Hybrid Social Engineering

5 automated security scanners

Trust Transference Attacks

Purpose: The Trust Transference Attacks Scanner is designed to identify potential vulnerabilities in how trust is managed and exploited by malicious actors within a company’s security documentation, public policies, and trust center information. This helps in detecting bot-established credibility, human exploitation of gained trust, and relationship leveraging within the organization.

What It Detects:

Security Policy Indicators: Identifies the presence or absence of key security policy documents such as “security policy,” “incident response,” “data protection,” and “access control.”
Maturity Indicators: Checks for compliance certifications and maturity indicators like SOC 2, ISO 27001, penetration testing, and vulnerability scanning.
Trust Center Information: Evaluates the content of trust center pages to ensure they provide comprehensive information about security measures and incident response protocols.
Public Policy Pages: Analyzes public policy pages for transparency in security practices and adherence to best practices.
Relationship Leveraging Patterns: Detects patterns where relationships are leveraged or exploited, such as excessive trust given to third parties without proper vetting or oversight.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com). This is necessary for the scanner to gather information from the specified company website.
company_name (string): Company name for statement searching (e.g., “Acme Corporation”). This helps in identifying relevant documents and policies within the company’s documentation.

Business Impact: Identifying these vulnerabilities is crucial as it directly impacts the security posture of an organization, potentially exposing sensitive information to malicious actors or leading to trust exploitation that could compromise internal relationships and processes.

Risk Levels:

Critical: Conditions where critical risks are identified in security policies, such as significant gaps in incident response protocols or lack of data protection measures.
High: Risks associated with high-level vulnerabilities like incomplete or outdated security policies, inadequate trust center information, or failure to disclose third-party relationships clearly.
Medium: Vulnerabilities that are less severe but still pose a risk, such as partial compliance with standards (e.g., SOC 2 not fully met) or unclear public policy disclosures regarding security practices.
Low: Informational findings indicating minor issues like typographical errors in documentation or minor discrepancies in trust center information disclosure.
Info: Findings that provide minimal risk but contribute to a more comprehensive understanding of the company’s security posture, such as presence of basic security policies and some level of transparency in public policy pages.

Example Findings:

The company lacks a comprehensive “security policy” document, which could lead to high risks if an incident occurs without clear guidelines for response.
Public policy pages do not disclose details about third-party relationships or compliance certifications like ISO 27001, indicating potential trust exploitation and inadequate security practices.

Multi-channel Hybrid Targeting

Purpose: The Multi-channel Hybrid Targeting Scanner is designed to detect cross-platform coordination, channel-switching attacks, and comprehensive targeting by identifying patterns in security policies, incident response, data protection, and access control across multiple channels. This helps organizations understand if they are being targeted through coordinated efforts that switch between different communication platforms.

What It Detects:

Security Policy Indicators: Identifies the presence or absence of key security policy terms such as “security policy,” “incident response,” “data protection,” and “access control.”
Maturity Indicators: Looks for compliance certifications and maturity indicators like SOC 2, ISO 27001, penetration testing, and vulnerability scanning.
Cross-platform Coordination Patterns: Detects coordinated messaging across different channels (e.g., website, social media, press releases) that indicate a targeted attack strategy.
Channel-Switching Attacks: Identifies instances where attackers switch communication channels to evade detection or mislead the organization.
Comprehensive Targeting Indicators: Analyzes the depth and breadth of targeting efforts by identifying multiple points of engagement across various platforms and documents.

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 for organizations aiming to secure their communications and data across multiple channels, helping them identify potential threats from coordinated attacks that may evade traditional detection methods. Understanding these patterns can significantly enhance an organization’s security posture by enabling proactive measures against targeted attacks.

Risk Levels:

Critical: Severe conditions where critical aspects of the scanner’s purpose are not met or significant vulnerabilities in the system are detected.
High: Conditions that indicate high risk, such as widespread non-compliance with basic security policies or substantial exposure to data breaches.
Medium: Conditions suggesting medium risk, including partial compliance with key security measures or moderate exposure to potential threats.
Low: Informal findings indicating minimal risks, typically for less critical areas of the organization’s security infrastructure.
Info: Informational findings that provide insights but do not directly impact core security functions.

Example Findings:

A company may have a high risk of being targeted if they lack explicit data protection policies mentioned in their website content, which could be easily exploited by attackers looking to breach sensitive information.
An organization with no mention of SOC 2 compliance in its public statements might face medium risk, as it indicates potential gaps in security practices that are essential for protecting customer and organizational data.

Conversation Thread Hijacking

Purpose: The Conversation Thread Hijacking Scanner is designed to identify and mitigate potential threats posed by malicious actors attempting to infiltrate, manipulate, and exploit ongoing discussions in online forums, social media, and other public communication channels. This tool aims to protect the integrity of conversations and safeguard communities from disinformation campaigns and harmful content insertion.

What It Detects:

Unauthorized Discussion Infiltration: Identifies instances where unauthorized users insert themselves into ongoing discussions without prior context or relevance.
Context-Aware Insertion: Analyzes the timing and content of messages to determine if they are inserted in a way that manipulates the existing conversation flow.
Relationship Exploitation: Identifies attempts to exploit pre-existing relationships within a community to gain trust and influence.
Malicious Content Insertion: Looks for the insertion of malicious links, attachments, or other harmful content into ongoing conversations.
Disinformation Campaigns: Identify coordinated efforts to spread misinformation or false information within a community.

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 for maintaining the authenticity and trustworthiness of online conversations, which is essential in preventing financial loss, reputational damage, and public mistrust that can result from malicious infiltration and manipulation of discussions.

Risk Levels:

Critical: Detects unauthorized users inserting themselves into ongoing discussions without prior context or relevance.
High: Identifies messages inserted to manipulate the existing conversation flow or shift it towards specific topics or narratives.
Medium: Recognizes attempts to exploit personal connections or shared interests for influence within a community.
Low: Flags suspicious links or files that may contain malicious content, which could be used in phishing or malware distribution.
Info: Detects repeated messages or coordinated efforts indicating disinformation campaigns, providing informational insights into potential threats.

If the README doesn’t specify exact risk levels, infer them based on the scanner’s purpose and impact.

Example Findings:

A new participant joined a discussion about cybersecurity without any prior knowledge or relevance to the topic, indicating unauthorized infiltration.
An inserted message in a medical forum subtly shifts the conversation towards alternative medicine, exploiting context-aware manipulation techniques.

Bot-Human Attack Coordination

Purpose: The Bot-Human Attack Coordination Scanner is designed to detect and analyze patterns of initial automation followed by human intervention in security documentation and public policies. It aims to identify potential coordinated attack strategies, helping organizations better understand their exposure to cyber threats and improve their response mechanisms.

What It Detects:

Automation Indicators: Detection of automated scripts or tools mentioned in security documentation that could be used for scanning and probing without human intervention.
Human Takeover Patterns: Recognition of phrases indicating the need for human intervention after initial automation, suggesting a shift from purely automated processes to more interactive strategies.
Escalation Handoffs: Detection of mentions of incidents requiring manual response from human operators, highlighting the handoff process between automated systems and human operators.
Combined Technique Approaches: Recognition of combined use of different attack techniques in policies or documentation, indicating a strategic integration of multiple methods to enhance security measures.
Policy Maturity Indicators: Detection of compliance certifications and maturity models that reflect robust security practices and standards adherence.

Inputs Required:

domain (string): The primary domain to analyze, which could be the company’s main website address.
company_name (string): The official name of the company for which the documentation is being reviewed, used in search queries to gather relevant policy statements and security information.

Business Impact: This scanner helps organizations assess their cybersecurity posture by identifying potential gaps where automation might be insufficient or where human intervention is crucial. Understanding these points can help prioritize investments in more sophisticated automated tools or enhance incident response capabilities, thereby improving the overall security posture against coordinated attacks.

Risk Levels:

Critical: Conditions that could lead to immediate and severe impacts on business operations, such as unauthorized access to sensitive data or critical infrastructure systems.
High: Situations where automation might fail to detect emerging threats effectively, requiring manual intervention too frequently, which can strain resources and delay response times.
Medium: Where the balance between automated detection and human oversight is compromised, leading to a mix of effective protection and potential vulnerabilities that could be exploited by attackers.
Low: Minimal impact on security posture where automation provides adequate coverage with minimal need for human intervention, indicating a well-balanced approach in cyber defense.
Info: Informal or advisory findings related to best practices compliance but not directly impacting critical operations.

Example Findings:

“The company’s data breach response policy mentions the use of automated scanning tools followed by manual review for high-risk incidents, indicating a balanced approach.”
“Incorporating ISO 27001 standards in their security documentation suggests a commitment to robust information security practices.”

Purpose: The Reinforcement Learning Social Engineering Scanner is designed to detect adaptive phishing techniques and refine response-based strategies by analyzing company behavior and security policies. It aims to identify potential vulnerabilities in how organizations handle social engineering attacks, ensuring that their responses are effective and not easily manipulated.

What It Detects:

Adaptive Phishing Indicators: The scanner identifies patterns indicative of sophisticated phishing attempts and detects variations in phishing tactics over time to understand adaptive strategies.
Response-Based Technique Refinement: It analyzes how organizations refine their response techniques after detected attacks, evaluating the effectiveness and adaptability of security measures in response to social engineering.
Behavior-Informed Attacks: The scanner identifies behaviors that may indicate susceptibility to behavior-informed attacks and detects patterns suggesting that attackers are tailoring their strategies based on observed organizational behavior.
Security Policy Compliance: It checks for the presence and adherence to relevant security policies, ensuring compliance with standards such as SOC 2, ISO 27001, and other certifications.
Public Documentation Analysis: The scanner reviews publicly available documentation for security-related information, assessing the quality and comprehensiveness of trust center information and policy pages.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com) - This is necessary for scanning the website to detect potential vulnerabilities in handling social engineering attacks.
company_name (string): Company name for statement searching (e.g., “Acme Corporation”) - Providing the company’s name helps in searching and analyzing relevant security documents and policies.

Business Impact: This scanner is crucial for organizations to assess their vulnerability to adaptive phishing techniques and refine their response strategies. By identifying potential vulnerabilities, the organization can enhance its security posture against sophisticated social engineering attacks, protecting sensitive information and maintaining trust with stakeholders.

Risk Levels:

Critical: The scanner identifies critical issues such as unpatched systems or unauthorized access points that could lead to immediate data breaches or significant damage to organizational assets.
High: High-risk findings include widespread phishing attempts detected by the scanner, which may indicate a lack of effective security measures against adaptive attacks.
Medium: Medium-risk findings involve less severe vulnerabilities such as outdated software versions or incomplete security policies that could be exploited with some effort but do not pose an immediate threat.
Low: Low-risk findings are generally informational in nature, providing suggestions for improving documentation or enhancing general cybersecurity practices without immediate risk to the organization.
Info: These findings provide additional insights into the effectiveness of the company’s security measures and public disclosures, contributing to a comprehensive understanding of the security posture.

If specific conditions for each risk level are not detailed in the README, these descriptions are inferred based on the purpose of the scanner and its potential impact on organizational security.

Example Findings:

The scanner may flag a company with outdated SSL certificates as a critical issue due to the inherent risks associated with insecure data transmission.
A high-risk finding might be identified when the scanner detects multiple phishing attempts that bypass previous security measures, indicating an urgent need for improved adaptive defense strategies.