General – Page 4 – Léargas Security

What Is SecOps and What Is The Value Of SecOps To Organizations?

As organizations continue to embrace digital transformation, software development has become a critical part of their operations. However, with the rise of cyber threats and data breaches, security has become a top concern for many organizations.

This is where SecOps comes in…

A methodology that integrates security practices into the DevOps process.

SecOps is a collaborative approach that brings together security professionals, developers, and operations teams to ensure that security is incorporated throughout the entire software development lifecycle. By integrating security into the development process, SecOps helps to identify and address security vulnerabilities earlier, reducing the likelihood of security breaches and data leaks.

So, what is the value of SecOps to organizations? Let’s take a look:

Enhanced Security

One of the primary benefits of SecOps is enhanced security. By incorporating security into the development process, organizations can identify and address security vulnerabilities earlier in the development lifecycle. This means that security issues can be remediated before they become major problems, reducing the likelihood of security breaches and data leaks.

Faster Time to Market

In today’s fast-paced business environment, time to market is critical. SecOps helps teams to identify and resolve security issues earlier in the development cycle, reducing delays and accelerating time to market. By reducing the time it takes to get products and services to market, organizations can stay ahead of the competition and meet the needs of their customers more effectively.

Improved Collaboration

SecOps fosters collaboration between security, development, and operations teams, breaking down silos and enabling teams to work together more effectively. This collaboration helps to ensure that security is integrated into the development process from the outset, rather than being an afterthought. By working together, teams can identify and address security issues more effectively, reducing the likelihood of security incidents and data breaches.

Cost Reduction

Early identification and remediation of security vulnerabilities can save organizations money in the long run. By identifying and addressing security issues earlier in the development process, organizations can avoid costly security incidents and data breaches. This can result in significant cost savings, as well as reducing the risk of reputational damage.

Regulatory Compliance

Finally, SecOps helps organizations to meet regulatory requirements and standards, such as GDPR, HIPAA, and PCI DSS, by incorporating security into the software development process from the outset. By ensuring that security is integrated into the development process, organizations can avoid costly fines and penalties for non-compliance.

SecOps is a powerful approach to security that can help organizations to build more secure software, reduce costs, and accelerate time to market. By integrating security into the development process, organizations can identify and address security vulnerabilities earlier, reduce the risk of security incidents and data breaches, and meet regulatory requirements and standards. As organizations continue to embrace digital transformation, SecOps will become an increasingly critical part of their operations.

At Léargas Security, we provide several integration points for SecOps and SDLC.

Reach out and ask how we can help you, today!

The Importance of Normalization and Scoring of Threat Intelligence Artifacts

In the present-day, interconnected world, businesses confront an expanding threat landscape. To safeguard themselves from cyber threats, organizations rely on threat intelligence, which is one of the most valuable tools available. However, the effectiveness of threat intelligence hinges on the quality of its data. That’s why normalization and scoring of threat intelligence artifacts are two indispensable procedures that guarantee high-quality data.

Visibility and Log Fidelity – Recommendations

In the world of cybersecurity, adequate visibility and log fidelity are critical components in ensuring the necessary security of your organization’s assets. As cyber threats continue to evolve and become more sophisticated, it’s essential to have a comprehensive view of your many networks, cloud assets, and endpoints, provides and the ability to identify potential security incidents quickly.

Breaking these components down, “Visibility” refers to the level of insight you have into your organization’s activity. This insight includes understanding how your network operates, what devices are connected to it, and the types of traffic flowing through it. In essence, visibility provides a complete picture of your organization’s landscape, allowing you to identify and address potential security issues proactively. Adequate amounts of log fidelity will be required to raise the confidence in the assertions made by the analyst.

“Log fidelity”, on the other hand, refers to the accuracy and completeness of the data collected. It’s essential to collect logs from various devices in your organization to ensure that you have a complete picture of the activity. Log fidelity allows you to trace activity and identify potential security incidents with precision and speed.

Adequate amounts of log fidelity will be required to raise the confidence in the assertions made by the analyst, and more will always be better.

One might desire to collect the highest-fidelity of logs, but there are significant pros and cons to be considered. Some of the most important ones are outlined below.

Pros

Improved troubleshooting
Increasing log verbosity can provide more detailed information about system operations, making it easier to identify and diagnose issues.
Better understanding of system behavior
With more detailed logs, it’s easier to understand how a system is behaving, providing valuable insights into its operation.
Improved security
Detailed logs can provide security teams with more information about potential security incidents, making it easier to identify and respond to them.
Improved performance
In some cases, increasing log verbosity can help identify performance issues that might have gone unnoticed with less detailed logs. This is effectively implementing a SNR (Signal-To-Noise Ratio).

Cons

Increased storage requirements
More detailed logs require more storage space, which can be a concern for systems with limited disk space.
Licensing costs
Many SIEMs are built on a pricing model that could significantly increase the cost of platform, as the total volume of logs will increase.
Increased processing overhead
Generating more detailed logs can require additional processing overhead, which can impact system performance.
Reduced performance
In some cases, increasing log verbosity can cause a system to slow down, especially if there is a high volume of log data.
Privacy concerns
Detailed logs can contain sensitive information, which can pose privacy concerns if not handled properly.

Together, visibility and log fidelity provide a powerful tool for cybersecurity professionals to protect their organization from potential threats, but they must be properly tuned. Without adequate visibility, it’s challenging to know what’s happening within your organization, making it difficult to identify potential security incidents and manage the security posture. Similarly, without log fidelity, it’s challenging to trace activity and identify the root cause of a security incident.

Here are some recommendations for log levels in cybersecurity:

Use a consistent log level system
It’s essential to use a consistent log level system across all devices and applications in your network. This ensures that all logs are categorized and prioritized in a consistent manner, making it easier to identify potential security incidents. Normalizing the log data in the earlier stages of collection will likely reduce the TCO (Total Cost of Ownership) of the platform.
Use a minimum of three log levels
It’s recommended to use a minimum of three log levels: information, warning, and error. This provides a basic framework for identifying potential issues while keeping log files manageable. Where possible, consider formatting the logs in JSON (JavaScript Object Notation) as it can lower the cost of normalization between other logs.
Define log levels based on severity
Define log levels based on the severity of an event or activity being logged. This ensures that the most critical events are identified and addressed promptly.
Define thresholds for log levels
Define thresholds for each log level based on the severity of the event or activity being logged. For example, a warning log may be generated when a device is running low on storage space, and an error log may be generated when a device has encountered an error.
Define retention
Define the period of time that log data is kept and available for analysis. Retention policies define the length of time that log data is stored and are typically based on compliance requirements or organizational needs.
Monitor logs in real-time
It’s recommended to monitor logs in real-time to detect potential security incidents promptly. This can be done using Léargas Security, which can alert security teams when critical events occur.
Regularly review and analyze logs
Regularly reviewing and analyzing logs can help identify potential security incidents that may have gone unnoticed. This can help security teams identify and address vulnerabilities and threats before they cause significant damage.

Log levels play a critical role in cybersecurity by providing information on the severity of an event or activity being logged. By using a consistent log level system, defining log levels based on severity, and regularly reviewing and analyzing logs, security teams can identify and address potential security incidents proactively. By monitoring logs in real-time and using automated tools, security teams can detect and respond to potential security incidents promptly, minimizing the impact of a security breach or data loss incident.

At Léargas Security, our goal is to work with our customers to determine their operational and regulatory needs, because it helps the organizations identify and manage security risks, comply with legal and regulatory requirements, establish effective security practices, and allocate resources effectively. By understanding their operational and regulatory needs, organizations can establish appropriate policies, procedures, and technical controls that mitigate risks and protect critical assets.

Need help? Contact us today at, sales@leargassecurity.com!

Inline Detections and Hunting: The Differences and Value Gained

The threat landscape is continually evolving and growing increasingly complex, therefore organizations must take a proactive approach to cybersecurity. Traditional security tools such as firewalls, intrusion detection systems (IDS), and antivirus software are no longer sufficient to protect against advanced threats. Inline security detections and threat hunting are two approaches that can help organizations to better detect and respond to security threats.

Attack Surface Reduction: Why It Matters.

In today’s digital age, cybersecurity is more critical than ever before. With the growing number of cyber threats, it is essential to reduce the attack surface to protect your organization’s assets. What is the “attack surface”? The attack surface refers to the total number of vulnerabilities, entry points, and possible attack vectors that hackers can exploit to gain unauthorized access to an organization’s systems and data. In this blog post, we will discuss the importance of reducing the cybersecurity attack surface and some effective ways to do it.

The Importance of Artificial Intelligence and Machine Learning in Cybersecurity

Léargas Security, like many other Extended Detection and Response (XDR) platforms, has become an essential part of modern cybersecurity. As the number and complexity of cyber threats continue to increase, more organizations are turning to Léargas to provide comprehensive and proactive threat detection and response capabilities. And one of the most significant advancements in the Léargas platform in recent years has been the integration of artificial intelligence (AI) and machine learning (ML) algorithms.

Let’s understand what Léargas is. Léargas is an advanced security platform that provides organizations with a comprehensive approach to threat detection and response. Unlike traditional security solutions that only focus on specific parts of an organization’s infrastructure, the Léargas platform leverages data from multiple security tools and data sources, both on-premises and in the cloud, to provide a more holistic and comprehensive view of the network, endpoints, and cloud environments. The Léargas platform combines security analytics, threat intelligence, and automated response capabilities to detect and respond to threats across the entire infrastructure.

With the integration of artificial intelligence and machine learning, Léargas can improve the detection capabilities and speed up response times for its subscribers. Artificial intelligence and machine learning algorithms can process copious amounts of data from a growing number of sources in real-time, identifying patterns and anomalies that may indicate an attack. This allows the Léargas platform to detect and respond to threats more quickly, reducing the risk of damage and data loss.

So, here are some specific ways that the Léargas platform utilizes AI and ML:

Enhanced detection capabilities: AI and ML algorithms can analyze large volumes of data from various sources, such as network traffic, logs, and endpoints. This enables Léargas to detect advanced and emerging threats that traditional security solutions may miss.
Faster response times: AI and ML algorithms can automate response actions, such as isolating infected endpoints, blocking malicious traffic, and containing the attack. This permits Léargas to respond quickly to threats, reducing the time-to-detection and time-to-response.
Reduced false positives: AI and ML algorithms can filter out false positives, reducing the number of alerts that security teams need to investigate. This saves time and resources, allowing security teams, both MSP (Managed Service Providers), MSSP, and independent organizations to focus on more critical threats.
Improved threat intelligence: AI and ML algorithms can analyze threat intelligence data, identifying new patterns and trends that may indicate emerging threats. This enables Léargas to stay ahead of the threat landscape, providing proactive threat detection and response capabilities. Additionally, Léargas partners with companies like Critical Path Security to gain more valuable intelligence each day.
Better risk management: AI and ML algorithms can provide risk scoring and prioritization, allowing security teams to focus on the most critical threats.
Malware analysis: Machine learning algorithms are used by the Léargas platform and the supported EDR (Endpoint Detection and Response) solutions to analyze malware behavior, identifying patterns that may indicate the presence of malware, ransomware, or an internal threat actor on a network.

Léargas strives to secure organizations by enhancing threat detection capabilities, speeding up response times, reducing false positives, improving threat intelligence, and providing better risk management.

As the threat landscape continues to evolve, organizations need advanced security solutions that can keep pace with the changing threat landscape. The AI-powered Léargas security platform provides a proactive and comprehensive approach to cybersecurity, helping organizations to stay one step ahead of cyber threats.

Correlation and Enrichment: Office365 and Endpoint Security

As organizations increasingly rely on cloud-based services such as Office 365 for their productivity and collaboration needs, it’s critical to understand the importance of correlating logs from both the cloud service and the endpoint devices. This correlation can provide a comprehensive view of the activities taking place within the organization and help ensure the security and compliance of sensitive information, no matter where the endpoint might be.

One of the main benefits of correlating Office 365 and Endpoint Security logs is that it can help identify suspicious or malicious activity. For example, if a user’s endpoint device shows signs of a security breach, geographically-impossible authentication attempts, or attacks such as a virus or malware event, the corresponding Office 365 logs can provide valuable information on what data may have been accessed or exfiltrated.

The Léargas Security platform automatically correlates the data from the sources into single searches and alerts.

Additionally, correlating Office 365 and Endpoint Security logs can also help organizations identify compliance violations, such as unauthorized access to sensitive information. With the right tools, organizations can quickly identify when a user has taken actions that violate their data protection policies, such as downloading confidential data onto a personal device or sending sensitive information to an unauthorized email recipient.

Moreover, correlating logs can help improve incident response time. In the event of a security incident, having a comprehensive view of the activities that took place can help organizations quickly identify the source and scope of the problem, enabling them to respond and resolve the issue more efficiently.

Here are the Top 10 reasons for automatically correlating Office 365 and Endpoint Security logs:

IMPROVED VISIBILITY INTO USER ACTIVITY: Correlating logs provides a comprehensive view of what users are doing within the organization, including access to sensitive information and email correspondence, regardless of location and time.
DETECTING SUSPICIOUS OR MALICIOUS ACTIVITY: Correlating logs can help identify potential security threats and unauthorized access to sensitive data.
IMPROVING INCIDENT RESPONSE TIME: Having a comprehensive view of activities can help organizations quickly identify the source and scope of security incidents, allowing them to respond more efficiently.
ENSURING COMPLIANCE WITH INDUSTRY REGULATIONS: Organizations can use log data to demonstrate compliance with regulations such as GDPR and HIPAA.
AUDITING AND COMPLIANCE REPORTING: Log data can provide valuable insights for auditing and compliance reporting, helping organizations ensure that their security and privacy practices are up to standards.
PROTECTING SENSITIVE DATA: Correlating logs can help organizations identify when sensitive data is being accessed, downloaded, or sent to unauthorized recipients, allowing them to take appropriate action to protect it.
DETECTING ENDPOINT SECURITY BREACHES: Endpoint devices are a common target for attackers, and correlating logs can help organizations identify when a device has been compromised and what data may have been accessed.
IDENTIFYING UNUSUAL USER BEHAVIOR: Correlating logs can help organizations identify when users are engaging in suspicious or unusual behavior, allowing them to take appropriate action to mitigate potential threats.
DETECTING DATA EXFILTRATION: By tracking user activities, organizations can identify when sensitive data is being exfiltrated and take appropriate action to prevent it.
ENHANCING SECURITY AND PRIVACY: By correlating logs, organizations can gain a better understanding of their security and privacy practices and take appropriate steps to improve them.

Finally, correlating Office 365 and Endpoint Security logs can also provide valuable insights for auditing and compliance reporting. Organizations can use the data from these logs to demonstrate their compliance with industry regulations and standards, such as GDPR and HIPAA, by providing a detailed view of their security and privacy practices.

Zeek vs NetFlow: Why Léargas chose Zeek

As organizations continue to rely more on networked systems for critical operations, the need for efficient and effective network traffic analysis solutions becomes increasingly important. Two popular solutions for network traffic analysis are Zeek and Netflow, and many organizations are faced with the challenge of choosing between the two. In this blog post, we will take a closer look at each solution and explore why we are proudly built on Zeek.

What is Zeek?
Zeek is a powerful and flexible open-source network security monitoring tool that provides a rich set of features for network traffic analysis. Zeek operates by capturing network packets and creating logs of network activity in real-time. These logs provide detailed information about network connections, protocols, and other relevant data, making it an ideal solution for security professionals who need to quickly identify security threats and respond to incidents. What is Netflow?
Netflow is a network traffic analysis protocol that was developed by Cisco Systems. Netflow provides a method for collecting information about network traffic and analyzing it to identify trends, anomalies, and other important information. Unlike Zeek, which focuses on analyzing network packets, Netflow focuses on analyzing network flow data, which is a high-level view of network activity. Netflow is well-suited for organizations that want to get an overview of network traffic patterns without getting into the technical details of packet analysis. Zeek vs Netflow: Pros and Cons
Zeek and Netflow each have their own strengths and weaknesses, and the solution that is best for you will depend on your specific needs and requirements.

Pros of Zeek:

Network traffic analysis and inspection
Intrusion detection and threat hunting
Integrated Threat Intelligence
Embedded File Extraction and Analysis
Protocol analysis and decoding
Flexible logging and reporting
Customizable and extensible scripting
High-performance and scalability
Integration with other security tools
Advanced analytics and data visualization
Flexible deployment options (e.g. standalone, cluster, cloud)

Cons of Netflow:

Limited in terms of the data it provides compared to Zeek
May not provide enough detail for advanced network security analysis
Does not provide real-time analysis

Conclusion
Choosing between the Zeek-based, Léargas Security platform over Netflow-based platforms for network traffic analysis is an easy decision.

If you’re looking for a solution that provides a rich set of features for network traffic analysis, real-time analysis of network packets, and the ability to identify security threats and respond to incidents quickly, then the Zeek-based, Léargas Security is the solution for you.

With the right solution in place, you can ensure that your network is secure and that you have the information you need to quickly respond to security incidents.

What is SOAR and how can it help you?

What is SOAR and how can it help you?

SOAR (Security Orchestration, Automation, and Response) is a technology that enables security teams to automate repetitive tasks, aggregate multiple security tools and technologies into one unified platform, and improve the speed and accuracy of incident response. It helps organizations to streamline their security operations and make them more efficient and effective.

SOAR and platforms such as Léargas Security can perform tasks such as:

Automating routine and repetitive tasks, freeing up security teams to focus on more complex incidents.
Integrating with other security tools, such as SIEMs, firewalls, and endpoint protection solutions, to gather data and automate incident response.
Correlating and analyzing data to quickly identify potential threats and prioritize incidents.
Providing a centralized and standardized incident response process to improve the speed and efficiency of response efforts.
Documenting and reporting on security incidents to improve incident response and to meet compliance requirements.

How does this differentiate from a SIEM?

SIEM stands for Security Information and Event Management, and is a type of software that collects and analyzes security data from various devices on a network to provide a centralized view of security events and to identify potential security threats. SIEMs help organizations to comply with security regulations, detect and respond to security incidents, and monitor the security posture of their networks.

SIEM and SOAR are both security technologies, but they serve different purposes and have different focuses.

SIEMs are designed to collect, store, and analyze security-related data from various sources such as network devices, servers, and applications. The goal of SIEMs is to provide a centralized view of security events and to help detect and respond to potential security threats.

Léargas Security, on the other hand, is designed to automate and orchestrate security-related processes such as incident response, threat hunting, and vulnerability management. Léargas Security provides a platform for security teams to automate repetitive tasks, standardize incident response procedures, and improve the overall efficiency of the security operations.

In summary, organizations may choose Léargas Security that leverages SOAR technology over a SIEM, because Léargas Security offers a more comprehensive and integrated approach to threat detection and response that covers multiple environments, while other platforms are limited to a narrower scope of security events and data.

Will ChatGPT Change Cybersecurity?

The leading question around the Cybersecurity community has been, “Will ChatGPT and OpenAI change Cybersecurity?“.

It’s a great question, as those technologies are far more advanced than most of us expected them to be at this point in time. The answer is, “We aren’t entirely sure, but we have an idea.“.

Even asking ChatGPT for the answer is met with some ambiguity.

“It is possible that ChatGPT or similar language models may be used in the field of cybersecurity in the future. For example, they could potentially be used to generate more realistic and diverse phishing or malware attacks, or to assist in analyzing large volumes of text-based data such as logs or email communications. However, it’s important to note that these models are not inherently malicious and their use in cybersecurity would depend on how they are implemented and controlled by organizations.”

Anyone that has spent time around machine learning or data modeling will agree that all data used to build those models is historical, because that’s how data works. You can’t collect it until it has happened. This understanding helps frame up the possibilities around the potential of ChatGPT and OpenAI.

Created predictions aren’t binary, meaning a “yes” or a “no”, but made in “varying degrees of confidence”.

So, knowing that it can’t do all of the things, let’s look at some of the things that it can, and often, won’t do.

Offensive Capabilities

Phishing – It will not automatically write a phishing email. Protections are in place to dissuade the use of the platform for malicious uses. Yes, some protections can be bypassed, but as new tactics are attempted, new protections are put in place.
Social Engineering – ChatGPT will create content that could be used in a social engineering campaign, but the effectiveness of that content still comes down to the creativity of the threat actor. It will not fully automate a social engineering campaign.
Malware Generation – ChatGPT will happily write an Ansible playbook or other remote management program that can be used in Malware. However, it will not create new vulnerabilities and requests to do so respond with how to defend a system against a particular class of vulnerabilities.

Defensive Capabilities

Also, it can build defenses.

Zeek Behavioral Detections – ChatGPT can create detections for malicious events that could occur on networks, such as this detection for beaconing. Beaconing is a common indicator of a successful ransomware event.
Windows Event Log Detections – ChatGPT will create detections that will search the Security event log for events that correlate with specific event IDs, then filters the events that occurred in the past day and checks if any events match the criteria. If any events are found, it will output a warning message and display the matching events. Otherwise, it will output a message saying that no suspicious activity was detected.
Email Phishing and Ransomware Detections – ChatGPT will build a detection looks for specific keywords in the subject, sender, and body of an email. If the email contains “urgent”, “bank”, “click here”, “password”, and “account” in those fields, it will trigger the detection and print a message indicating that a phishing email has been detected.

As we continue the conversation around ChatGPT and the potential impacts it might have, let’s not lose focus on the positives of this incredible innovation. As shown above, ChatGPT currently provides more positive impact than negative.