Penetration Testing

• Web Applications – Simulating real-world attacks to identify vulnerabilities in web applications, including authentication flaws, injection attacks, misconfigurations, and security gaps that could be exploited by attackers.
  
• Mobile Applications – Assessing security weaknesses in iOS and Android applications, focusing on insecure data storage, weak authentication mechanisms, improper API calls, and reverse engineering risks.
  
• API Security – Evaluating the security of APIs by testing authentication, authorization, data exposure, and injection vulnerabilities to prevent unauthorized access and data leaks.
  
• Thick Client Application – Testing security flaws in desktop or enterprise applications that interact with local or remote servers, including insecure storage, network communication weaknesses, and privilege escalation risks.
  
• Source Code Security Audit – Conducting a thorough review of application source code to identify security flaws, insecure coding practices, and potential vulnerabilities before they can be exploited.
  

• Amazon Web Services (AWS) – Evaluating AWS configurations, IAM policies, storage security (S3 buckets), network security groups, and overall cloud security posture to identify misconfigurations, excessive permissions, and potential attack vectors.
  
• Microsoft Azure – Assessing Azure environments for security weaknesses in identity management, storage, virtual machines, and networking components while ensuring compliance with best practices and security frameworks.
  
• Google Cloud Platform (GCP) – Analyzing GCP security configurations, IAM roles, storage settings, network security, and API exposure to identify vulnerabilities and improve cloud security resilience.
  

• External Infrastructure – Assessing publicly exposed assets such as websites, servers, and network devices to identify vulnerabilities that could be exploited by external attackers. This includes scanning for misconfigurations, outdated software, and weak authentication mechanisms.
  
• Internal Infrastructure – Simulating insider threats or compromised devices within the internal network to uncover security gaps, lateral movement risks, and privilege escalation opportunities. This helps organizations strengthen their internal defenses.
  
• Active Directory Security – Evaluating the security of Microsoft Active Directory, identifying misconfigurations, weak authentication mechanisms, and privilege escalation paths that attackers could exploit to gain domain dominance.
  
• WiFi Networks – Testing the security of wireless networks, including encryption strength, rogue access points, authentication mechanisms, and potential risks from unauthorized access or man-in-the-middle attacks.
  
• Kubernetes Infrastructure – Assessing Kubernetes clusters for security weaknesses, misconfigured RBAC (Role-Based Access Control), exposed secrets, container runtime vulnerabilities, and insecure network configurations.
  

• AI Model Vulnerability Testing – Assessing machine learning models for security weaknesses, including adversarial manipulations, data leakage, and improper access controls that could expose sensitive information or compromise decision-making.
  
• Third-party Model Integration Security – Evaluating the security risks associated with integrating third-party AI models, ensuring proper API security, authentication, and protection against data exposure or model tampering.
  
• Adversarial Attack Simulation – Simulating real-world attacks on AI models, such as adversarial perturbations, evasion attacks, and model inversion techniques to identify weaknesses and improve model robustness.
  
• Model Integrity Verification – Ensuring the integrity of AI models by verifying authenticity, detecting unauthorized modifications, and preventing model theft or injection of malicious logic.
  

• Embedded Systems Security – Assessing security risks in embedded devices, including firmware integrity, secure boot mechanisms, hardware interfaces, and potential attack vectors such as buffer overflows and side-channel attacks.
  
• Device Firmware Security – Analyzing firmware for vulnerabilities, backdoors, insecure update mechanisms, and reverse engineering risks to prevent unauthorized modifications or exploitation.
  
• Wireless Communication Security – Testing the security of wireless communication protocols (e.g., Bluetooth, Zigbee, LoRa, RFID, NFC) to identify vulnerabilities such as weak encryption, unauthorized access, and interception risks.
  
• Hardware Penetration Testing – Conducting in-depth analysis of physical hardware security, including chip-level attacks, debugging interfaces (JTAG/SWD), supply chain risks, and tamper resistance testing.
  
• IoT Ecosystem Risk Assessment – Evaluating the security of interconnected IoT devices, cloud integrations, APIs, and data transmission channels to identify risks, misconfigurations, and potential attack surfaces.
  

• Level 1 – Basic security verification, suitable for all applications, covering common vulnerabilities like injection attacks and misconfigurations.
  
• Level 2 – Standard security verification, ideal for applications handling sensitive data, requiring strong authentication, session management, and secure coding practices.
  
• Level 3 – Advanced security verification, designed for critical applications (e.g., banking, healthcare) that demand the highest security standards, including in-depth cryptography and secure architecture reviews.