Synthetic Actor Modeling

5 automated security scanners

Threat Group Capability Simulation

Purpose: The Threat_Group_Capability_Simulation Scanner is designed to detect Tactics, Techniques, and Procedures (TTP) emulation, resource projection, and motivation modeling by analyzing domain data through various threat intelligence feeds. This tool helps in identifying potential threats and understanding the capabilities of threat groups targeting the specified domain.

What It Detects:

Threat Indicator Detection:
- Identifies CVE numbers indicating known vulnerabilities.
- Looks for keywords related to malware, ransomware, trojans.
- Searches for command and control (C2) references.
- Detects phishing and credential harvesting attempts.
Exposure Indicator Detection:
- Finds mentions of exposed, leaked, or breached data.
- Identifies unauthorized access incidents.
- Locates data dumps or sensitive information leaks.
Vulnerability Analysis:
- Utilizes Shodan API to find exposed services and vulnerabilities.
- Checks VirusTotal for domain/IP reputation.
- Cross-references CISA KEV for known exploited vulnerabilities.
- Uses AbuseIPDB for IP reputation analysis.
- Queries NVD/CVE database for detailed vulnerability information.
Resource Projection:
- Analyzes the resources available to threat groups based on collected data.
- Projects potential attack vectors and resource capabilities.
Motivation Modeling:
- Models the motivations behind potential attacks by analyzing detected indicators.
- Provides insights into why a particular domain might be targeted.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com)
shodan_api_key: API key for Shodan to access DNS data.
virustotal_api_key: API key for VirusTotal to check domain/IP reputation.
abuseipdb_api_key: API key for AbuseIPDB to analyze IP reputation.
CISA KEV feed: Access to the database of known exploited vulnerabilities provided by CISA.
NVD/CVE database: For detailed vulnerability information queries.

Business Impact: This scanner is crucial for organizations looking to proactively identify and mitigate potential threats posed by sophisticated cyber threat groups. By detecting indicators of compromise, exposure of sensitive data, and potential vulnerabilities, the scanner helps in enhancing cybersecurity posture and protecting critical assets from exploitation.

Risk Levels:

Critical: Findings include high-risk CVE vulnerabilities that are actively exploited or have significant impact on system functionality.
High: Vulnerabilities exist but may not be currently exploited, with potential for severe consequences if breached.
Medium: Exposure to potential threats is identified, requiring attention and potentially remedial actions.
Low: Informational findings that do not directly pose a risk but could indicate areas for improvement in security practices.
Info: Minimal or no impact findings; generally considered non-critical unless part of broader threat detection scenarios.

Example Findings:

Detected unauthorized access on port 22, potentially indicating initial compromise and further exploitation.
Identified CVE-2021-44228 as a critical vulnerability affecting the Log4j library, which has been actively exploited in recent attacks.

Attack Infrastructure Prediction

Purpose: The Attack Infrastructure Prediction Scanner is designed to detect Command and Control (C2) evolution, hosting strategies, and communication methods by analyzing domain information through various threat intelligence feeds. This tool helps in identifying potential malicious activities and infrastructure changes that could pose a security risk.

What It Detects:

C2 Evolution Detection: Identifies new or evolving C2 servers using the Shodan API and looks for patterns indicating command and control activity such as “command\s*(?:and|&)\s*control|c2|c&c”.
Hosting Strategy Analysis: Analyzes hosting providers and IP reputation using VirusTotal API and AbuseIPDB to detect suspicious hosting strategies by identifying known exploited vulnerabilities from CISA KEV.
Communication Method Identification: Scans for communication methods used by potential malicious actors, including malware-related communications identified through regex patterns like “malware|ransomware|trojan”.
Vulnerability Exploitation Detection: Checks for known vulnerabilities associated with the domain/IP using the NVD/CVE database.
Exposure Indicator Analysis: Looks for indicators of data exposure or breaches, such as exposed, leaked, or breached patterns.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com)

Business Impact: This scanner is crucial for organizations aiming to maintain a secure and resilient cybersecurity posture by proactively identifying potential malicious activities and infrastructure changes associated with command and control activities, hosting strategies, and communication methods used by malicious actors.

Risk Levels:

Critical: Conditions that would lead to critical severity include the detection of new or evolving C2 servers actively communicating through known malware patterns, exploiting significant vulnerabilities from CISA KEV, and exposing sensitive data without proper security measures in place.
High: Conditions for high severity involve detecting compromised hosting providers or IP addresses associated with ransomware or trojan communications, indicating a high risk of data exposure or breach.
Medium: Conditions for medium severity include the identification of potential vulnerabilities that could be exploited by malicious actors but do not necessarily pose an immediate critical threat to data security.
Low: Informational findings at low severity involve general indicators of communication methods used in malware operations, which may require further investigation but are less likely to lead to significant security incidents.
Info: Conditions for informational findings include basic exposure indicators that could be indicative of potential data leaks or breaches, requiring monitoring and follow-up investigations.

Example Findings:

A domain is actively communicating with known C2 servers using malware communication patterns, indicating a high risk of malicious activity.
An IP address associated with the domain has been flagged as hosting exploits from CISA KEV vulnerabilities, posing a critical threat to data security and integrity.

Resource Allocation Projection

Purpose: The Resource Allocation Projection Scanner is designed to analyze and evaluate target prioritization modeling, effort distribution simulation, and focus area forecasting within an organization. It aims to identify potential misallocations of security resources, inefficient threat response strategies, and areas of vulnerability that might be overlooked due to improper focus.

What It Detects:

Target Prioritization Modeling: Identifies patterns indicating specific targets or sectors are prioritized without comprehensive risk assessment, with a tendency to overemphasize high-profile targets at the expense of broader security coverage and prioritizing easy-to-exploit vulnerabilities over critical but harder-to-address issues.
Effort Distribution Simulation: Analyzes resource allocation patterns to identify uneven distribution across different departments or threat vectors, disproportionate spending on specific technologies or solutions without corresponding threat justification, and gaps in resource allocation for emerging threats or less visible attack surfaces.
Focus Area Forecasting: Forecasts potential areas of focus based on current threat intelligence and historical data, detecting misalignments between forecasted threats and actual security investments and overconfidence in specific defense mechanisms that may not cover evolving attack strategies.
Threat Intelligence Integration: Evaluates the integration of external threat intelligence feeds into resource allocation models, identifying gaps or delays in incorporating real-time threat data into decision-making processes and reliance on outdated or incomplete threat information for strategic planning.
Vulnerability Modeling and Simulation: Simulates potential attack scenarios based on identified vulnerabilities to assess resource allocation effectiveness, detecting underinvestment in addressing critical vulnerabilities that pose significant risk and overemphasis on low-risk vulnerabilities while high-severity issues remain unaddressed.

Inputs Required:

domain (string): The primary domain to analyze, providing a context for the scanner to evaluate security resource allocations against potential threats and vulnerabilities related to this domain.

Business Impact: This scanner is crucial as it helps organizations refine their security strategies by identifying areas where resources are misallocated or inefficiently utilized. Correcting these inefficiencies can significantly enhance an organization’s overall security posture, protecting against both known and emerging cyber threats more effectively.

Risk Levels:

Critical: Conditions that could lead to severe consequences such as significant data breaches, system failures, or compliance violations.
High: Conditions that pose a high risk of significant impact on operations or security if not addressed promptly.
Medium: Conditions that may affect performance but do not necessarily compromise critical systems immediately.
Low: Informal findings that might indicate minor issues requiring attention but generally do not significantly impact the overall security posture.
Info: Informational findings that provide insights into potential areas for improvement without immediate operational risks.

If specific risk levels are not detailed in the README, these inferred categories can help categorize the severity of detected issues.

Example Findings: The scanner might flag prioritizing a single high-profile client over other significant but less visible clients, neglecting to allocate resources for addressing critical vulnerabilities that could be exploited by advanced threats.

Attack Chain Forecasting

Purpose: The Attack Chain Forecasting Scanner is designed to detect Tactics, Techniques, and Procedures (TTP) sequencing prediction, target selection modeling, and attack progression simulation. It aims to anticipate potential cyber threats by analyzing domain-specific threat intelligence data.

What It Detects:

Identifies CVE numbers indicating known vulnerabilities.
Detects keywords related to malware, ransomware, trojans, and other malicious software.
Recognizes command and control (C2) references that may indicate ongoing cyber attacks or potential breaches.
Flags phishing and credential harvesting attempts which are crucial for protecting sensitive information.
Looks for terms indicating data exposure, leaks, or breaches such as unauthorized access mentions and data dump references.
Utilizes Shodan API to find exposed services and vulnerabilities in the network infrastructure.
Checks VirusTotal API for domain/IP reputation to assess potential risks associated with compromised systems.
Cross-references CISA KEV for known exploited vulnerabilities, providing critical insights into actively exploited threats.
Validates IP reputation using AbuseIPDB to identify risky or malicious IPs that may be involved in cyber attacks.
Looks up vulnerabilities in the NVD/CVE database to provide a comprehensive view of potential security risks.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com). This is essential for identifying and monitoring specific targets that may be vulnerable or under attack.

Business Impact: This scanner plays a critical role in enhancing the cybersecurity posture of organizations by proactively detecting potential threats before they can cause significant damage. It helps in understanding the sequence of attacks, predicting target selection, and assessing exposure levels, which is crucial for developing effective defense strategies and mitigating risks associated with cyber threats.

Risk Levels:

Critical: Conditions that directly lead to severe data breaches or critical system failures are considered critical. This includes high reputation scores indicating low risk but not zero risk, as well as abuse confidence scores above a certain threshold.
High: High-risk conditions include low reputation scores and high abuse confidence scores, which suggest significant exposure to cyber threats.
Medium: Conditions that indicate moderate risk involve average reputation scores and moderate abuse confidence scores. These are still areas of concern but less severe than critical or high risks.
Low: Low-risk conditions pertain to domains with high reputations and low abuse confidence scores, indicating minimal exposure to cyber threats.
Info: Informational findings include general risk indicators that do not necessarily pose an immediate threat but should be monitored for trends or changes in the security landscape.

Example Findings:

The scanner identifies a CVE number related to a recently patched vulnerability, which is crucial for IT teams to promptly apply updates and patches to avoid exploitation.
It detects unauthorized access mentions on a system that has not been authorized by any user, prompting an immediate review of the organization’s access controls.

This structured documentation provides a clear understanding of how the Attack Chain Forecasting Scanner operates and what it can detect, helping users make informed decisions about their cybersecurity measures.

Actor Adaptation Modeling

Purpose: The Actor Adaptation Modeling Scanner is designed to detect how adversaries might adapt their tactics in response to current defenses by analyzing threat intelligence feeds. It aims to predict defense response, technique substitution forecasting, tool replacement simulation, and vulnerability exploitation indicators based on patterns identified from various sources.

What This Scanner Detects:

Defense Response Prediction: Identify patterns indicating that the adversary is aware of and adapting to specific defensive measures. Examples include bypassing firewalls or evading intrusion detection systems.
Technique Substitution Forecasting: Detect signs that the adversary is switching from one attack technique to another in response to detected defenses, such as shifting from phishing to spear phishing attacks.
Tool Replacement Simulation: Recognize indicators that the adversary is replacing one tool with another to maintain or enhance their operational capabilities, including using more stealthy malware variants or updating command and control tools.
Vulnerability Exploitation Indicators: Identify mentions of known vulnerabilities that are being exploited or are likely to be targeted, such as specific CVE numbers associated with the domain under analysis.
Threat Intelligence Correlation: Analyze data from multiple threat intelligence sources to correlate and predict potential adversary actions, including exposure in Shodan databases and listings in CISA’s Known Exploited Vulnerabilities (KEV) catalog.

Inputs Required:

domain (string): Primary domain to analyze (e.g., acme.com). This is the essential input that specifies the scope of the analysis, allowing the scanner to focus on specific entities for detection and prediction.

Business Impact: This scanner is crucial for organizations aiming to anticipate and defend against potential cyber threats by understanding how adversaries might adapt their tactics in response to current defensive measures. It helps security teams stay proactive in mitigating risks associated with known vulnerabilities and emerging threat patterns, thereby enhancing overall cybersecurity posture.

Risk Levels:

Critical: Conditions that directly indicate active exploitation of a vulnerability or significant exposure that could lead to immediate negative impacts on the organization’s security and operations.
High: Conditions where there is evidence of an adversary actively probing for vulnerabilities or attempting to exploit them, posing a high risk if not addressed promptly.
Medium: Conditions indicating potential risks related to specific threats but not yet confirmed as actively exploited or significantly impacting systems.
Low: Informative findings that do not necessarily indicate active threat activity but can provide valuable insights into the adversary’s interests and tactics.
Info: Non-critical findings that may suggest areas for improvement in security measures but are unlikely to pose immediate risks.

If specific risk levels are not detailed in the README, these are inferred based on typical severity indicators of cybersecurity threats.

Example Findings:

A pattern indicating that an adversary has bypassed a firewall and is now evading intrusion detection systems, suggesting a high level of adaptability and threat awareness.
Evidence of exploitation of known vulnerabilities in the organization’s software, which could lead to unauthorized access if not addressed.