Federal agencies face a formidable challenge in navigating the deluge of emerging vulnerabilities while managing the remediation of existing ones.
According to research from the Qualys Threat Research Unit (TRU), nearly 30,000 vulnerabilities were discovered and published on the Common Vulnerabilities and Exposures (CVE) list in 2023, up from just over 25,000 in 2022.
More alarmingly, the Qualys TRU team identified 206 CVEs that were published and weaponized, surpassing numbers from recent years. This is significant because the increased likelihood of these weaponized vulnerabilities being actively exploited poses a severe threat to government security.
Federal agencies are seeking more proactive strategies to protect their digital domains. That said, agencies need a strategic approach to cyber risk management, where risk prioritization is critical. A comprehensive and unified perspective on managing cyber risk is essential to converting intricate data into actionable intelligence.
To effectively combat cyber threats, agencies must employ a dual approach of risk prioritization and automation. This strategy facilitates a timely response to cyber threats and aids in their prevention. By methodically identifying and addressing vulnerabilities, federal resources can be allocated precisely, ensuring that the most critical threats are eliminated first.
Steadfast risk scoring can protect critical federal data
In federal cybersecurity, risk prioritization scoring is akin to a war doctrine — it’s steadfast and unchanging. Risk prioritization remains the backbone for operational decisions, whether federal security teams respond to an incident or implement necessary patches. The crux of the matter lies in the composition of an agency’s scoring system. A risk score is measured as an index reflecting operational reality, and the quality of the underlying data determines its efficacy. A high-risk score (e.g., a risk score of “900”) indicates a vulnerability that is not only remotely exploitable but also has verifiable evidence of active exploitation.
A robust scoring system incorporates various heuristics to assess the severity of a vulnerability. It evaluates the exposure level, known exploits and the potential for unauthorized access or data theft. The system’s sophistication is evident in its ability to weigh these factors and produce a score that accurately reflects the urgency and risk associated with each vulnerability.
To that end, many agencies lack the proper scoring indexes for risk prioritization. However, federal leaders can leverage risk prioritization and automation to shape the future of federal cybersecurity in various ways.
Safeguarding critical federal data using automation
One of the most daunting tasks in cybersecurity is recognizing and safeguarding critical assets, such as financial management and human resource systems. The complexity of modern federal IT environments, which often include a mix of on-premises, cloud and mobile assets, can make it challenging to maintain a comprehensive inventory. Additionally, the rapid pace of technological change, agency legacy technology and the continuous evolution of foreign and domestic cyber threats can outpace traditional asset management approaches.
The Cybersecurity and Infrastructure Security Agency’s Binding Operational Directive 23-01 addresses these challenges by mandating federal agencies to perform automated asset discovery and vulnerability enumeration. This directive helps with risk prioritization by ensuring that all assets are accounted for and assessed for vulnerabilities regularly. By requiring automated processes, the directive aims to reduce human error and ensure that asset discovery and vulnerability assessments are conducted promptly and consistently.
Through asset management and automated scanning solutions, agencies can gain insights into their digital footprint, network vulnerabilities and the overall state of their cybersecurity posture.
Empowering federal cybersecurity teams with actionable Intelligence and holistic risk perspectives
In the intricate web of modern digital infrastructures, the assortment of tools managing assets and vulnerabilities underscores the need for a cohesive strategy in risk prioritization. The crux of this strategy hinges on attaining a holistic perspective and seamless integration amidst the diverse risk landscape inherent in today’s multifaceted government environments.
In this case, the objective is to furnish security teams with tangible, actionable intelligence. A consolidated view of risks empowers federal security teams to identify critical threats and strategically direct their resources. Implementing a federal risk management strategy that aggregates and interprets data from various sources, culminating in a stratified risk report, equips security teams to respond promptly and knowledgeably, fortifying defenses against potential cyber incursions.
Using AI/ML for advanced risk prioritization
Artificial intelligence and machine learning can enhance risk prioritization by enabling agencies to proactively identify and mitigate potential threats based on predictive analytics and pattern recognition. For instance, the Department of Homeland Security (DHS) leverages AI/ML to strengthen its cybersecurity measures, shifting from reactive, signature-based defense systems to a more dynamic, proactive security posture. As a result, DHS can prioritize risks based on their potential impact and likelihood, ensuring resources are allocated efficiently to protect against the most significant threats.
Priority-based automation strategies: The future of federal cyber risk management
Federal agencies must proactively prioritize and automate cybersecurity risks to manage threats effectively. Risk prioritization is essential within a federal risk management framework, helping security teams identify the most urgent vulnerabilities that require immediate attention while addressing others later. This strategic approach optimizes resource allocation to target the most severe threats promptly. Automation enhances this process by accelerating the detection and remediation of these vulnerabilities, thus shortening the response time from discovery to resolution.
By employing a cohesive risk management strategy, agencies can overcome the constraints of piecemeal evaluations, strengthen their defenses around vital assets and uphold resilience amidst continually changing cyber threats.
Richard Seiersen is chief risk technology officer at Qualys.
How risk prioritization and automation can shape the future of federal cybersecurity
Federal agencies face a formidable challenge in navigating the deluge of emerging vulnerabilities while managing the remediation of existing ones.
Federal agencies face a formidable challenge in navigating the deluge of emerging vulnerabilities while managing the remediation of existing ones.
According to research from the Qualys Threat Research Unit (TRU), nearly 30,000 vulnerabilities were discovered and published on the Common Vulnerabilities and Exposures (CVE) list in 2023, up from just over 25,000 in 2022.
More alarmingly, the Qualys TRU team identified 206 CVEs that were published and weaponized, surpassing numbers from recent years. This is significant because the increased likelihood of these weaponized vulnerabilities being actively exploited poses a severe threat to government security.
Federal agencies are seeking more proactive strategies to protect their digital domains. That said, agencies need a strategic approach to cyber risk management, where risk prioritization is critical. A comprehensive and unified perspective on managing cyber risk is essential to converting intricate data into actionable intelligence.
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To effectively combat cyber threats, agencies must employ a dual approach of risk prioritization and automation. This strategy facilitates a timely response to cyber threats and aids in their prevention. By methodically identifying and addressing vulnerabilities, federal resources can be allocated precisely, ensuring that the most critical threats are eliminated first.
Steadfast risk scoring can protect critical federal data
In federal cybersecurity, risk prioritization scoring is akin to a war doctrine — it’s steadfast and unchanging. Risk prioritization remains the backbone for operational decisions, whether federal security teams respond to an incident or implement necessary patches. The crux of the matter lies in the composition of an agency’s scoring system. A risk score is measured as an index reflecting operational reality, and the quality of the underlying data determines its efficacy. A high-risk score (e.g., a risk score of “900”) indicates a vulnerability that is not only remotely exploitable but also has verifiable evidence of active exploitation.
A robust scoring system incorporates various heuristics to assess the severity of a vulnerability. It evaluates the exposure level, known exploits and the potential for unauthorized access or data theft. The system’s sophistication is evident in its ability to weigh these factors and produce a score that accurately reflects the urgency and risk associated with each vulnerability.
To that end, many agencies lack the proper scoring indexes for risk prioritization. However, federal leaders can leverage risk prioritization and automation to shape the future of federal cybersecurity in various ways.
Safeguarding critical federal data using automation
One of the most daunting tasks in cybersecurity is recognizing and safeguarding critical assets, such as financial management and human resource systems. The complexity of modern federal IT environments, which often include a mix of on-premises, cloud and mobile assets, can make it challenging to maintain a comprehensive inventory. Additionally, the rapid pace of technological change, agency legacy technology and the continuous evolution of foreign and domestic cyber threats can outpace traditional asset management approaches.
The Cybersecurity and Infrastructure Security Agency’s Binding Operational Directive 23-01 addresses these challenges by mandating federal agencies to perform automated asset discovery and vulnerability enumeration. This directive helps with risk prioritization by ensuring that all assets are accounted for and assessed for vulnerabilities regularly. By requiring automated processes, the directive aims to reduce human error and ensure that asset discovery and vulnerability assessments are conducted promptly and consistently.
Through asset management and automated scanning solutions, agencies can gain insights into their digital footprint, network vulnerabilities and the overall state of their cybersecurity posture.
Empowering federal cybersecurity teams with actionable Intelligence and holistic risk perspectives
In the intricate web of modern digital infrastructures, the assortment of tools managing assets and vulnerabilities underscores the need for a cohesive strategy in risk prioritization. The crux of this strategy hinges on attaining a holistic perspective and seamless integration amidst the diverse risk landscape inherent in today’s multifaceted government environments.
Read more: Commentary
In this case, the objective is to furnish security teams with tangible, actionable intelligence. A consolidated view of risks empowers federal security teams to identify critical threats and strategically direct their resources. Implementing a federal risk management strategy that aggregates and interprets data from various sources, culminating in a stratified risk report, equips security teams to respond promptly and knowledgeably, fortifying defenses against potential cyber incursions.
Using AI/ML for advanced risk prioritization
Artificial intelligence and machine learning can enhance risk prioritization by enabling agencies to proactively identify and mitigate potential threats based on predictive analytics and pattern recognition. For instance, the Department of Homeland Security (DHS) leverages AI/ML to strengthen its cybersecurity measures, shifting from reactive, signature-based defense systems to a more dynamic, proactive security posture. As a result, DHS can prioritize risks based on their potential impact and likelihood, ensuring resources are allocated efficiently to protect against the most significant threats.
Priority-based automation strategies: The future of federal cyber risk management
Federal agencies must proactively prioritize and automate cybersecurity risks to manage threats effectively. Risk prioritization is essential within a federal risk management framework, helping security teams identify the most urgent vulnerabilities that require immediate attention while addressing others later. This strategic approach optimizes resource allocation to target the most severe threats promptly. Automation enhances this process by accelerating the detection and remediation of these vulnerabilities, thus shortening the response time from discovery to resolution.
By employing a cohesive risk management strategy, agencies can overcome the constraints of piecemeal evaluations, strengthen their defenses around vital assets and uphold resilience amidst continually changing cyber threats.
Richard Seiersen is chief risk technology officer at Qualys.
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