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Qualysec did a great job identifying vulnerabilities in our web and cloud applications and gave us clear steps to fix them. They stuck to deadlines, handled re-tests, and supported well.
Kenny Kim
Product Manager
AI Red Teaming Services
Secure your AI models and applications with Qualysec’s AI red teaming. We uncover vulnerabilities, simulate adversarial threats, and help ensure security, compliance, and reliability.
Talk to an Expert
Fortune 100 to startup we secure them all
DEFINITION
What is AI Red Teaming?
Secure your AI systems today! Choose Qualysec to uncover AI vulnerabilities before attackers exploit them.
AI red teaming is a structured adversarial testing process in which security experts simulate attacks against AI systems, LLMs, and ML apps to identify weaknesses before unethical hackers can exploit them. Originally adapted from military and cybersecurity practices, AI red teaming goes beyond traditional penetration testing by addressing threats that are unique to AI, such as prompt injection, adversarial inputs, model inversion, and training data poisoning. Red teaming has become a foundational requirement for organizations seeking to build safe, reliable, and trustworthy AI systems.
WHAT MAKES US DIFFERENT
What Makes Qualysec's AI Red Teaming Different
Every AI Red Teaming engagement includes exclusive security deliverables that provide deep visibility into architectural and AI ecosystem risks.
AI Threat Modeling Report
We map your AI system's attack surface and uncover potential threats across the architecture.
- Attack path mapping & risk identification
- Trust boundary & data flow analysis
- Prompt injection & misuse risk assessment
- Architecture-level security insights
AI-BOM Report
We inventory and analyze all critical components in your AI ecosystem.
- Complete visibility of AI assets & components
- Model, dataset & framework identification
- Dependency & integration mapping
- Third-party & vendor risk identification
Vulnerabilities
Common AI Security Vulnerabilities
Testing AI models, agents, and LLM applications to uncover vulnerabilities before attackers do.
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Prompt Injection
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Jailbreaking
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Data Leakage
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Data Poisoning
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AI Hallucinations
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AI agentic vulnerabilities
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Supply chain Attack
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RAG Testing
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Bias and Toxicity
Process
Our AI Red Teaming Process
At Qualysec, we tailor every AI red teaming engagement to match your threat model, organizational maturity, and the level of access available to our team. Each approach uncovers a distinct layer of risk in your AI systems.
Define Scope
Information Gathering
Enumeration
Attack and Penetration
Reporting
Remediation Testing
Define Scope
We define the scope based on your AI models, data flows, integrations, and real usage scenarios to ensure complete coverage of critical components.
"Don't compromise between depth and speed. Own both. Connect with Swagat, Your trusted penetration testing advisor."
Swagat Kumar Dash
Head Of Business Development
Testimonials
What Our Clients Say About Us
Read what our clients say about our services. See how Qualysec has helped several businesses to keep their digital assets safe!
Key Benefits
Benefits of Conducting AI Red Teaming
Proactively stress-testing your AI systems through expert-led red teaming gives your organization the intelligence it needs to stay ahead of adversarial threats, meet compliance requirements, and build AI products your users can trust.
Uncover Hidden AI Vulnerabilities
Identify exploitable weaknesses that automated scanners and conventional security tools routinely miss in AI systems.
Prevent Costly AI Security Breaches
Detecting and remediating adversarial vulnerabilities before deployment is exponentially less expensive than responding to a breach, data leak, etc.
Accelerate Regulatory Compliance
Demonstrate alignment with EU AI Act, NIST AI RMF, and OWASP LLM Top 10 requirements that satisfy auditors and regulators.
Validate AI Safety Controls & Guardrails
Confirm that your model's safety filters, content policies, and refusal mechanisms perform as intended under real-world adversarial pressure.
Build Stakeholder & Customer Trust
A verified AI red teaming report signals that your AI systems have been independently stress-tested and meet the highest security standards.
Strengthen Your Overall AI Security Posture
Red teaming findings feed directly into your AI risk management program.
Other Types
Different Types of AI Red Teaming Engagements
At Qualysec, we tailor every AI red teaming engagement to match your threat model, organizational maturity, and the level of access available to our team. Each approach uncovers a distinct layer of risk in your AI systems.
Black Box AI Red Teaming
Our team simulates an external adversary with no prior knowledge of your AI system – no model details, no system prompts, no architecture access. This approach tests how your AI application holds up against real-world attackers who interact with it exactly as end users or threat actors would.
White Box AI Red Teaming
With full access to your model architecture, system prompts, training pipeline, and integration details, our red team performs the most thorough adversarial assessment possible. This helps uncover deep logic flaws, alignment weaknesses, and vulnerabilities invisible to external testing alone.
Gray Box AI Red Teaming
Combining both approaches, our team operates with limited internal context, such as knowledge of the model type or general system behavior, while simulating a semi-informed adversary. This balanced method delivers comprehensive AI security insights.
Free Downloads
Download Our Free AI Red Teaming Resources and Reports
Access practical resources from Qualysec to understand how AI Chatbot Security testing works and what to expect during a real assessment.
AI Security Testing Report
A detailed sample report from a real AI red teaming engagement covers adversarial vulnerability findings, severity ratings, proof-of-concept attack scenarios, and actionable remediation recommendations.
AI Security Testing Methodology
A step-by-step breakdown of Qualysec's AI red teaming methodology covers threat modeling, adversarial attack simulation, safety and alignment evaluation, and risk analysis. Understand exactly how we stress-test AI systems against different threats.
AI Security Testing Checklist
A comprehensive AI red teaming checklist aligned with OWASP Top 10 for LLMs, NIST AI RMF, and EU AI Act requirements. Use it to assess your AI system's readiness before a formal engagement, track remediation progress, or validate your internal AI security controls.
Process To Start Assessment
How to Begin Securing Your App with Qualysec
Key steps to start protecting your web application from cyber threats.
1
Contact us↗
Reach out to us and our friendly team will listen to your concerns and understand your unique security needs. Whether you prefer a call, email, or chat, we're ready to start your journey towards a more secure web app.
2
Pre-Assessment Form↗
We send you a simple pre-assessment form to fill up with the appropriate information. This helps us understand your app's architecture, current security measures, and specific concerns.
3
Proposal Meeting↗
After we review our findings from the pre-assessment and outline our proposed approach, we discuss security strategy and answer any questions you may have through either online or face-to-face meetings.
4
NDA and Agreement Signing↗
We get a clear Non-Disclosure Agreement signed by you to protect your sensitive information. We finalize our service agreement after you are completely satisfied. This helps us both know exactly what to expect from our partnership.
5
Pre-requisite Collection↗
We provide our clients with a checklist of everything we need to begin testing, such as access credentials and documentation. Our team assists and ensures a smooth start to your app's security enhancement journey.
Get a Quote
Protect Your AI API from Emerging Threats
Request a tailored quote from Qualysec and understand how advanced security testing can help protect your APIs from unauthorized access and evolving attack techniques.
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FAQ
Frequently Asked Questions
Request a tailored quote from Qualysec and understand how advanced security testing can help protect your APIs from unauthorized access and evolving attack techniques.
AI red teaming is a structured process where security experts simulate adversarial attacks, such as prompt injection, jailbreaking, and model evasion against AI systems to identify vulnerabilities before hackers can exploit them. It is important because AI models introduce entirely new attack surfaces that traditional penetration testing tools are not designed to detect, making dedicated AI red teaming essential for any organization deploying LLMs or machine learning applications.
Traditional penetration testing focuses on network, application, and infrastructure vulnerabilities. AI red teaming specifically targets risks unique to AI systems, including adversarial inputs, training data poisoning, harmful output generation, model inversion attacks, and misaligned model behavior that conventional pentest methodologies do not cover.
Qualysec's AI red teaming services cover a wide range of systems including LLMs, generative AI applications, RAG-based systems, AI chatbots, agentic AI workflows, machine learning APIs, and custom-trained models, across industries such as fintech, healthcare, legal, SaaS, and enterprise software.
Our AI red teaming engagements test for vulnerabilities listed in the OWASP Top 10 for LLMs and beyond, including prompt injection, insecure output handling, training data poisoning, model denial of service, sensitive information disclosure, insecure plugin design, jailbreaking, membership inference attacks, and indirect prompt injection through external data sources.
Yes, increasingly so. The EU AI Act mandates risk assessments for high-risk AI systems, NIST AI RMF recommends adversarial testing as part of AI risk management, and sector-specific regulators in finance and healthcare are beginning to require AI security evaluations. Qualysec's reports are structured to support these compliance requirements.
Engagement timelines vary based on the complexity of your AI system, the number of models and endpoints in scope, and the depth of testing required. A standard AI red teaming assessment typically takes 1–3 weeks, while more complex agentic or multi-model environments may require 4–6 weeks. Qualysec provides a clear timeline during the scoping phase.
No, Qualysec conducts all AI red teaming engagements in a controlled, agreed-upon manner, typically against staging or sandboxed environments to make sure there is zero disruption to your live AI applications or end users. Any testing against production systems is done with explicit sign-off and careful coordination.
You receive a comprehensive AI red teaming report that includes an executive summary, detailed vulnerability findings with severity ratings, proof-of-concept demonstrations, root cause analysis, prioritized remediation recommendations mapped to OWASP LLM Top 10 and applicable frameworks, and a letter of attestation for use with clients, auditors, and regulators.