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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
Simulate real-world scenarios and attacks on your AI to discover prompt injection, jailbreaks, hallucinations, data leakage, insecure tool use, and vulnerabilities of agents before attackers.
Talk to an Expert
Fortune 100 to startup we secure them all
DEFINITION
What is AI Red Teaming?
Protect your AI systems from threats. Collaborate with Qualysec for targeted adversarial simulations and discover structural vulnerabilities.
AI Red Teaming is an adversarial security evaluation where professionals simulate attacks to exploit AI systems, LLMs, RAG applications, and machine learning models. Unlike traditional penetration testing, it targets AI-specific risks like prompt injection, data poisoning, system prompt leakage, and agentic exploits. By mirroring real-world attackers, this process serves as a blueprint for AI security, significantly enhancing overall reliability and defense.
WHAT MAKES US DIFFERENT
What Makes Qualysec's AI Red Teaming Different
Each AI Red Teaming engagement comes with detailed security outputs for visibility into vulnerabilities in AI systems and the risks to the ecosystem.
AI Threat Modeling Report
Explore how Qualysec uncovers adversarial vulnerabilities of your AI systems using our actual reports from our real world AI red teaming engagements. Each report includes:
- Attack path mapping & risk classification
- Attack path analysis with risk prioritization
- Standard/ Framework : STRID, MITRE ATT&CK, OWASP, NIST
- Third-party vendor supply chain risk identification
AI-BOM Report
Detailed audit and assessment of key elements of your AI environment. Each report includes:
- Comprehensive inventory of AI ecosystem components
- Mapping AI dependencies and system integrations
- Third-party supply chain risk assessment
- Verify components, track versions and lifecycles
Vulnerabilities
Common AI Security Vulnerabilities
We evaluate and stress-test your AI models, autonomous agents, and LLM implementations to discover and remediate critical flaws before they can be weaponized.
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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 Poisoning
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Bias and Toxicity
Process
Our AI Red Teaming Process
We customize our adversarial testing approach to your unique AI models, risk profile, and deployment architecture at Qualysec. Our phased approach will systematically expose deep-seated risks in all aspects of your AI environment.
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
Proactive testing of your AI systems with the help of experts via red teaming provides your organization with the intelligence it needs to stay ahead of these new threats, meet compliance and regulatory standards, and build AI products that users can trust.
Uncover Hidden AI Vulnerabilities
Discover advanced logic-based weaknesses and present opportunities to bypass security even automated scanners and conventional security systems are unable to.
Prevent Costly AI Security Breaches
Identify and resolve any malicious vulnerabilities before they are released into production, reducing the risk of unauthorized access to data, manipulation of models, or downtime.
Accelerate Regulatory Compliance
Show adherence to new frameworks and international standards, such as EU AI Act, NIST AI RMF, and the OWASP Top 10 for LLMs.
Validate AI Safety Controls & Guardrails
Ensure that your safety filters, content moderation policies and input/output guardrails are effective and dependable at avoiding toxic generation, hallucinations, or exploit execution in real-world situations.
Build Stakeholder & Customer Trust
When an AI Red Teaming assessment is verified, it indicates that your deployments are assessed by an independent party with the highest level of safety standards, which helps to build confidence with enterprise clients.
Strengthen Your Overall AI Security Posture
Integrate technical red teaming findings directly into your broader risk management framework to establish long-term, adaptive defenses.
Other Types
Different Types of AI Red Teaming Engagements
At Qualysec, we design each assessment based on your threat model and architecture. Depending on your security goals, we have multiple levels of model access.
Black Box AI Red Teaming
Our developers emulate an outside hacker who doesn't know your AI system. We test your public APIs, user interfaces, and model outputs just like a hacker without any inside information would. The method tries to find out what vulnerabilities a potential threat could exploit in a realistic way.
White Box AI Red Teaming
Full access to model architecture, system prompts, training pipelines, training data, and integrations are used in comprehensive audits. This enables deep logic analysis, security parameter verification and precise structural vulnerability mapping.
Gray Box AI Red Teaming
We combine both methodologies by conducting tests with partial system access, such as API documentation and high-level architecture, but not training data. We simulate a semi-insider threat or sophisticated supply chain attacker. This approach tests your defenses against threats with limited but specific knowledge of your systems.
Free Downloads
Download Our Free AI Red Teaming Resources and Reports
: Explore how AI security testing works and what to expect during a security assessment with Qualysec.
AI Red Teaming Report
A sample report from a real AI red team engagement, broken down into detail, shows the way Qualysec records adversarial vulnerabilities, security findings, proof-of-concept exploits and suggestions for mitigation. Discuss real-life results and reporting.
AI Red Teaming Methodology
A detailed explanation of Qualysec's AI red teaming methodology, which includes threat modeling, AI-BOM assessment, attack simulation, safety evaluation, and risk assessment. Try out our testing framework when it comes to threat scenarios.
AI Red Teaming Checklist
A comprehensive AI red teaming checklist aligned with the OWASP LLM Top 10, NIST AI RMF, leading AI compliance requirements, and industry best practices. Use this checklist to assess your AI security posture and validate internal security controls before a formal AI red teaming engagement.
PRICING
Pricing for AI Red Teaming
Our Penetration Testing Service Pricing Could Save You Millions!
Process To Start Assessment
How to Begin Securing Your AI/LLM system with Qualysec
Key steps to start protecting your AI/LLM systems from emerging 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 AI/LLM system/application.
2
Pre-Assessment Form↗
We send you a simple pre-assessment form to fill up with the appropriate information. This helps us understand your AI/LLM system's architecture, current security measures, and specific concerns.
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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 sign an NDA to protect your sensitive information and finalize the service agreement. This ensures clear expectations and a smooth partnership from the start.
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 AI/LLM system/app's security enhancement journey.
Get a Quote
Protect Your AI System from Emerging Threats
Request a tailored quote from Qualysec and understand how advanced security testing can help protect your AI systems from emerging threats and attacks.
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FAQ
Frequently Asked Questions
Get quick answers to common questions about AI Red Teaming, its benefits, frequency, costs, and more.
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.