Find out how DataRobot’s artificial intelligence (AI) capabilities can integrate with your cybersecurity defenses to augment your intelligence, prioritize vulnerability management, and shorten decision cycles for a faster and more accurate collective defense.

Optimize Your Security Operations Center

DataRobot’s artificial intelligence (AI) platform can help Security Operations Center (SOC) leaders through shortened decision cycles, anomaly detection, and automated responses.

SOC 1.0 was about controlling the data flowing in and out of the business by bounding networks and sending alerts on traffic coming in and out of the network. 

SOC 2.0 incorporated lateral traffic detection and sensor reporting from servers and endpoints across the corporate network. Leaders now have visibility over the network and stand to optimize detection and response. 

SOC 3.0 is the deployment of AI/ML into existing security processes to detect disparate threats from insiders and advanced persistent threats (APTs), as well as providing the augmented intelligence needed to decrease response times and empower your analysts to focus on the most difficult security incidents.

DataRobot automates the entire end-to-end process of preparing, building, and deploying accurate predictive models that are available to integrate with your cloud platform-of-choice, onsite system, or fully-managed service. Our Automated Machine Learning platform will help your security teams create trusted solutions that can predict and auto-route alert responses, shortening analyst decision cycle per alert through consequence-based alert prioritization.

Data Agnostic

DataRobot can ingest nearly all data types, enabling us to quickly answer intelligence requirements in real-time.

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Our solution has built-in compliance reporting and automated guardrails to ensure that your AI applications are more robust, accurate, interpretable and stable, and therefore more trustworthy.

Continuously Learning

Continuously Learning

The DataRobot platform can deploy your existing or offline models directly into production, while monitoring the models over time for drift and accuracy, letting you know when AI/ML needs to be retrained.

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The DataRobot platform can integrate directly with existing processes, workflows, and systems to create a seamless, effortless transition.

Detect Advanced Persistent Threats

The Problem

In December 2020, the U.S. learned that an Advanced Persistent Threat (APT) cyber actor had gained and maintained access to over 18,000 networks inside the U.S. government, private companies, and non-profit organizations since at least March 2020. This attack was a complex supply chain attack involving cyber activity,  human actors, and malicious code embedded in the design process. Advanced actors are using every available method to gain access to networks. Solutions that focus exclusively on cybersecurity will never illuminate and isolate these threats. The DataRobot AI Cloud sits above typical cybersecurity solutions, able to harvest financial data, security data, and more to identify these multi-pronged attacks by advanced persistent threat actors.

How DataRobot Can Help

  • Quickly analyze huge volumes of network and open source data to protect the security of our intelligence systems and networks.
  • Predict adversary activity based on threats and consequence with evolutionary predictions on identifying insider threats.
  • Recognize previously unseen activity and seemingly isolated events as correlated activity by advanced actors.
cut down

Efficient Time Management

Cut down on the hours analysts spend on reading intelligence to increase hours acting on intelligence.

Avoid signature based

Detect the Undetected

Avoid signature-based detection methods, utilizing AI to detect never before seen malware.

Vulnerability Management

The Problem

For many organizations, it is unrealistic to expect every vulnerability will be resolved in near-real-time. Instead, they must choose to patch those vulnerabilities that pose the greatest risk to the health of their missions and the information networks that enable them.

While the National Vulnerability Database (NVD) assigns a Critical Vulnerability Security Score (CVSS) to each vulnerability, this is not enough context to inform which vulnerability management efforts will have the greatest impact on the security of specific organizations and networks. The CVSS captures the impact of a vulnerability if it were to be exploited, but it does not account for actual weaponization. There are over 120k published Common Vulnerabilities and Exploits (CVE) in the NVD. However, studies indicate only 20-22% of known CVEs have public exploits–meaning, the vast majority of CVEs cannot be weaponized by the vast majority of actors.

How DataRobot Can Help

  • Identify and prioritize mission-critical machine learning use cases to augment existing cyber processes, tools, and people.
  • Identify your key terrain and provide machine learning operations to predict the patches and terrain most important to your company.
Current patching

Prioritize Predictions

Current patching is typically a minimum of 30 days behind release dates for most cybersecurity solutions. DataRobot will predict what patches are more important to your enterprise for faster and safer vulnerability management.

In 2019 the average medium

Streamline Processes

In 2019, the average medium to large company spent around 413 weekly hours on vulnerability management processes. This is enough work for ten people each week! Initial DataRobot augmented VM shows a minimum of 25% decrease in hours worked.

Business Email Compromise

The Problem

The number one intrusion method by adversaries is still phishing. Prior techniques involved sending malicious links and malware-filed attachments to launch an infection into the host system. The market leaders in email security can largely stop these malicious techniques. 

But what happens when your adversary doesn’t send any malicious links or attachments? How do you know they are your adversary? How can you define intent?

DataRobot uses its native Natural Language Processing (NLP) ability to classify emails and predict whether your employees are seeing fraudulent requests or influence operations.

How DataRobot Can Help

  • Classify emails as valid, malicious, sensitive, or benign based on the text strings in the email.
  • Cue SOC analysts to investigate when a seemingly benign email will lead to a fraudulent or malicious outcome.
  • Detect when adversaries are embedding over time, building confidence in your employees to later lure them into unwitting fraudulent or criminal activity.
DataRobot can find correlations

Effective Detection

DataRobot can find correlations across multiple disparate datasets and link the chain to determine whether seemingly benign emails have malicious intent.

DataRobots unique ability to look across the enterprise is unparalleled in cybersecurity.

Proven AI

DataRobot’s unique ability to look across the enterprise is unparalleled in cybersecurity.

Cybersecurity leaders dont need to purchase another platform. They can repurpose the DataRobot platform to get more bang for the buck

Decrease Expenditures

Cybersecurity leaders don’t need to purchase another platform. They can repurpose the DataRobot platform to get more bang for the buck.

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