Deception Capability Assessment

5 automated security scanners

Honeypot Believability Scoring

Purpose: The Honeypot Believability Scoring Scanner is designed to assess the authenticity of honeypots by identifying artificiality indicators, technical inconsistencies, and behavioral inauthenticity. This tool helps organizations ensure that their deception capabilities are effective and indistinguishable from real systems, enhancing overall security posture.

What It Detects:

Artificiality Indicators: The scanner detects overly simplistic or repetitive content that suggests automated generation (e.g., default configurations), unusual or inconsistent metadata (e.g., timestamps or authorship information), and the presence of placeholder text or generic content lacking specificity.
Technical Inconsistencies: It checks for mismatched software versions or technologies, outdated or deprecated components, discrepancies in network configurations and service availability, and misconfigurations that could indicate a lack of proper setup or maintenance.
Behavioral Inauthenticity: The scanner analyzes user interaction logs to identify unnatural or scripted behavior, evaluates login patterns for anomalies (e.g., excessive failed attempts or unusual timing), and assesses file access sequences for deviations from typical usage patterns.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com). This input helps in assessing the authenticity of honeypots related to a specific website.
company_name (string): Company name for statement searching (e.g., “Acme Corporation”). This parameter is used to search and evaluate company statements for indications of deception technologies or practices.

Business Impact: Ensuring that deception capabilities are authentic and effective is crucial for maintaining a robust security posture against sophisticated cyber threats. The ability to detect inauthentic honeypots can significantly enhance the reliability of cybersecurity measures, reducing the risk of false reassurances and improving overall defense strategies.

Risk Levels:

Critical: Conditions that could lead to immediate system compromise or significant data loss are considered critical. These include mismatched software versions that align with known vulnerabilities exploited by advanced threats.
High: High-risk findings involve technical inconsistencies such as outdated components and misconfigurations that might be exploited by less sophisticated adversaries but still pose a serious threat to security.
Medium: Medium-severity risks pertain to behavioral inauthenticity, where the system’s behavior deviates from expected norms, potentially allowing limited exploitation or observation of sensitive information.
Low: Low-risk findings include minor artificiality indicators and inconsequential technical inconsistencies that do not significantly impact security posture but are still indicative of potential issues requiring attention.
Info: Informational findings provide context about the system’s configuration and can be used for continuous improvement in honeypot effectiveness without immediate concern for security risks.

Example Findings:

“The website contains overly simplistic content that suggests automated generation, indicating a high risk of using default configurations.”
“Login attempts show an unusual pattern with excessive failed login attempts within a short period, suggesting potential honeypot usage.”

Deception Diversity Assessment

Purpose: The Deception Diversity Assessment Scanner is designed to identify and assess limitations in technology variety, narrow scenario descriptions, and restricted target audiences within a company’s security documentation and public policies. This tool aims to uncover potential gaps that could be exploited by adversaries, thereby enhancing the overall security posture of the organization.

What It Detects:

Technology Variety Limitations: The scanner identifies repeated mentions of specific technologies without diversity and checks for over-reliance on single vendors or products.
Scenario Narrowness: It detects limited scenarios described in security policies and incident responses, flagsging generic or overly simplistic response strategies.
Target Audience Restrictions: The scanner identifies language that targets a narrow audience, such as technical experts only, and checks for lack of communication clarity for non-technical stakeholders.
Policy Indicators Absence: It searches for the presence of key policy indicators like “security policy,” “incident response,” “data protection,” and “access control.” It also flags missing or inadequate coverage of these critical areas.
Maturity Indicators Absence: The scanner looks for maturity indicators such as SOC 2, ISO 27001, penetration testing, and vulnerability scanning, identifying gaps in compliance certifications and security assessments.

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 potential vulnerabilities and gaps in the company’s security documentation, which could be exploited by adversaries. By detecting these issues early, organizations can implement appropriate countermeasures to mitigate risks effectively.

Risk Levels:

Critical: The scanner identifies critical findings such as missing or inadequate coverage of “security policy,” “incident response,” and “data protection.”
High: High severity findings include over-reliance on specific technologies and narrow scenario descriptions in security policies.
Medium: Medium severity includes restrictions in communication for non-technical stakeholders and lack of diversity in technology mentions.
Low: Low severity involves missing maturity indicators like SOC 2 or ISO 27001 compliance, which are less critical but still need attention to improve overall security posture.
Info: Informational findings pertain to the absence of specific policy indicators that do not directly impact security but could be improved for better clarity and coverage.

Example Findings:

The scanner might flag a company heavily relying on proprietary software without considering open-source alternatives, which is critical as it limits technology variety.
A scenario where all incident responses are described in the same narrow format indicates high severity since it restricts flexibility and adaptability to new threats.

Honeytoken Distribution Coverage

Purpose: The Honeytoken Distribution Coverage Scanner is designed to identify deployment gaps, placement strategy weaknesses, and distribution inadequacy of honeytokens within an organization’s environment. This tool helps in identifying areas where attackers might exploit vulnerabilities due to poor deception capability implementation.

What It Detects:

Deployment Gaps: Identifies sections or systems without any honeytoken presence and checks for uneven distribution across different departments or business units.
Placement Strategy Weaknesses: Evaluates the strategic placement of honeytokens to ensure they cover critical assets and potential attack vectors, detecting clustering in non-critical areas.
Distribution Inadequacy: Assesses the overall number of honeytokens deployed relative to the size and complexity of the organization’s network, identifying underutilization or overutilization based on best practices.
Documentation and Policy Compliance: Reviews company security documentation for policies related to honeytoken deployment and management, checking adherence to compliance certifications that require specific deception capabilities.
Public Policy Pages and Trust Center Information: Analyzes public policy pages and trust center information for mentions of honeytokens or similar deception technologies, ensuring transparency and alignment with stated security practices.

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 strengthen their security posture by proactively identifying and addressing weaknesses in honeytoken deployment, which could be exploited by attackers to gain unauthorized access or information.

Risk Levels:

Critical: Conditions that indicate severe vulnerabilities or imminent threats where immediate action is required.
High: Conditions that suggest significant risks with potential consequences if not addressed promptly.
Medium: Conditions indicating moderate risk, requiring attention but not as urgent as critical issues.
Low: Conditions suggesting minimal risk, typically for informational purposes only.
Info: Informational findings that provide context but do not directly indicate a security risk.

If the specific risk levels are not detailed in the README, they have been inferred based on the scanner’s purpose and impact.

Example Findings:

A section of the network does not contain any honeytokens, indicating potential gaps for attackers to exploit.
Honeytokens are predominantly placed in non-critical areas, suggesting a need for better strategic planning against sophisticated threats.

Deception Environment Richness

Purpose: The Deception Environment Richness Scanner is designed to detect and highlight deficiencies in the fidelity of a deception environment, including its interaction capabilities and system emulation. This tool helps identify vulnerabilities that could be exploited by adversaries within such environments.

What It Detects:

Poor Environment Fidelity: Identifies discrepancies between what an environment claims to offer and its actual functionality, assessing whether emulated systems exhibit unrealistic or inconsistent behavior.
Limited Interaction Capability: Evaluates the breadth and depth of interactions possible within a deception environment, flagging any lack of diverse interaction methods like SSH in addition to HTTP.
Unconvincing System Emulation: Analyzes the realism of system emulations to ensure they are not easily distinguishable from real systems, focusing on default configurations or obvious indicators that might reveal them as fake.
Inadequate Data Variety: Assesses the authenticity and variety of data within a deception environment, detecting generic or repetitive data that could be easily recognized as deceptive.
Lack of Dynamic Behavior: Evaluates the dynamic aspects of systems in a deception environment, checking for static configurations or lack of automated responses to simulated attacks.

Inputs Required:

domain (string): The primary domain under examination, such as acme.com, which helps in identifying relevant security and deception-related pages on the company’s website.
company_name (string): The name of the company, like “Acme Corporation”, used for searching within their site to find mentions or references related to deception environments.

Business Impact: This scanner is crucial as it helps in enhancing the realism and effectiveness of security measures against sophisticated cyber threats by identifying gaps that could be exploited by adversaries during simulated attacks.

Risk Levels:

Critical: Severe deficiencies that directly impact the ability to detect or mitigate advanced persistent threats, potentially leading to significant security breaches.
High: Notable shortcomings in environment fidelity and interaction capabilities that increase the risk of successful exploitation by attackers.
Medium: Moderate issues requiring attention but not as critical as high risks, still posing a potential threat if left unaddressed.
Low: Minor deficiencies that may affect efficiency but do not significantly compromise security posture.
Info: Informative findings providing baseline knowledge about the environment’s current state without immediate risk to security.

If specific conditions for these risk levels are not detailed in the README, they have been inferred based on the purpose and impact of the scanner.

Example Findings:

The deception environment lacks clear indicators that distinguish it from a real network setup, making it difficult to assess its effectiveness against advanced threats.
Interaction methods available within the environment are limited primarily to HTTP, which does not reflect typical adversary behavior engaging with multiple protocols for reconnaissance and exploitation.

Deception Integration Depth

Purpose: The Deception Integration Depth Scanner is designed to uncover gaps in deception capabilities by analyzing company security documentation, public policy pages, trust center information, and compliance certifications. It helps identify issues such as lack of detailed descriptions for network pathways and asset connections, which could be exploited.

What It Detects:

Security Policy Indicators: Checks for the presence of key security policies such as security policy, incident response, data protection, and access control.
Maturity Indicators: Identifies compliance with standards like SOC 2, ISO 27001, penetration testing, and vulnerability scanning.
Limited Pathway Integration: Evaluates the depth of integration with real assets by looking for detailed descriptions of network pathways and asset connections.
Connection Authenticity Issues: Detects inconsistencies or vague descriptions that suggest potential deception in how connections to real assets are presented.
Isolation from Real Assets: Identifies signs of isolation, such as lack of references to actual systems or environments, indicating possible disconnection from genuine operational contexts.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com) - This is necessary for searching the company’s site and gathering relevant security documentation.
company_name (string): Company name for statement searching (e.g., “Acme Corporation”) - Used to search specific statements related to the company.

Business Impact: This scanner helps in assessing the robustness of a company’s security posture by identifying gaps that could be exploited through deception tactics. It is crucial for organizations aiming to enhance their security measures and compliance with industry standards.

Risk Levels:

Critical: Conditions where there are significant gaps in security policies, or lack of detailed asset connections which could lead to unauthorized access or data breaches.
High: Presence of incomplete or vague descriptions regarding network pathways and asset connections that might indicate a higher risk of deception or misrepresentation.
Medium: Inconsistencies in the presentation of security measures but not severe enough to be considered critical, potentially indicating areas for improvement.
Low: Minimal issues with security policies and asset connections, generally indicating good compliance and representation.
Info: Informal findings related to minor inconsistencies or missing information that does not significantly impact overall security posture.

Example Findings:

The company’s privacy policy lacks explicit data protection measures, which could be a critical issue if the organization handles sensitive user data.
Network diagrams in the compliance documentation do not detail specific asset connections, indicating high risk for limited pathway integration and potential deception issues.