Blueinfy strongly believes in developing and evolving solid technologies and methodologies in the application security space to provide excellent services to clients. To serve this commitment, blueinfy runs a dedicated research lab and builds technologies, tools, and approaches, that can help in delivering services efficiently. Over the years we have built key technologies, which we leverage in our services.
Blueinfy has designed and developed a platform to facilitate the process of collaborative penetration testing, knowledge sharing, quality review, automatic report generation & management reporting. The features of this platform enable us to manage, track, monitor and gather statistics about security of applications and organizations in an excellent manner which maps with the customer centric commitment that we believe in.
This serves as a proxy during testing, analyzing request and response data to enhance manual testing by generating a detailed mind map or threat model. It helps in fingerprinting key components in the stack, information disclosure, probable important parameters and valuable information etc., allowing testers to efficiently identify security risks. By leveraging large language models (LLMs), the product provides intelligent insights for comprehensive security assessments.
This tool is designed to enhance penetration testing for AI/ML implementations, addressing the unique challenges introduced by these technologies. As AI/ML systems become more prevalent, traditional testing methods must evolve to include test cases focused on prompting vulnerabilities such as jailbreaking, prompt injection, and traditional attacks like SQL injection, RCE, and data exfiltration via prompts. Additionally, factors like fairness, ethics, and accountability must be considered, as they directly impact brand integrity. The tool aids in generating prompts based on key factors like biases, abuse, ethical concerns, and threats, as well as using bypass techniques such as enactments, separators, and spelling issues. Custom logic can also be incorporated to align testing with the specific implementation and use case, making it a powerful solution to aid AI/ML testing.
The source code scanner is specially designed for analyzing and tracing code in order to identify potential coding errors and security vulnerabilities. The scanner allows to write custom rules based on the requirements, coding language and list of vulnerabilities to be reported and in turn outlines when those rules are met so as to aid quicker manual code reviews.
Our company’s custom-built reporting solution is designed to address the unique needs of various review types, where each assessment demands specific formats and tailored content. Recognizing that clients often require their own reporting standards, this tool offers the flexibility needed for seamless report generation. The solution integrates smoothly with vulnerability tracking platforms, significantly enhancing the efficiency of monitoring and remediation efforts. Built on an XML framework, the tool ensures consistent, high-quality reporting, while allowing full customization to meet client and platform-specific requirements.
The Mobile App Binary Scanner is a specialized tool designed to detect threats and vulnerabilities across mobile platforms by scanning binaries and installers, including APKs and iOS applications. It identifies security risks such as data leaks, policy violations, and improper permission settings in manifest and other relevant files before release. The tool's automation accelerates vulnerability detection, providing faster and more accurate assessments while streamlining mobile app security reviews across all platforms.
This tool is designed to enhance our DAST scanning service, enabling continuous 24/7 scans through a customizable scheduling system. It allows app scans to be configured to run at specified frequencies, such as monthly or quarterly, ensuring consistent security assessments. The tool maintains context for each scan, including identified vulnerabilities, authentication mechanisms, and previous results. If vulnerabilities are marked as false positives after manual review, the tool retains this history, saving time and effort by eliminating the need for repeated verification. This tailored solution streamlines the DAST scanning process and enhances overall efficiency.
These custom Python scripts, developed to support Blueinfy's asset profiling and data classification service, automate critical tasks such as domain enumeration, response data extraction, and API invocation to detect third-party components and their vulnerabilities. The scripts also conduct SSL checks, identify certificate issues, and detect potential sub-domain takeovers. Vulnerabilities discovered through passive analysis are logged efficiently, and the output can be integrated with platforms like JIRA for seamless tracking and management. By running in recursive cycles, these scripts enable continuous monitoring, tracking, and resolution of issues, streamlining the asset profiling process.