AlgoSec

Ever feel like managing network changes is a constant firefight? Many security teams spend more time chasing manual tasks than actually improving security. Based on our experience, here's a few expert tips to help create the right automation framework for your org: - You don’t need to leap to full automation overnight. Most teams start at Level 2 or 3, getting structure + smart policy-change recommendations. - Visibility and control remain key. As automation increases, validation and risk assessment stay tightly managed. - High-value automation frees your team. At Level 5, low-risk changes can be auto-implemented, letting SecOps focus on higher-impact work. - Zero-touch isn’t a pipe dream. By Level 6, many change requests run automatically with human oversight where it matters most. The takeaway? Even small steps in automation can reduce risk, speed up changes, and give your team back time to focus on strategy.

Most security teams know they need more automation, but few know where they actually stand. Modern networks are too complex for manual change processes, yet many organizations are still stuck somewhere between spreadsheets and “semi-automated” workflows. A structured maturity model can help you see the gap and the next step. Quick pulse check: Where’s your team today? Once you've selected your level, tell us what’s helping you move forward or what’s holding you back in the comments.

Even mature cloud teams are still tripping over policy blind spots and independent research from GigaOm confirms. Below are the 3 biggest pitfalls found in the GigaOm report and share our expert take on what they mean for network security teams. We feel a tiny bit qualified to give our expert take because GigaOm name AlgoSec in the report an Outperformer for addressing these same challenges. Which of these priorities is most urgent for your team? #gigaom #NetworkSecurity #HybridEnvironments #cloudsecurity

As security leaders experiment with AI-driven automation, the real challenge isn’t just running 20x faster. It’s doing so while maintaining control, agility, and security guardrails that keep operations safe. The promise of AI in security automation isn’t about replacing human oversight — it’s about amplifying it. When done right, AI becomes the force multiplier for efficiency and precision, allowing teams to automate confidently without sacrificing visibility or compliance. The key question for every CISO right now: Where can AI truly enhance our efficiency and where do we still need human judgment to keep risk in check?

"With 60 percent of organizations now managing at least 250 business applications across hybrid multi-cloud environments, relying on traditional firewall policy-based network security is no longer effective. Building security around networks and infrastructure creates blind spots, inconsistent policies, and a higher risk of misconfigurations and downtime. These challenges only intensify as more applications are deployed and existing applications require updates. Applications are the backbone of modern business, and security strategies need to be aligned accordingly." That is the wisdom and expertise from our Field Chief Technology Officer, Kyle Wickert showcased in Solutions Review's Cybersecurity Awareness Month expert opinion roundup.

A staggering 39% of organizations admit to a critical lack of full visibility, meaning their security teams lack full knowledge of what’s running in significant parts of their cloud network (per our report). And an additional 23% of security incidents in the last year were directly linked to assets that were either unmonitored or riddled with misconfigurations. This lack of control has a direct and measurable impact on your risk profile. On average, it takes organizations too long to discover a new, unauthorized cloud asset, leaving a massive window of opportunity for attackers to exploit. The consequences are severe. Achieving total visibility isn’t as simple as flipping a switch. The blind spots in your cloud environment are a symptom of fundamental architectural and operational challenges: - Decentralized DevOps: Modern DevOps practices empower your teams to deploy and manage their own infrastructure, but this can bypass your traditional security gates. New assets are often created and then forgotten, leading to a sprawling and unaccountable network that you can’t fully secure. - Multi-cloud sprawl: When you use multiple cloud providers—AWS, Azure, GCP, and more—you are forced to grapple with different APIs, security tools, and data formats. This makes it virtually impossible for your security team to get a unified view of your entire environment without a centralized solution. - The rise of shadow IT: The ease of spinning up cloud resources and subscribing to SaaS applications has created a new security nightmare. When your business units or individual employees bypass official IT channels, they create unmanaged endpoints that you cannot see or protect. - Cloud misconfigurations: With thousands of configuration options, even a small error—like an open S3 bucket or an overly permissive firewall rule—can expose your sensitive data. These misconfigurations are difficult to track manually and often go undetected until a breach occurs. The question isn’t whether you have blind spots—it’s how quickly you can find and fix them. How are you approaching unified visibility across multi-cloud and DevOps-driven networks today?

In 2026, the question won’t be “Can we automate?”, it’ll be “Can we trust what we’re automating?” Hybrid networks have evolved faster than the tools meant to secure them. That’s how visibility gaps turn into risk blind spots. Fragmentation makes “visibility” feel like a patchwork puzzle and without a unified view, automation can’t deliver on its promise of speed and control. The future of network security isn’t just automation; it’s trusted automation, built on consistency, context, and connected visibility. How close is your organization to a truly unified view of your hybrid network?

What's intelligent automation? We're so glad you asked! Intelligent automation combines AI with other advanced technologies to automate and streamline complex, repetitive tasks. It provides a single source of visibility into security and compliance issues across a hybrid network environment in order to ensure ongoing adherence to internet security standards, as well as industry and internal regulations. Our approach to change management leverages intelligent automation and is characterized by six distinct levels, where each level is defined by how much human interaction is required. Here’s a brief look at each level of automation as it moves towards reducing manual interactions: 1. Manual Control At the initial stage, security operators are primarily responsible for planning and executing network-related tasks. AlgoSec provides essential visibility tools that offer insights into network structures, security policies, and potential risks. 2. Assisted Control Security operators are introduced to a security management solution that includes a structured workflow to facilitate efficient task execution. While the workflow can be audited, operators continue to manually carry out various activities within the provided framework. 3. Partial Automation This is the transition towards intelligent automation where security operators receive assistance from AlgoSec’s policy management but own responsibility for change validation and approval. 4. Conditional Automation In this stage, the security operator’s workload decreases and rule changes are being implemented automatically on the different devices. Risk is automatically identified and the operator’s focus shifts toward validating and authorizing the recommended modifications. 5. High Automation By creating a customized risk profile, the security management solution automatically handles low-risk changes, freeing up security operators to focus on critical tasks. Integration with external solutions is recommended for a more tailored and sophisticated approach to automation. 6. Very High Automation At the highest level, AlgoSec’s policy management solution processes the majority of change requests submitted. While security operators still play a role in specialized cases, this level of automation allows the solution to operate seamlessly, ensuring a highly efficient and reliable network environment. Throughout the process, AlgoSec centers each organization’s unique operational capabilities and philosophical perspectives, including customizing the automation process to create a tailored approach and timeline. The goal is to help organizations fully understand the individual levels and their value prior to continuing on the automation journey. Which level of automation do you see your organization currently at? Does your organization have goals to increase it's level of automation?

Hybrid-cloud security is getting too complex for humans alone. AI just isn’t a helper anymore—it’s your co-pilot. We’re moving from “detect and respond” to “anticipate and prevent.” From scattered policies to unified visibility across every environment. The real question isn’t if AI belongs in your security stack — it’s where and how much autonomy you’re ready to give it. Where do you think AI belongs in your security stack and how much autonomy do you think it should have? #CloudSecurity #AI #RiskManagement

We are honored to be recognized as a Customers’ Choice in the Gartner Peer Insights “Voice of the Customer” report for Network Automation Platforms for the second year in a row. A special thanks goes out to you - our customers. Your continued trust and invaluable feedback enable us to drive innovation to help organizations secure application connectivity across their hybrid environments. See link to the report in the first comment👇