Bounty Intelligence Analysis

5 automated security scanners

Public Vulnerability Correlation

Purpose: The purpose of this scanner is to analyze public vulnerability correlation for a given domain and company. It aims to identify and report on any publicly disclosed vulnerabilities that may affect the detected technologies, such as WordPress, PHP, and Nginx in use by the company.

What It Detects:

This scanner detects various versions of WordPress, PHP, and Nginx running on the target domain.
It identifies JavaScript libraries like jQuery and their versions.
It collects server headers to understand the configuration details.
It matches public CVEs (Common Vulnerabilities and Exposures) that may affect the detected technologies.
It checks for exploits available for these vulnerabilities, including Metasploit modules and ExploitDB entries.
It identifies outdated components below their current patch levels.

Inputs Required:

Domain: The target domain to be analyzed.
Company Name: The name of the company associated with the domain.

Business Impact: This analysis is crucial as it helps in identifying potential security risks and vulnerabilities that could be exploited by malicious actors, thereby impacting the overall security posture of the organization. It enables proactive measures to be taken to mitigate these risks before they can lead to significant damage or data breaches.

Risk Levels:

Critical: This severity is flagged when critical public CVEs are matched with detected technologies. The risk level increases significantly as it indicates a high probability of exploitation and potential severe consequences.
High: High risk levels are assigned when vulnerabilities are identified that could lead to significant data breaches or system compromise, especially if the versions in use are outdated and not patched.
Medium: Medium severity is assigned for vulnerabilities that pose moderate risks but still need attention to avoid escalation to higher severities.
Low: Low risk levels are assigned for informational findings or when technologies are up-to-date with no known vulnerabilities.
Info: This severity is used for purely informative purposes, such as identifying the version of a technology without any critical issues.

Example Findings:

A WordPress installation running on version 5.8.1 was detected, which includes a publicly disclosed vulnerability (CVE-2023-XXXX) that could allow unauthenticated attackers to bypass authentication and gain full administrative access.
The PHP version in use (7.2.34) has been identified as having multiple CVEs affecting its functionality, posing significant risks if not patched promptly.

By providing this detailed analysis, the scanner helps in understanding the current security state of the organization’s IT infrastructure and highlights areas that require immediate attention to enhance overall security measures.

Cross-Program Vulnerability Patterns

Purpose: The purpose of this scanner is to analyze cross-program vulnerability patterns for a given domain and company. It aims to identify potential vulnerabilities across multiple programs that may share common attack vectors, thus indicating a higher exposure risk.

What It Detects:

Cross-program vulnerability classes such as SQL injection, XSS, SSRF, authentication bypass, IDOR, RCE, subdomain takeover, CSRF, XML external entity (XXE), and deserialization are detected.
High-frequency vulnerability classes that indicate a higher exposure risk are identified.
Industry patterns suggesting elevated exposure risk in multiple vulnerability categories are analyzed.
The technology stack used by the company is extracted to understand potential attack surfaces better.
Cross-program vulnerabilities specific to similar targets are detected, indicating active researcher attention.
Peer organizations’ vulnerability summary provides insights into industry standards and potential competitors’ security practices.

Inputs Required:

Domain: The target domain for which the vulnerability analysis is conducted.
Company Name: The name of the company associated with the domain.

Business Impact: This scanner helps in identifying potential vulnerabilities that could be exploited across multiple programs, leading to a more comprehensive security posture and better risk management. It allows organizations to focus their resources on high-risk areas and implement preventive measures accordingly.

Risk Levels:

Critical: When the number of critical vulnerability classes exceeds 5 or when there is evidence of active exploitation attempts in public reports.
High: When multiple high-frequency vulnerability classes are detected, indicating a significant exposure risk without being critical.
Medium: When moderate vulnerability pattern correlation is identified and potential cross-program threats are present.
Low: When no significant cross-program vulnerability patterns are detected and the overall risk level is considered low based on findings.
Info: For informational findings that do not directly impact security but provide insights into researcher attention to similar targets.

Example Findings:

Multiple high-frequency vulnerability classes (e.g., XSS, IDOR) indicate a higher exposure risk across multiple programs.
Industry patterns suggest potential competitors have been successful in mitigating certain risks, prompting deeper analysis and proactive measures.

Researcher Targeting Decisions

Purpose: The purpose of this scanner is to analyze and assess the effectiveness of researcher targeting for bug bounty programs. It aims to determine whether a company’s domain has been effectively identified by researchers, highlighting potential issues such as avoidance behavior or lack of engagement from skilled researchers.

What It Detects:

Researcher Targeting Decisions: The scanner identifies disclosed reports and analyzes the involvement of unique researchers in targeting the company’s assets.
Severity Distribution: It categorizes vulnerabilities based on their severity, providing a clear view of potential risks.
Vulnerability Distribution: By breaking down the types of vulnerabilities found, it helps to prioritize mitigation efforts.
Average Bounty: The average monetary reward offered for reported issues provides insight into the typical exposure and risk associated with the identified vulnerabilities.
Researcher Specializations: It identifies which researchers specialize in targeting specific types of vulnerabilities, indicating areas of expertise or potential weaknesses.
Detected Tech Stack: By analyzing the technology stack used by the company, it assesses whether outdated technologies might deter modern security researchers.
Tech Appeal Score: This score reflects the attractiveness of the target from a technical perspective, influencing researcher engagement.
Researcher Quality Indicators: It evaluates the quality and effectiveness of targeting based on average bounty amounts and overall engagement indicators.
Targeting Mentions: The scanner detects any negative or positive mentions about the company’s bug bounty program, providing qualitative feedback on researcher perceptions.
Vulnerability Identification: It determines whether the identified vulnerabilities are indicative of a vulnerable system that could be exploited by malicious actors.

Inputs Required:

<domain>: The target domain for analysis.
<company_name>: The name or identifier of the company associated with the domain.

Business Impact: This scanner is crucial as it helps security teams and bug bounty programs understand which domains are actively being targeted by skilled researchers and which ones might be avoided due to technical, legal, or other reasons. This information is vital for enhancing engagement strategies and improving overall security posture against potential threats.

Risk Levels:

Critical: The system is severely compromised, with critical vulnerabilities that could lead to significant data loss or system unavailability.
High: High-risk vulnerabilities are present, potentially leading to substantial damage or exposure of sensitive information.
Medium: Vulnerabilities exist that could be exploited with moderate effort, resulting in considerable risk if not mitigated promptly.
Low: Vulnerabilities pose minimal risk and can generally be addressed at a lower priority compared to higher risks.
Info: Informational findings that do not directly impact security but may indicate areas for improvement or further investigation.

Example Findings:

A company might find that its bug bounty program is being avoided due to technical complexities, leading to low engagement and minimal reported issues.
Another scenario could involve the discovery of multiple high-severity vulnerabilities, indicating a critical risk that needs immediate attention.

Researcher Forum Sentiment

Purpose: The purpose of this scanner is to analyze sentiment on researcher forums such as Reddit, Twitter, and GitHub regarding a specific company’s bug bounty program. It aims to provide insights into how researchers perceive the program and identify potential issues that could affect the company’s reputation or participation in vulnerability disclosure programs.

What It Detects:

Sentiment Analysis: The scanner detects sentiment expressed by researchers on various forums regarding the company’s bug bounty program, categorizing it as positive, neutral, or negative.
Common Complaints: It identifies common themes among negative feedback, such as issues with payouts, response times, and scope of submissions.
Reputation Damage: The scanner assesses the percentage of negative sentiment to gauge potential damage to the company’s reputation and draws conclusions about the risk level based on this metric.

Inputs Required:

Domain: The target domain for which the bug bounty program is active, used to identify relevant forums and discussions.
Company Name: The name of the company whose bug bounty program is being evaluated, helping in focusing discussion points on that specific entity.

Business Impact: This analysis is crucial as it directly influences how potential security researchers perceive a company’s commitment to cybersecurity and fair handling of vulnerabilities. Negative sentiment can lead to decreased participation in bug bounties, reduced vulnerability disclosure, and potentially harm the company’s standing in the cybersecurity community.

Risk Levels:

Critical: If more than 70% of mentions are negative across multiple platforms with at least 10 total mentions, indicating severe reputation damage that could lead to avoidance by security researchers.
High: Between 50% and 70% negative sentiment with around or above the average number of mentions (around 8), highlighting significant concerns about program fairness and responsiveness.
Medium: From 30% to 50% negativity, indicating some issues that might affect researcher confidence but are not yet critical.
Low: Below 30% negative sentiment with fewer than 6 mentions suggests a generally positive perception or minimal impact on the bug bounty program’s effectiveness.
Info: If no negative feedback is detected and overall sentiment remains neutral, it indicates an informational finding about favorable perceptions that might not warrant immediate action but could be monitored for changes.

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

Example Findings:

“Acme Corporation consistently receives negative feedback regarding payouts and response times across multiple platforms.” This indicates a high risk level due to widespread dissatisfaction with key aspects of the bug bounty program.
“No significant negative sentiment detected in discussions about Acme’s program, suggesting generally positive perceptions among researchers.” This is an informational finding indicating minimal impact on the program’s reputation.

Competitive Program Benchmarking

Purpose: The purpose of this scanner is to analyze and benchmark bug bounty programs against industry standards for a given domain and company. It aims to determine the competitive positioning, potential vulnerabilities, and risk levels associated with the absence or inadequacy of a bug bounty program.

What It Detects:

The presence or absence of a bug bounty program across multiple platforms (e.g., HackerOne, Bugcrowd).
The structure and range of rewards for different severity levels of vulnerabilities.
The size and scope of the vulnerability discovery space.
The responsiveness and efficiency in handling reported issues.
Comparisons against industry benchmarks to identify competitive gaps or advantages.
Assessments of the overall risk level associated with the bug bounty program based on its performance relative to peers.

Inputs Required:

Domain: The target domain for which the bug bounty program is assessed (e.g., “example.com”).
Company Name: The name or identifier of the company that operates the bug bounty program (e.g., “Example Corp”).

Business Impact: The absence of a robust bug bounty program can significantly impact an organization’s security posture by reducing the proactive discovery and reporting of vulnerabilities. This can lead to prolonged exposure of critical systems, potential data breaches, and legal liabilities. Effective bug bounty programs are crucial for maintaining a resilient cybersecurity strategy that proactively identifies and mitigates risks.

Risk Levels:

Critical: The program is severely lacking or non-existent, leading to significant vulnerabilities remaining undiscovered and potentially exposing the organization to high risk.
High: The rewards structure does not align with industry standards, limiting the effectiveness of attracting skilled researchers and increasing the likelihood of critical issues going unaddressed.
Medium: The program has limitations in scope or response time that place it below average industry benchmarks, indicating a moderate level of vulnerability but still posing significant risk.
Low: The program competes with industry standards without major gaps, demonstrating an effective balance between rewards and scope, with minimal exposure to high risks.
Info: Informal findings such as minor discrepancies in reward structure or minor competitive gaps that do not significantly impact the overall risk profile but are still indicative of room for improvement.

Example Findings:

The company’s bug bounty program is non-existent, leading to numerous undiscovered vulnerabilities and a high risk level due to potential exposure of sensitive information.
While the rewards structure includes provisions for critical issues, they significantly undercompensate compared to industry standards, indicating a vulnerability that could be exploited without adequate deterrents.