AI-powered external exposure assessment at scale.

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April 14, 2026

CyCognito

Cyber threat intelligence

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AI-powered external exposure assessment at scale.

External Exposure Assessment Remediation Priorities Automated Security Testing Contextual Analysis AI-powered Risk Management Digital Footprint Interpretation

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Overview

AI at CyCognito is designed to assist with external exposure assessment on a large scale, validates the risk and directs remediation priorities. It leverages various AI technologies to offer a comprehensive solution for surveillance and risk management.

This includes intelligent discovery, where AI models aid in establishing associations between assets to generate a continuously updated interpretation of your digital footprint.

CyCognito uses semantic search aided by natural language processing that enables users to make data requests in plain language and receive useful responses.

Their contextual analysis feature uses AI to identify an assets function, underlying technology, and exposure traits, providing insights about potential attackers' interest to create a risk profile for prioritization.

Through adaptive testing, AI insights ensure tests are run comprehensively for each asset, adapting as the environment evolves for risk validation. In terms of security, they have automated security testing to focus on significant risks as the environment changes.

Moreover, AI-assisted logic is employed for routing each finding to the appropriate owner, providing clear remediation context and confirming that fixes are complete.

The AI technologies powering CyCognitos platform include Bayesian Machine Learning, Large Language Models, Generative AI models, Graph-based AI, and Natural Language Processing.

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May 1, 2024

Initial release of CyCognito.

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Cyber threat intelligence CyCognito

Cyber threat intelligence

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Pros and Cons

Pros

External exposure assessment

Validates risk at scale

Intelligent discovery

Updated digital footprint interpretation

Semantic search feature

Natural language data requests

Contextual analysis

Assets' function and exposure identification

Risk profile creation

Adaptive testing

Environment-evolving risk validation

Automated security testing

Clear remediation context provision

Fix completion confirmation

Bayesian Machine Learning

Large Language Models

Cyber threat intelligence

Asset association establishment

Potential attackers' interest detection

Comprehensive surveillance

Intelligent asset discovery

Automated exploit intelligence

Seedless discovery

Exposure context determination

Continuous risk validation

Risk prioritization

Remediation automation

Real World Impact Determination

True exposure separation

Material risk focus

Asset ownership prediction

Probabilistic graph models

Ownership attribution, business and risk enrichment

Relationship mapping and explanation

External relationships and exposure points connection

Plain language queries

Organizational data extraction and match

Live, connected map building

View 33 more pros

Cons

Complex implementation process

Possible high false positives

Absence of real-time risk monitoring

Risk classification may be subjective

Dependent on natural language input

Lack of third-party integrations

Adaptability takes time

Automated remediation context may be unclear

View 3 more cons

Q&A

What is CyCognito?

CyCognito is a platform that uses AI technology to assist with large-scale external exposure assessments, risk validation, and guidance on remediation priorities.

What is the function of AI in CyCognito?

AI in CyCognito assists in discovering and establishing associations between assets to generate a continuously updated interpretation of the digital footprint. It uses semantic search, aided by natural language processing, to enable plain-language data requests and generate useful responses. The AI also identifies an asset's function, underlying technology, and exposure traits, and provides insights about potential attackers' interest to create a risk profile for prioritization. Furthermore, AI insights ensure comprehensive testing of each asset and adapt to environmental changes for risk validation.

How does CyCognito's AI models aid in intelligent discovery?

CyCognito's AI models enable intelligent discovery by assisting in identifying and establishing associations between assets. It assesses the relationships between various assets to generate a continuously updated view of the organization's digital footprint, hence uncovering potential points of hidden risk across brands, subsidiaries, and external environments.

Can you explain CyCognito's semantic search feature?

The semantic search feature in CyCognito uses natural language processing to interpret user data requests made in plain language and to provide precise responses. Users don't need queries or filters because the system comprehends the request and returns appropriate results.

How does AI assist in the contextual analysis in CyCognito?

The AI in CyCognito performs contextual analysis by identifying each asset's function, underlying technology, and exposure characteristics. By providing insight into an attacker's possible interest, a risk profile is created to guide prioritization.

What are the different AI technologies powering CyCognitos platform?

The AI technologies powering CyCognito's platform include Bayesian Machine Learning, Large Language Models, Generative AI models, Graph-based AI, and Natural Language Processing.

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How does Adaptive Testing feature work in CyCognito?

Adaptive testing in CyCognito uses AI insights to determine how tests are run for each asset. As the environment evolves, the testing adjusts to validate the risks that matter most.

What is the role of AI in automated security testing in CyCognito?

AI plays a critical role in CyCognito's automated security testing by focusing on significant risks as the environment evolves. It drives test sequences for each asset type and automatically runs targeted checks.

How does CyCognito use AI for large-scale external exposure assessment?

CyCognito uses an AI-assisted system for large-scale external exposure assessment by identifying and verifying assets and their connections using AI-driven discovery. This helps in improving coverage in large, complex environments.

How does CyCognito validate risk?

CyCognito validates risk using AI-assisted validation that uses exploitability evidence, asset context, and threat signals to separate true exposures from noise, thus highlighting the highest priority risks.

Can you explain CyCognito's risk management capabilities?

In terms of risk management, CyCognito employs AI technologies to identify assets, establish connections, evaluate each asset's purpose, business role, and data sensitivity to turn technical findings into clear, actionable insights.

How does CyCognito's AI-assisted logic help in remediation priorities?

CyCognito's AI-assisted logic helps in remediation priorities by routing each security finding to the appropriate owner. It provides a clear remediation context and verifies that the fixes are complete, ensuring a verifiable process that reduces risk and makes accountability clear.

What is the role of CyCognito in surveillance?

CyCognito plays a significant role in surveillance by using AI technologies to continuously monitor and validate risks throughout the digital environment, thus ensuring comprehensive risk management and remediation processes.

Does CyCognito help in generating a digital footprint interpretation? How?

Yes, CyCognito helps in generating a digital footprint interpretation. It uses AI to identify and establish associations between assets, providing a continuously updated view of your digital footprint.

What is the purpose of Bayesian Machine Learning in CyCognito?

In CyCognito, Bayesian Machine Learning is used alongside probabilistic graph models to predict asset ownership and type, testing relationships across entities to boost accuracy and reduce false positives.

How does CyCognito utilize Large Language Models and Generative AI models?

CyCognito utilizes Large Language Models to support asset discovery, ownership attribution, business and risk enrichment, and enable natural-language search. The Generative AI models are used to map and explain relationships between entities and organizations, creating accurate, natural-sounding summaries and responses in real-time.

Can you explain how Graph-based AI is used in CyCognito?

Graph-based AI in CyCognito is used to link assets with organizations, people, threats, and technologies. It builds a live, connected map of external relationships and exposure points.

How does CyCognito use Natural Language Processing in semantic search?

CyCognito uses Natural Language Processing in semantic search to allow users to query data in plain language. It also extracts and matches organizational data from business sources in milliseconds, enabling fast, large-scale discovery.

What is the role of AI in risk validation within CyCognito?

In CyCognito, AI plays a significant role in risk validation by adjusting testing to validate the risks that matter most as the environment changes. This ensures a comprehensive, up-to-date risk profile.

How does CyCognito manage routing of security findings to the appropriate authority?

CyCognito manages the routing of security findings to the appropriate authority using AI-assisted logic. It ensures that each finding reaches the right owner with clear remediation context and confirms that fixes are complete.

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