Organizations today continuously face a number of fast-moving cyber threats that regularly challenge the effectiveness of their cybersecurity defenses. However, to keep pace, businesses need a proactive and adaptive approach to their security planning and execution.

Cyber threat exposure management (CTEM) is an effective way to achieve this goal. It provides organizations with a reliable framework for identifying, assessing and mitigating new cyber risks as they materialize.

The importance of developing cybersecurity resilience

Regardless of the industry, all organizations are subject to certain security risks. While various tools and solutions can help to reduce this risk, the only real way of maintaining a strong security posture is by developing a certain amount of cybersecurity resilience.

Cybersecurity resilience is the ability of a business to maintain its core operational state regardless of an attempted or even successful cyberattack. The key components of cybersecurity resilience include:

• Proactive risk management: It’s important to be able to identify and mitigate any potential threats before they have the opportunity to exploit known vulnerabilities. This requires regular risk assessments and strict security policies.

• Continuous monitoring and improvement: Monitoring systems and networks is critical to help identify suspicious network activity while informing the necessary stakeholders for mediation. Regularly reviewing logs and threat reports also allows organizations to improve their security efforts going forward.

• Incident response and recovery: In the event of a successful breach, organizations must be prepared to handle all necessary protocols for threat containment while executing critical recovery efforts to minimize operational disruption.

• Maintaining a progressive cybersecurity culture: While security tools and solutions are important, organizations looking to establish more cybersecurity resilience need to also build awareness with their employees on relevant threats and how they can help protect themselves and the business.

What is CTEM?

While establishing cybersecurity resilience on its own is important, the prevalence and severity of modern-day security threats mean organizations need to look for a more comprehensive approach to threat management.

CTEM relies on the use of automated routines spread across an organization’s entire infrastructure, designed to identify and assess any security gaps present. Unlike traditional vulnerability assessments, which are typically scheduled throughout the year, CTEM solutions enable real-time threat intelligence at all times.

When integrated across all of an organization’s IT assets, including on-premise and cloud networks, systems, applications and databases, CTEM solutions provide a much more proactive approach to strengthening an organization’s security posture.

Key components of CTEM

CTEM frameworks operate by incorporating several key components across an organization’s entire infrastructure. These components include:

Threat intelligence

Leveraging real-time threat intelligence, CTEM references an organization’s location, industry type and digital structure to benchmark against similar organizations while recognizing and prioritizing likely threats. This helps businesses place their mitigation efforts in the right places while always being one step ahead of malicious attackers.

Vulnerability management

CTEM makes use of active vulnerability scanning and assessment tools to look for common vulnerabilities and exposures (CVEs) as well as misconfigurations in systems and networks that could lead to exploitation. Using automated routines, CTEM solutions will run continuous scans for these vulnerabilities and then prioritize them based on the most critical risks.

Security testing

Applying CTEM frameworks across an organization can often include making use of penetration testing services and establishing red teams to help simulate real-world attack scenarios. This helps organizations validate the effectiveness of their current cybersecurity solutions and helps to “stress-test” response capabilities.

Risk assessment

CTEM solutions apply various risk assessment methodologies to help evaluate the potential impact of discovered vulnerabilities. This includes considering various factors that can impact remediation efforts, including the types of assets at risk, how financially sensitive each asset is and the potential impact a successful breach could have on the long-term viability of an organization.

Breaking down the five stages of CTEM

CTEM deployments are an iterative process that involves continuous improvement and refinement. The five stages of CTEM include:

1. Scoping: The initial stage of CTEM involves establishing certain boundaries within which the solution will operate. This requires organizations to identify the relevant systems, applications or key data the solution will actively monitor. Another element of this stage is to outline any specific goals or objectives that need to be achieved to ensure the solution is properly calibrated.

2. Discovery: The discovery stage is when all digital assets are cataloged within the defined scope. While many assets may already be defined during initial scoping stages, the CTEM discovery process may also identify unknown assets, including SaaS solutions or other shadow IT elements that may have been missed. This stage is completed using a series of automated tools that scan and catalog new assets as they’re discovered.

3. Prioritization: After all assets are properly cataloged, the next step is to assess and prioritize all risks associated with each of them. To achieve this, CTEM solutions will apply risk assessment protocols and active threat intelligence to determine the most critical risks.

4. Validation: The validation stage makes sure that any identified vulnerabilities are legitimate and require an actual remediation process. This is designed to minimize or eliminate any false positives.

5. Mobilization: The final stage of CTEM is mobilization, which is any action necessary to remediate vulnerabilities and mitigate risks. This can include coordinated efforts between security teams, IT operations and business stakeholders to ensure that vulnerabilities are addressed effectively.

Start implementing CTEM in your organization

Implementing CTEM is a crucial step towards improving an organization’s cybersecurity resilience. Here are some steps your organization can follow to start benefiting from CTEM integrations:

1. Begin with a cybersecurity risk assessment: Take the time to conduct a comprehensive cybersecurity risk assessment with the help of a security services partner to identify any potential vulnerabilities in your organization.

2. Embrace automation: Leveraging automation tools to streamline various aspects of your CTEM program is critical to enable real-time threat mitigation. This can help to reduce manual security efforts, improve the accuracy of risk remediation efforts and accelerate incident response times.

3. Prioritize and validate: Prioritize any discovered vulnerabilities based on their potential impact on your organization and validate any potential attack vectors using techniques like penetration testing and red team simulations.

4. Establish clear communication channels: It’s important to ensure that security information is shared effectively between different teams and stakeholders. Regardless of the type of CTEM solution your organization chooses to implement, establishing clear communication channels and protocols is essential to ensure that security information is disseminated effectively and acted on in a timely manner.

Keep your business ready

Implementing a CTEM program for your organization is a critical step for organizations considering today’s increasing cyber threats. By taking a proactive and continuous approach to your risk management strategy, you can significantly minimize your digital attack surface while achieving a more resilient cybersecurity posture.

The post How CTEM is providing better cybersecurity resilience for organizations appeared first on Security Intelligence.

A recent CISA red team assessment of a United States critical infrastructure organization revealed systemic vulnerabilities in modern cybersecurity. Among the most pressing issues was a heavy reliance on endpoint detection and response (EDR) solutions, paired with a lack of network-level protections.

These findings underscore a familiar challenge: Why do organizations place so much trust in EDR alone, and what must change to address its shortcomings?

EDR’s double-edged sword

A cornerstone of cyber resilience strategy, EDR solutions are prized for their ability to monitor endpoints for malicious activity. But as the CISA report demonstrated, this reliance can become a liability when paired with inadequate network defenses. Here’s why:

1. Tunnel vision on endpoints: EDR excels at identifying threats on individual devices but struggles with network-wide attacks. This leaves gaps when hackers exploit lateral movement or unusual data transfers — activities that often require network-level visibility to detect.
2. Playing catch-up with threats: Traditional EDR tools depend on recognizing known indicators of compromise (IOCs). Advanced attackers can easily sidestep these tools by using novel techniques or blending in with legitimate activity.
3. Blind spots in legacy systems: Legacy environments often go unnoticed by EDR, giving attackers free rein. In the CISA case, these systems allowed the red team to persist for months undetected.
4. Overwhelmed defenders: Even when EDR generates alerts, security teams can become desensitized by a flood of notifications. As seen in the CISA assessment, critical warnings can slip through the cracks simply because defenders are too stretched to respond.

Common EDR pain points

The challenges highlighted in the CISA report mirror broader issues organizations face with EDR:

• Detection without context: EDR tools often spot anomalies on endpoints but fail to connect the dots across the broader network. This lack of context can leave organizations blind to coordinated attacks.
• Weak network integration: Without network-layer defenses, EDR struggles to identify malicious activities like unusual traffic patterns or data exfiltration, key tactics in advanced breaches.
• Fragmented systems: Many organizations operate a patchwork of security tools, leaving critical gaps in coverage and making it harder to correlate data across endpoints, networks and cloud environments.

The next evolution of EDR

Recognizing these shortcomings, cybersecurity is rapidly evolving beyond traditional EDR. Here’s how:

1. Extended detection and response (XDR): XDR takes EDR to the next level by integrating endpoint, network and cloud data into a single platform. This broader scope allows organizations to see the full attack picture and respond more effectively.
2. AI-driven insights: Cutting-edge EDR solutions now harness machine learning to detect subtle behavioral anomalies. By identifying deviations from normal activity, these tools catch threats even when no IOCs exist.
3. Zero trust security: Zero trust architectures take endpoint defense a step further by ensuring no device or user is trusted by default. This integration of endpoint, identity and network security reduces dependence on EDR alone.
4. Network visibility: Modern EDR tools are incorporating network traffic analysis to close the gaps identified in the CISA report. Monitoring traffic for anomalies, such as unusual data flows or external connections, bolsters defenses.
5. Cloud-native solutions: As businesses embrace hybrid and cloud environments, EDR is evolving to provide seamless coverage across on-premises and cloud systems, addressing vulnerabilities in these critical areas.

Why do gaps persist?

Even with these advancements, many organizations struggle to fully address EDR’s limitations:

• Resource strains: Small security teams often lack the bandwidth or expertise to implement and manage advanced solutions like XDR.
• Budget constraints: Upgrading to integrated platforms or modernizing legacy systems can be costly.
• Legacy challenges: Outdated environments remain vulnerable, acting as weak points that attackers can exploit.
• Leadership missteps: As the CISA report pointed out, organizations sometimes deprioritize known vulnerabilities, leaving critical gaps unaddressed.

Building a more resilient future

The CISA red team findings are a wake-up call: Endpoint protection alone is no longer enough. To outsmart today’s sophisticated adversaries, organizations must adopt a layered defense strategy that integrates endpoint, network and cloud security. Solutions like XDR, zero trust principles and advanced behavioral analysis offer a path forward — but they require strategic investments and cultural shifts.

The post Insights from CISA’s red team findings and the evolution of EDR appeared first on Security Intelligence.

Practicing good data hygiene is critical for today’s businesses. With everything from operational efficiency to cybersecurity readiness relying on the integrity of stored data, having confidence in your organization’s data cleanliness policy is essential.

But what does this involve, and how can you ensure your data cleanliness policy checks the right boxes? Luckily, there are practical steps you can follow to ensure data accuracy while mitigating the security and compliance risks that come with poor data hygiene.

Understanding the 6 dimensions of data cleanliness

It doesn’t matter where your company data is sourced — without addressing its quality and accuracy, you won’t be able to rely on it. To create the right data cleanliness policy, you’ll need to understand its different dimensions. These include:

• Accuracy: Identifies to what extent data can be trusted and is free from errors. This requires specific validation protocols and compliance with data collection standards.
• Completeness: Signifies whether or not collected data provides clear answers to certain questions. It involves evaluating any missing data attributes and recognizing any apparent gaps.
• Consistency: Checks that data is properly mirrored when stored in multiple databases and represented by a percentage of matched values.
• Validity: Refers to data adherence against predefined rules or formats. It helps eliminate the violation of logical constraints or data type restrictions.
• Uniqueness: Makes sure all data types reference the same units of measure or support formats to remove the possibility of information overlapping or duplication across data sets.
• Timeliness: Represents the degree to which data remains up-to-date. This ensures data is accessible when it’s required so it can be used properly.

Once you have a grasp on these six core elements, you’re ready to move forward with crafting your data cleanliness policy.

Step 1: Define policy scope and objectives

The first step to take when creating a data cleanliness policy is to define all appropriate business objectives. Any specific data sets or systems and the intended use of the information within them should be clearly outlined.

This step also involves considering often-overlooked data, including unused software logs, outdated emails and former customer records. If this information is forgotten about, it can lead to security issues down the road when they are left in unsecured locations.

Step 2: Classify data assets

With your policy scope defined, you’ll need to take inventory of all relevant data sources. Data assets can include various databases spread across multi-cloud environments, locally stored spreadsheets or any other areas where data is stored.

Classifying all data assets is another way to minimize forgotten data from compiling and creating high-value targets for cyber criminals. During this process, you’ll also want to categorize data based on its relative sensitivity or regulatory requirements. This will make it easier to implement the right access controls and data retention policies.

Step 3: Establish data quality standards

The data quality standards you develop for your policy should be measurable and easy to understand. To achieve this, you’ll need to lay out specific criteria for each data type, including the acceptable formats data should be in and any validation rules you have in place.

With your metrics in place, you’ll be able to regularly monitor their performance over time. Many times, regulatory requirements will stipulate that data needs to meet certain accuracy and completeness benchmarks. Having these trackable metrics in place provides the transparency needed to ensure these regulations are continuously being met.

Step 4: Assign roles and responsibilities

Establishing clear accountabilities is essential when managing organizational data. Your data cleanliness policy should define the various roles in your organization, including specifying who can access data and what levels of permission they have.

Controlling the amount of individuals who can access, modify or delete data is one of the most important elements of ensuring data integrity over the long term. It helps you to mitigate the danger of insider threats as well as establish clear lines of accountability if and when anomalies are located in data sets.

It is also common to make use of a data governance team that can help to implement and enforce various policy initiatives. These teams can reduce the likelihood of data inconsistency and help support various data security protocols in place.

Step 5: Implement data cleansing procedures

In the event that data issues are discovered, your policy should also cover necessary data correction procedures. This can include standardization, normalization or deduplication of data stored across systems.

Another supporting element of this process is having clear data retention and disposal policies in place. This helps to reinforce best practices when it comes to data lifecycle management. It also minimizes a digital attack surface, making it less likely that sensitive information is left in a vulnerable storage state, and helps to minimize damages in the event of a successful cyberattack.

Maintain healthier organizational data

Being able to rely on the accuracy and consistency of your company data is critical. Not only does data integrity play an important factor in improving the value of your technology investments, but it also helps to strengthen your cybersecurity posture.

By following the steps above, you’ll be able to draft a data cleanliness policy that allows you to maintain healthier organizational data while extracting its full value.

The post How to craft a comprehensive data cleanliness policy appeared first on Security Intelligence.