The Platform

Enable your security and operations teams to proactively identify, prioritize, and remediate exposures to stay ahead of attackers.

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GigaOm Radar for Attack Surface Management

The expansion of an organization's attack surface continues to present a critical business challenge. Download the GigaOm Radar for Attack Surface Management to get an overview of the available ASM solutions, identify leading offerings, and evaluate the best solution for you.  

Use Cases

The CyCognito platform helps you identify all of the attacker-exposed assets in your IT ecosystem for a complete view of your attack surface.

State of External Exposure Management

Download CyCognito’s State of External Exposure Management Report to learn key recommendations that your Security teams can implement to improve their exposure management strategy and minimize risk. 

Our Customers

External attack surface management is advancing cybersecurity into a new era. Learn how security experts across all industries benefit from using CyCognito’s platform.

The Total Economic Impact™ of The CyCognito Platform

Read The Total Economic Impact™ of The CyCognito Platform — a Forrester study. Cost Savings And Business Benefits Enabled By The CyCognito Platform. 

About CyCognito

We believe all organizations should be able to protect themselves from even the most sophisticated attackers.

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Resources

The knowledge you need to manage and protect your attack surface.

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AI at CyCognito

CyCognito has integrated AI to power robust and accurate attack surface discovery and testing. Discover what CyCognito AI can do for you and the AI techniques we use.

What You Can Do with CyCognito’s AI

Discover All of Your Assets

CyCognito’s asset discovery process starts with a single data point - the name of your organization - and then uses AI to crawl and understand financial databases, news sites and hundreds of websites.

Get Full Asset Context

CyCognito builds context around all of the assets it discovers. Our AI maps each asset to a business unit or brand, and adds details like the type of asset, underlying technology, related applications, and if there is potentially exposed customer data.

Classify Assets by Type or Risk

Assets can be easily organized by type or risk. Our AI classifies assets by examining their API call responses and types of data they store.

Ask Any Question

Want to see all of your ecommerce servers not protected by a WAF? Just ask: “Show me all ecommerce servers not protected by a WAF.” Our AI language processing allows you to ask almost any question about what you own and if it’s at risk without using a specialized query language.

Automatically Configure Tests

No more time consuming test configuration. Our AI understands the type of assets you own and automatically configures the test engine to run the proper test types with the right payloads.

Can Humans Keep Up with Discovery?


Assuming a human could find all of the information the CyCognito platform does (up to fifty data points per asset, including IP address, name, type, owner, location, included technologies, related assets, known vulnerabilities, and threats), we estimate it would take at least one hour per asset on average for initial discovery and 30 minutes per asset to keep all of the asset metadata up to date.

So, one hour per asset, multiplied by a midsized attack surface of 5,000 assets, that's 5,000 hours, or over two work-years just for initial discovery. Spending 30 minutes per asset once per year to keep it up to date would add another 2,500 hours - over one additional work-year. On top of that, company attack surfaces fluctuate by +/- 10 percent monthly, adding even more hours of initial discovery per year for newly added assets. Lastly, the average attack surface size for an enterprise is 50,000 assets, not 5,000. That’s 30 work-years.

AI Techniques CyCognito Uses

CyCognito uses a number of AI techniques and technologies to create high-precision discovery and testing. Let’s look at some of them and how they are applied in the platform.

Bayesian Machine Learning (BML)

CyCognito uses BML to structure graph data models and test hypotheses around asset ownership and type.

Generative Pre-trained Transformers (GPT)

CyCognito uses GPT to summarize the relationship between organizations or entities and to create answers to user search queries.

Generative AI (GenAI)

CyCognito uses GPT-3.5/4 to summarize the relationship between organizations or entities, and to create answers to user search queries.

Graph-based AI (GraphAI)

CyCognito uses GraphAI to represent assets and their relationships to organizations, people, threats and other technologies.

Large Language Models (LLMs)

CyCognito uses LLMs for several tasks, including asset discovery, ownership attribution, data enrichment, and search.

Natural Language Processing (NLP)

CyCognito uses NLP to understand organizational structure by extracting information from business databases and websites, and then matching entities mentioned within. NLP has a significant performance advantage over LLMs - milliseconds vs. seconds - and is a better choice for large scale applications like attack surface discovery.