When we think of digital pipelines, we often think of developers, not defenders. However, in the age of AI, threats are evolving much faster than ever. Now more than ever, pipelines have become equally important to developers, cybersecurity, network security, and anti-fraud professionals alike.
We all know DevOps pipelines. This is the infrastructure on which the modern mobile economy is built. Pipelines are used to bring Android & iOS apps to market, ingest, analyze, and visualize user and application data, and provide the necessary orchestration and management layer to ensure everything runs smoothly. Pipelines also form a critical foundation on which to leverage Agentic AI coding or “Coding Assistants” to boost developer productivity and gain a competitive advantage.
Today, defenders – like cybersecurity, network security, and anti-fraud specialists – don’t use pipelines to deliver needed protections into applications. Instead, they often choose point products and, in doing so, slow down their own AI-driven future. Bottom line, there is no AI-driven future – for developers or defenders – without pipelines.
What’s a Pipeline?
A digital “pipeline” is a series of connected systems that automate actions, process digital assets (code, data, etc.), and move digital assets from one stage to the next using data and rules defined by the business. Think of a pipeline as the infinite loop of innovation required to build complex products. A pipeline breaks tasks into manageable, repeatable steps, uses data to improve products, and increases engineering, business, and operational outputs.
Why AI Needs Pipelines
AI (LLMs) and Agentic AI applications have impressive capabilities. They can generate code, perform analysis, and synthesize large unstructured data sets. But, AI needs data and the code that flows through pipelines to gather context, provide insight, and take action. Without pipelines, data or otherwise, AI and machine learning models have nothing to process, and AI coding assistants like Co-Pilot and Cursor have no context to write code. Pipelines bring the needed data, context, and system-level points of ingress and egress to the AI models that fuel the future.
Point Products Are Not a Pipeline
To protect the business, security and anti-fraud teams will typically try to assemble a patchwork of point products, each designed to address a specific threat or set of vulnerabilities. However, this approach creates gaps and several points of friction that conflict with a pipeline approach to protecting the brand and business. Here’s how:
- Manual Integration, Maintenance, Response: Security, anti-fraud and anti-bot point products typically require a significant amount of manual work, maintenance and intervention. From the initial implementation or remediation efforts, to fine-tuning configurations, to triaging crashes or resolving conflicts, point products create a lot of work that cyber and development teams don’t have the resources to complete.
- Siloed Threat Data: Each point product stores its own data, often without integration across other systems. This creates a lack of visibility into the bigger picture, slowing down incident response and making deep threat analysis and research an impossibility.
- Defense Gaps & Solution Conflict: Security and Anti-Fraud products from different vendors often impose conflicting enforcement models inside apps. Adding more point products create an environment where these solutions fight against one another, introducing friction and leading to shelfware – or entire areas in the application left unprotected.
Point products are either too slow or too narrow to create an infinite loop of defense innovation needed to keep up with AI-driven threats. Moreover, because the business’s DevOps pipeline produces constant innovation, security, anti-fraud and anti-bot implementations become stale fast. In short, you can’t build a cyber pipeline out of point products.
How to Build a Cyber pipeline
At a basic level, cyber pipelines should be focused on automating tasks, leveraging consolidated threat data, and using AI to ensure that security and anti-fraud measures evolve as quickly as the app, OS and threats they seek to address.
To do this requires:
- Workflow Automation: A cyber pipeline is, at its core, workflow automation. It’s a system for eliminating repetitive or manual tasks, reducing human error, and increasing operational efficiency. Done right, it also creates digital records or “memories” that serve as the operational foundation for AI models to plug into.
- Learning Systems: Cyber pipelines must leverage learning systems to perform critical integration and remediation processes autonomously. Learning systems increase agility and speed by addressing compatibility, implementation consistency and adaptability of defenses on the fly. Learning systems can also feed Agentic AI models or provide feedback to the business including developers, DevSecOps teams and fraud analysts.
- Universal Threat Data: A true cyber pipeline must aggregate threat data from security, anti-fraud, scam, ATO and bot detections under a single pane of glass. This creates the needed “data pipeline” for AI to perform deep threat analysis and, armed with global data sets, allows the system to benchmark and manage defense posture against global, regional or industry specific threats.
- Continuous Response & Improvement: Threats evolve rapidly, and so too must the response. With a cyber pipeline, security teams can react to threats in real-time, minimizing damage and preventing future attacks. On top of that, a cyber pipeline doesn’t just react to threats—it predicts them. By integrating AI-powered predictive threat detection, businesses can anticipate fraud, bot attacks, and other malicious activities and build defenses before the attacks even happen.
Instead of adding point products to patch vulnerabilities, organizations should leverage a platform to create a unified cyber pipeline that continuously evolves and adapts. The key advantage here is agility. Pipelines allow businesses to deploy new security measures as quickly as they deploy new features, ensuring that security is never an afterthought but an integral part of the business process.
The Future of Cybersecurity is Pipelines
Much like its DevOps counterpart, a cybersecurity pipeline is a continuous, automated workflow of constant innovation and improvement designed to keep mobile businesses secure and resilient against threats in real time. A pipeline approach to protecting the mobile brand, user, and business delivers not only faster deployment, agility, and instant compatibility but also a more innovative approach to threat defense. By adopting this modern, holistic strategy, businesses can protect their mobile revenues and ensure that their security and anti-fraud measures grow as quickly and effectively as their mobile products. In a world where speed and sophistication rule, it’s time for CISOs to start building cyber pipelines that can keep pace with new AI-based threats and the pipeline innovation that drives the mobile business.
