this generation of agentic AI.”

Detecting and classifying attacks faster with GPT‑4.1 and OpenAI o3

At the core of Outtake’s platform is a system of customizable AI agents designed to investigate digital threats and carry out enforcement decisions, all orchestrated by GPT‑4.1 and OpenAI o3. Customers configure verified whitelists, brand guidelines, intellectual property policies, and enforcement preferences, then train the agent using natural language. 

Once deployed, the agents continuously crawl surfaces such as app stores, websites, social platforms, and ads to collect and interpret raw signals at scale. 

GPT‑4.1 processes multimodal inputs like screenshots, transcripts, and embedded visuals, surfacing potential threats even when signals are buried inside images or videos.

Outtake’s verified communication network: AI agents scan surface areas and map trustworthy and suspicious entities.

Classifying risk with best-fit models

Each finding is scored for severity. GPT‑4.1 classifies the abuse type, such as phishing, impersonation, or copyright violation, and determines whether the system should take action. 

OpenAI o3 connects the dots across platforms to reveal larger patterns, like when a spoofed domain, a lookalike app, and a fake social account all point to the same abuse campaign. Outtake is building toward higher-order reasoning that helps agents detect coordinated threats that might otherwise go undetected in isolation.

Outtake customers stay in control of the decision-making logic. Agents follow predefined rules, but security and legal teams can intervene on edge cases or override decisions. And customer feedback can be incorporated in real time, allowing Outtake’s agents to adapt to new rules and threats without retraining or engineering changes.

Taking precise, quick action with function calling 

Once a case meets enforcement criteria, function calling allows the agent to automatically compile the relevant evidence, draft and file a resolution notice. These actions are taken quickly and are logged and auditable, with outputs optimized to meet the compliance requirements of each platform.

Outtake has reduced takedown timelines from 60 days to just hours and helped enterprise customers avoid millions in fraud losses. This speed is possible because the AI agent handles the investigative grunt work, freeing analysts to focus on final reviews and new threats.

Leading Outtake’s model evaluations for accuracy and reasoning

Outtake’s agents operate in complex, high-stakes environments where reasoning across platforms and formats is essential. The models powering them must detect subtle patterns, connect related signals, and generate outputs that hold up under scrutiny. 

In internal evaluations, OpenAI models consistently outperform alternatives, particularly across reasoning accuracy. This performance gives Outtake the confidence to scale its system without compromising on quality, enabling agentic AI to handle high volumes of enforcement with speed and consistency.

“We’ve built an in-house system to evaluate new models against cybersecurity-specific KPIs,” says Dhillon. “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.

Outsmarting the next generation of attacks with OpenAI 

As digital threats grow more sophisticated and scale in volume, Outtake is extending its defense system to help customers strengthen identity across their networks and foster more transparent communication between humans and AI online. Maintaining trust in this expanding digital landscape requires agents that can reason across context, modality, and intent, which is why Outtake continues to rely on OpenAI models at the core of its system.

“OpenAI models gave us the speed and reasoning to match the threat,” says Dhillon. “We’re continuing to build with OpenAI so our agents can adapt just as quickly as the attacks do.”

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