Fortify Your AI Systems with Advanced Penetration Testing Strategies

Uncover AI and LLM Vulnerabilities With Expert-led AI Penetration Testing

Our AI security specialists deploy cutting-edge testing techniques, including adversarial attack simulations, bias detection, and data leakage assessments, to safeguard AI-driven applications from cyber threats and compliance risks.

AI Security Risks Are Growing—and Traditional Testing Isn’t Enough

AI-powered applications introduce new security challenges that traditional penetration testing tools fail to detect. Adversarial attacks, data leaks, and bias exploitation can threaten your AI system’s reliability, compliance, and trustworthiness without a proactive approach.

AI Red Teaming in Action: What We Offer

AI-powered Vulnerability Scanning

Leverages advanced AI-driven tools to identify and assess security vulnerabilities in AI/LLM models, ensuring a thorough evaluation of potential risks. Provides rapid and accurate threat detection, reducing security blind spots often missed by traditional testing.

Adversarial Attack Simulations

Conducts real-world attack simulations to test AI model resilience against adversarial inputs, including prompt injection, data poisoning, and model manipulation techniques. Strengthens AI defenses by identifying and mitigating attack vectors before exploiting them.

Bias and Ethical Risk Detection

Evaluates AI/LLM responses for biased decision-making and unintended ethical risks, ensuring compliance with industry standards and fairness guidelines. Helps organizations build trustworthy AI models that align with ethical AI principles and regulatory expectations.

AI-driven Social Engineering Attack Simulations

Simulates phishing attacks, adversarial conversations, and other AI-targeted social engineering threats to assess system resilience. It enhances security awareness and mitigates risks related to AI-generated misinformation and unauthorized data access.

Supply Chain Vulnerabilities Detection

Identifies security risks within the AI supply chain, including third-party dependencies and data integrity issues. Assesses vulnerabilities in pre-trained models, open-source libraries, and software components. Enhances AI security by detecting and mitigating risks in the supply chain, preventing potential backdoors, data tampering, and compromised dependencies.

AI Data Leakage and Privacy Assessment

Identifies and prevents unauthorized data exposure by assessing how AI models process and store sensitive information. Protects customer data integrity and ensures compliance with privacy regulations like GDPR and HIPAA.

Our Cutting-edge Approach to AI/LLM Security Testing

  • Our custom-built scripts identify security flaws in LLMs that other tools often overlook, ensuring comprehensive risk assessment beyond standard security testing techniques.
  • We deploy autonomous, AI-powered attack simulations that adapt dynamically, uncovering adversarial exploits at a scale and depth unattainable by manual testing alone.
  • Our security testing framework understands the nuances of AI-generated responses, crafting sophisticated adversarial prompts that exploit hidden biases, ethical loopholes, and unintended outputs.
  • Our approach uncovers hidden jailbreak techniques that bypass traditional security measures, ensuring LLMs remain resilient against unauthorized prompt manipulation and exploitation.
  • We analyze LLM API interactions to detect vulnerabilities, ensuring secure and controlled model deployments.

Why it Matters

Critical systems are under attack—is yours secure?

Cybercriminals exploit vulnerabilities through adversarial techniques, data poisoning, and system manipulation. Traditional security tools are not designed to detect these evolving threats, exposing organizations.

If left unprotected, enterprise systems can be compromised, leading to misinformation, unauthorized data exposure, and ethical concerns, undermining both security and customer trust.

Advanced Tools and Frameworks for Comprehensive Security Testing

Our AI Red Teaming service leverages industry-leading tools and custom-built frameworks to identify vulnerabilities, simulate adversarial attacks, and ensure compliance. These tools enhance security assessments, automate threat detection, and strengthen system resilience.

Jump To Section

AI Security & Adversarial Testing
Vulnerability Scanning & Penetration Testing
Input Validation & Attack Simulation
Custom & Proprietary Tools

Why Choose QASource for AI Red Teaming?

Expertise in AI and Enterprise Security

Our team specializes in AI security, adversarial testing, and compliance-driven security assessments. With deep industry experience, we help organizations protect their systems from evolving threats, leveraging cutting-edge security expertise tailored to AI, LLMs, and traditional enterprise applications.

Comprehensive Security Testing Beyond Standard Methods

Unlike traditional security testing, our AI Red Teaming approach dynamically adapts to new attack patterns, using real-world adversarial simulations to uncover vulnerabilities missed by conventional tools. This enables organizations to identify and mitigate risks that standard penetration testing fails to detect.

Tailored Security Strategies for Your Industry

We customize security testing based on industry-specific threats, whether in finance, healthcare, retail, or AI-driven applications, ensuring compliance with relevant regulatory standards. Our tailored assessments provide security solutions for your industry's risks and compliance requirements.

Efficiency and Scalability

Our AI-augmented testing speeds up the process and makes it scalable, perfect for large projects and agile environments, so you can stay ahead without slowing down.

Client-centric Approach with Actionable Insights 

Our detailed security reports provide clear, actionable recommendations, ensuring your team has the insights to strengthen defenses and effectively remediate vulnerabilities. These meaningful security insights drive measurable improvements in system resilience.

Proven Success Across Regulated Industries

We have a track record of delivering measurable security improvements in highly regulated industries, helping organizations achieve compliance while fortifying their security posture. This ensures compliance with security regulations while enhancing overall system security.

Frequently Asked Questions

What is AI Red Teaming, and how does it differ from traditional penetration testing?

AI Red Teaming is a specialized security assessment that simulates real-world attacks on AI, LLM, and enterprise systems to uncover vulnerabilities. Unlike traditional penetration testing focusing on static vulnerabilities, AI Red Teaming adapts dynamically to evolving AI-specific risks like adversarial attacks, data leakage, and bias exploitation.

What types of threats does AI Red Teaming help mitigate?

Our AI Red Teaming service identifies and mitigates risks such as adversarial manipulations, prompt injections, model poisoning, bias exploitation, unauthorized data exposure, and compliance gaps that traditional security tools may overlook.

Can this service be customized for my industry’s security needs?

Yes, we tailor our AI Red Teaming assessments to industry-specific security challenges. Whether you're in finance, healthcare, retail, or AI-driven businesses, we align our security strategies with regulatory requirements and emerging threats unique to your sector.

How does AI Red Teaming ensure compliance with regulations like GDPR and HIPAA?

Our security assessments evaluate AI-driven applications for compliance with GDPR, HIPAA, SOC 2, and other regulatory standards. We identify data privacy risks, ensure ethical AI decision-making, and provide remediation strategies to align with legal requirements.

How often should AI Red Teaming assessments be performed?

We recommend conducting AI Red Teaming assessments at least annually or whenever significant updates to your AI/LLM models, security infrastructure, or regulatory requirements exist. Continuous security monitoring is also advised for high-risk applications.

What tools and frameworks do you use for AI Red Teaming?

We utilize a combination of open-source and proprietary tools, including Textattack, Promptmap, Garak, Giskard, BurpSuite, ModelScan, and custom scripts designed to simulate real-world AI security threats and adversarial attacks.

What is the timeline for an AI Red Teaming assessment?

The duration of an assessment depends on the scope and complexity of your AI system. On average, a full AI Red Teaming engagement takes 8 to 10 weeks, covering vulnerability scanning, adversarial attack simulations, compliance validation, and remediation planning.

Does AI Red Teaming disrupt normal business operations?

No, AI Red Teaming assessments are conducted in an isolated environment to ensure that live operations remain unaffected. We work closely with your team to set up a secure testing instance that accurately replicates your production environment.

What deliverables can I expect from an AI Red Teaming engagement?

At the end of the assessment, we provide a comprehensive report detailing identified vulnerabilities, risk impact analysis, attack simulation results, compliance gaps, and actionable remediation recommendations tailored to your specific security needs.

How can I get started with AI Red Teaming?

Getting started is easy. Schedule a consultation with our security experts to discuss your security concerns, define the scope of testing, and tailor an AI Red Teaming strategy that aligns with your organization’s needs.