Cognitive Defense Design

5 automated security scanners

Decision Support Optimization

Purpose: The Decision Support Optimization Scanner evaluates how well companies use tools and present information to support decision-making in organizational security documentation. It identifies gaps in tool assistance, information presentation, and cognitive amplification that can enhance decision-making processes.

What This Scanner Detects:

Tool Assistance Effectiveness:
- Identify mentions of specific security tools (e.g., SIEM, EDR) without detailed usage descriptions.
- Detect vague references to “automated systems” without specifying their role or impact.
- Verify if tool recommendations are aligned with industry best practices.
Information Presentation Clarity:
- Check for complex technical jargon that may confuse stakeholders.
- Evaluate the use of visual aids (e.g., diagrams, charts) in explaining security concepts.
- Assess the readability and accessibility of security documentation.
Cognitive Amplification Techniques:
- Identify instances where cognitive biases might influence decision-making (e.g., confirmation bias).
- Detect over-reliance on single-point solutions without considering broader security contexts.
- Evaluate the inclusion of diverse perspectives and expert opinions in security strategies.
Policy Indicators:
- Search for key policy terms such as “security policy,” “incident response,” “data protection,” and “access control.”
- Verify if policies are up-to-date and aligned with current threats and compliance requirements.
Maturity Indicators:
- Look for certifications like SOC 2, ISO 27001, penetration testing, and vulnerability assessments.
- Assess the maturity of security practices by evaluating the presence of these indicators in company documentation.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com)
company_name (string): Company name for statement searching (e.g., “Acme Corporation”)

Business Impact: This scanner is crucial as it helps organizations identify and address weaknesses in their security documentation, which can directly impact the effectiveness of their security posture against evolving threats. By improving tool usage, enhancing information clarity, and promoting cognitive amplification techniques, companies can better protect sensitive data and make informed decisions that align with industry standards.

Risk Levels:

Critical: Findings that indicate a significant gap in tool assistance, information presentation, or cognitive amplification within security documentation could lead to severe vulnerabilities being overlooked, potentially compromising critical assets.
High: Issues such as outdated policies or lack of maturity indicators can significantly hinder the organization’s ability to respond effectively to cyber threats and compliance requirements.
Medium: There may be some gaps in tool usage descriptions or information presentation that require further investigation but do not pose immediate high risks.
Low: Minor issues related to readability or minor cognitive biases might affect efficiency but generally do not impact overall security significantly.
Info: Informal findings such as the presence of certain terms without detailed context could be indicative of good practices, though they are less critical in nature.

Example Findings:

The company mentions SIEM tools for threat detection but does not provide details on how these tools are configured or utilized within their security infrastructure.
Informational documents use complex jargon that is difficult for non-technical staff to understand, potentially leading to miscommunications and inefficiencies in decision-making processes.

Automation Balance Strategy

Purpose: The Automation Balance Strategy Scanner evaluates the balance between human and machine roles in security operations to ensure appropriate automation levels. It detects whether human-machine teaming is optimized for augmentation rather than replacement, and verifies that automated systems are used judiciously based on judgment-appropriate criteria.

What It Detects:

Human-Machine Teaming Indicators: Identifies instances where human oversight is emphasized alongside machine capabilities, detecting collaboration between humans and machines through specific language.
Augmentation vs. Replacement Patterns: Tests for statements suggesting augmentation (e.g., “AI assists analysts”) and checks for phrases implying replacement (e.g., “AI replaces analysts”), assessing the role of automation in relation to human expertise.
Judgment-Appropriate Automation Language: Identifies criteria for when automation is deemed appropriate, detecting language indicating that decisions are based on judgment and risk assessment.
Security Policy Indicators: Searches for mentions of security policies related to human-machine interaction, including incident response plans involving both humans and machines, and evaluates data protection measures incorporating automated systems.
Maturity Indicators: Identifies certifications or standards indicating maturity in automation practices (e.g., SOC 2, ISO 27001), references to penetration testing and vulnerability assessments, and the presence of regular security audits and evaluations involving automation.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com) - This parameter is essential for searching company sites to collect relevant documents.
company_name (string): Company name for statement searching (e.g., “Acme Corporation”) - Used in the search query to identify specific statements related to the organization’s security practices.

Business Impact: Evaluating the balance between human and machine roles is crucial for ensuring a robust security posture that leverages both human expertise and automated systems effectively, thereby enhancing overall decision-making capabilities and risk management strategies.

Risk Levels:

Critical: Findings indicating inadequate human oversight in conjunction with automation or where automation is described as replacing critical human functions could be considered critical.
High: Issues such as poorly defined criteria for appropriate automation use or insufficient security policies governing interactions between humans and machines may lead to high risk findings.
Medium: Medium severity might include situations where automation is overused without sufficient human judgment, leading to potential operational inefficiencies or missed opportunities for improvement.
Low: Informal language indicating a flexible approach to automation that allows for adaptability in response to changing threats could be considered low risk if it does not compromise security objectives.
Info: Minimal mentions of automation without significant implications on the balance between humans and machines might fall under informational findings.

Example Findings:

“The documentation suggests a strong partnership between human analysts and AI, with clear language indicating that AI assists but does not replace human decision-making.”
“There is concern over the lack of specific criteria for automation use in high-risk scenarios, which could lead to inappropriate reliance on automated systems.”

Human-Centered Security Design

Purpose: The Human-Centered Security Design Scanner evaluates the balance between usability and security to ensure that controls are appropriate and do not create unnecessary friction for users. It also considers cognitive load, aiming to minimize complexity in security processes to avoid overwhelming users with information overload.

What It Detects:

Identify instances where security measures significantly impede usability.
Check for excessive complexity in authentication processes.
Evaluate the presence of clear and concise security instructions.
Assess whether controls are proportionate to the risk they mitigate.
Detect overly restrictive policies that may lead to user frustration or bypass attempts.
Verify that security measures do not create unnecessary friction for legitimate users.
Analyze the complexity of security processes and their impact on user cognitive load.
Identify potential areas where security instructions are too complex or overwhelming.
Evaluate the effectiveness of security training materials in reducing cognitive burden.
Search for policy indicators such as “security policy,” “incident response,” “data protection,” and “access control.”
Verify that policies are up-to-date and comprehensive.
Check for the presence of maturity indicators like SOC 2, ISO 27001, penetration testing, and vulnerability scanning.
Review trust center information for transparency regarding security practices.
Ensure that trust center content is clear and accessible to users.
Verify that trust center pages provide adequate information about data protection and incident response procedures.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com)
company_name (string): Company name for statement searching (e.g., “Acme Corporation”)

Business Impact: This scanner is crucial as it ensures that security measures do not unintentionally hinder user experience, which can lead to increased risk of data breaches and loss of trust in the organization’s digital services.

Risk Levels:

Critical: Conditions where security controls significantly impede usability or where cognitive overload is likely due to overly complex processes.
High: Conditions where policies are outdated, incomplete, or not enforced effectively, potentially leading to significant vulnerabilities or data breaches.
Medium: Conditions where there may be some usability issues with security measures but overall the system remains reasonably secure and usable.
Low: Informal or non-critical findings that do not significantly impact user experience or security posture.
Info: General informational findings about compliance, policies, and practices without immediate risk.

Example Findings:

The login page requires multiple factor authentication which is overly complex and may lead to usability issues for users who find the process too cumbersome.
A privacy policy that is difficult to navigate or understand could result in confusion among users about their data handling practices, potentially leading to trust issues.

Team Composition Strategy

Purpose: The Team Composition Strategy Scanner is designed to analyze the cognitive strengths, analysis style diversity, and background variation within a team. This helps in identifying gaps that could be exploited by adversaries, ensuring a well-rounded approach to strategic defense.

What It Detects:

Cognitive Strengths Identification: Detect patterns indicating diverse thinking styles (e.g., analytical, creative), strong problem-solving skills, critical thinking, and innovation.
Analysis Style Diversity: Check for a mix of quantitative and qualitative analysis approaches, different methodologies in security assessments, and various perspectives on threat modeling.
Background Variation: Identify team members with diverse backgrounds across multiple domains (e.g., software development, network security), including experience from different industries or sectors.
Policy and Procedure Review: Analyze company security documentation for comprehensive policies, incident response plans covering various scenarios, data protection measures, and access control protocols.
Compliance Certification Verification: Identify SOC 2, ISO 27001, and other relevant compliance certifications, penetration testing, vulnerability assessments, and regular security audits and updates.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com)
company_name (string): Company name for statement searching (e.g., “Acme Corporation”)

Business Impact: This scanner is crucial as it helps in identifying the cognitive and analytical diversity within a team, which is essential for developing robust strategies against potential adversaries who might exploit gaps in understanding or approach.

Risk Levels:

Critical: Conditions that could lead to significant security breaches or critical vulnerabilities in systems.
High: Conditions that pose high risks but are not as severe as critical issues, such as inadequate access controls or missing incident response plans.
Medium: Conditions indicating potential weaknesses that need attention but do not immediately threaten the core security of the organization.
Low: Informal or general findings that might suggest minor improvements in policies or practices without significant risk to the enterprise.
Info: General information or non-critical observations that provide context but do not directly impact security posture.

Example Findings:

The team lacks a diverse background, primarily consisting of technical experts with limited exposure to strategic management and policy-making aspects of cybersecurity.
There is a lack of documented incident response plans that cover all critical scenarios, indicating potential gaps in preparation for cyber threats.

Training Cognitive Resilience

Purpose: The Training Cognitive Resilience Scanner is designed to assess the effectiveness of stress inoculation programs, pattern recognition training, and intuition development within an organization by evaluating its internal security documentation, public policies, trust center information, and compliance certifications.

What It Detects:

Security Policy Indicators: Identifies the presence or absence of key security policy documents, comprehensive incident response plans, data protection measures, and robust access control mechanisms.
Maturity Indicators: Confirms SOC 2 compliance certification, validates adherence to ISO 27001 standards, detects regular penetration testing activities, and identifies vulnerability scanning and assessment processes.
Pattern Recognition Development: Analyzes the use of specific security-related keywords and phrases in documentation, evaluates the depth and breadth of incident response strategies, assesses the clarity and detail of data protection policies, and reviews access control procedures for thoroughness and effectiveness.
Intuition Training Indicators: Identifies proactive security measures beyond reactive responses, detects the presence of advanced threat detection capabilities, evaluates the organization’s ability to anticipate and mitigate potential threats, and checks for ongoing training programs focused on cognitive resilience.
Stress Inoculation Effectiveness: Assesses the frequency and quality of stress inoculation exercises, evaluates the organization’s preparedness for high-stress security incidents, identifies the integration of psychological support in security protocols, and reviews the effectiveness of communication strategies during simulated attacks.

Inputs Required:

domain (string): The primary domain to analyze, such as “acme.com”.
company_name (string): The company name for statement searching, such as “Acme Corporation”.

Business Impact: This scanner is crucial for organizations aiming to enhance their security posture by developing cognitive resilience through effective training programs and robust policies. It helps in identifying gaps and areas for improvement in security practices that are essential for the overall safety and compliance of an organization.

Risk Levels:

Critical: Conditions where critical vulnerabilities or non-compliance with mandatory standards exist, potentially leading to severe data breaches or legal repercussions.
High: Conditions where high-risk policies or significant gaps in security measures are identified, increasing the likelihood of a successful attack and potential damage.
Medium: Conditions where moderate risks are present, requiring attention for improvement but not as critical as higher severity issues.
Low: Informal or non-critical findings that do not significantly impact security posture but may suggest areas for optimization in training and documentation practices.
Info: General information about the scanner’s operation and findings, providing a baseline understanding without immediate action required.

If specific risk levels are not detailed in the README, these inferred descriptions can guide assessment of severity based on the purpose and impact of the scanner.

Example Findings:

The company lacks an up-to-date incident response plan documented clearly in the security policies.
There is no mention of ISO 27001 compliance within the public policy statements, indicating a gap in recognized international standards adherence.