Artificial Intelligence Archives

Event details:

Thursday, May 23, 2024
1:00 PM ET

Presenters:

Mark Sangster, VP, Chief of Strategy at Adlumin
Ben McPherson, Head of Solutions Engineering at Adlumin

About this Talk:

This webinar will explore how artificial intelligence (AI) is being used to revolutionize data security. Industry experts Mark Sangster, VP, Chief of Strategy, and Ben McPherson, Head of Solutions Engineering, will discuss how AI is addressing emerging threats in the cybersecurity landscape and Managed Detection and Response (MDR) space.

What you will learn:

How AI can analyze vast amounts of data to identify and predict security threats.
Different ways AI can be used to detect unusual user activity that might indicate a security breach.
Methods for how AI can be used to scan networks and systems for vulnerabilities.

As a thank you for joining our webinar, you’ll receive “The Ultimate Guide to Using Cybersecurity AI,” which includes key takeaways and recommendations for your security strategy. Additionally, one lucky participant will receive a $200 Amazon gift card.

By: Bronwen Cohn-Cort, Data Scientist, and Shaul Saitowitz, Data Scientist

Welcome to the Unraveling Cyber Defense Model Secrets series, where we shine a light on Adlumin’s Data Science team, explore the team’s latest detections, and learn how to navigate the cyberattack landscape.

The Essential Role of Threat Detection

Threat detection is a critical component of an organization’s cybersecurity strategy. Requiring the combination of human expertise and machine learning, risk can be significantly reduced by identifying threats before a potential attack.

Many threats can go unnoticed for months or even years. In IBM’s latest report, it takes an average of 277 days for security teams to identify and contain a data breach, and the cost of a breach skyrocketed, reaching an average of $4.45 million. Given the extended timeframe it often takes to detect and contain a data breach, organizations must proactively implement measures to quickly respond to potential threats and reduce the risk of costly damages.

To effectively combat malicious activity in your environment, it can be challenging to stay on top of all the potential threats, particularly as it demands skilled professionals who can develop models to apply artificial intelligence. Setting up alerts for when suspicious activity is detected can help organizations quickly respond to potential breaches and mitigate the risk of further damage to their systems and data.

Critical Detections for Your Network Security

While there are many types of security threats and detections to consider today, we highlight credential harvesting and insider threats as two crucial ones to add to your queue.

Adlumin Data Science is rolling out alerts for credential harvesting and insider threats, each capable of warning against prevalent attack tactics within their domains by utilizing user and entity behavior analytics. These detections are crucial as they are often difficult for organizations to identify.

Credential Harvesting Detection

A credential harvesting alert addresses a post-exploitation technique to broaden network access. After gaining a foothold, this alert will notify an organization about suspicious activities related to stealing login credentials from a computer system. This information can then be used to access other systems, steal data, or even compromise an entire network.

Sources of stored credentials include files, databases, registry entries, and memory structures where login credentials are stored, whether in plaintext or encrypted form. Some of these locations include LSASS (Local Security Authority Subsystem Service), GPP (Group Policy Preferences), and web browsers that store passwords. Cybercriminals can use one of many tools or techniques to capture the stored credentials.

These include utilities like Mimikatz, Hashcat, and SharpChromium. Once the credentials have been extracted, the attacker harvests them for future use. Encrypted passwords can be cracked offline and then used to access other systems within the network, furthering the attack.

The detection exposes several credential dumping techniques and delivers background on the tool discovered. This allows prompt stoppage of the unfolding attack and helps protect business assets. The detection model should be updated regularly to keep up with new tactics and methods.

Credential harvesting poses a significant threat to organizations, leading to unauthorized access, data breaches, and financial loss. Setting up alerts for credential dumping processes is crucial as it enables early detection and swift response to mitigate potential damage. Organizations can protect their sensitive information, maintain operational continuity, and uphold trust with customers and stakeholders by efficiently enriching, containing, and recovering from such incidents.

Insider Threat Detection: Aggregating and Analyzing Widespread File Deletion

Some ransomware variants, like REvil, involve mass file deletion; in some instances, an unauthorized insider may gain permissions sufficient to mass-delete files. The Insider Threat model detects and alerts on cases of a user or attacker deleting an abnormally high number of files across many different subdirectories. Further analysis is conducted to filter out file extensions and locations that likely correspond to benign deletion activity. For example, a user emptying the Recycle Bin would not trigger an alert.

Setting up an Insider Threat alert uses a machine learning model to determine anomalies in the number of Windows Event ID 4663 (“An attempt was made to access an object”) events with Delete access permissions. A high quantity of these 4663 events in a half-hour period significantly deviating from the customer baseline is considered anomalous.

The table below displays partially redacted information from 4663 events associated with an alert. For each, it shows the time of the log message, the computer name on which it occurred, and which Object Name and Process Name were associated with the event. This table can be used to further investigate the deletion activity by reviewing the details of what computers, locations, and types of files were involved.

Following an alert, activity from the username(s) in question should be examined if a threat actor compromised a user account. Suspicious behavior may warrant disabling the account and quarantining affected computers from the network. Review user actions and run an anti-malware scan and vulnerability assessment to check if the threat actor has performed any other actions, such as creating a logic bomb or backdoor.

Insider threats pose a significant risk to organizations as they can result in data breaches, financial loss, reputational damage, and operational disruptions. Malicious insiders or compromised accounts can intentionally or unintentionally cause harm by deleting critical files, installing malware, or stealing sensitive information.

Setting up Insider Threat alerts, like the one described here, is crucial for detecting suspicious activities, such as widespread file deletion, in a timely manner. By observing user behavior, organizations can proactively identify and respond to potential insider threats, mitigating the impact of security incidents and safeguarding their assets and operations.

Experience The Innovations 

Here at Adlumin, we know how important it is to see everything in cybersecurity. That’s why we offer a customized Security Operations Platform and Managed Detection and Response services to give organizations a complete view of their IT environment. But we go further than that. We believe in the value of firsthand experience, so we invite you to explore our platform yourself with a guided tour.

See how our platform helps your team find and address threats by arranging a demo or trying out our platform for free. Join the tour and boost your organization’s visibility to a whole new level.

Explore the Platform