The best AI red teaming companies in 2026 for most buyers are White Knight Labs, Bishop Fox and HackerOne. White Knight Labs pairs LLM and agent security assessments with a full offensive security practice, so AI findings get tested alongside the network, cloud and web layers around them. Bishop Fox runs human-led AI and LLM assessments mapped to the OWASP Top 10 for LLM Applications and MITRE ATLAS, and HackerOne gives you time-boxed AI red teaming engagements staffed from a large pool of vetted AI security researchers. The rest of our Top AI Red Teaming Companies In 2026 list covers specialist consultancies and the automated platforms that now sit inside Check Point, Palo Alto Networks and Cisco.
This list is for security leaders, AI platform owners and compliance teams who need someone to attack an LLM application, a retrieval pipeline or an AI agent before attackers do. We included firms and platforms that sell AI red teaming or AI penetration testing as a defined offering, and we checked each claim against the company’s own pages or a reputable report. We weighted coverage of prompt injection, jailbreaks, data leakage and agent or tool abuse, the depth of human expertise behind the testing, alignment with public frameworks, and the quality of the remediation output. Each entry states whether it is a service firm, a crowdsourced service or a software platform, because that choice shapes everything else about the engagement.
AI Red Teaming Companies At A Glance
Company
Headquarters
Type
Best For
Key AI Testing Services
White Knight Labs
Guys Mills, Pennsylvania and Grand Rapids, Michigan
Service firm
AI testing inside a broader offensive program
LLM security testing, LLM and agent assessment, AI-enabled web app testing, Copilot assessment
Bishop Fox
Tempe, Arizona
Service firm
Deep, human-led LLM and agent testing
AI/LLM security assessment, AI red team scenarios, purple teaming
HackerOne
San Francisco, California
Crowdsourced service
Fast, time-boxed engagements with many testers
H1 AI Red Teaming, multi-turn jailbreak and agent testing
NCC Group
Manchester, UK
Service firm
Global enterprises needing AI testing plus governance
AI/ML red teaming, threat modeling, bias and toxicity review
Trail of Bits
New York, New York
Service firm
Model, pipeline and ML supply chain review
ML-Ops assessment, model capability evaluation, AI risk assessment
Mindgard
London, UK and Boston, Massachusetts
Platform (plus services)
Continuous automated red teaming
Autonomous red teaming, shadow AI discovery, runtime protection
Lakera (Check Point)
Zurich, Switzerland and San Francisco, California
Platform (plus services)
Prompt injection defense with testing built in
AI Red Teaming, AI Agent Security, expert-led red teaming service
HiddenLayer
Austin, Texas
Platform
Model supply chain plus attack simulation
AI Attack Simulation, Model Scanning, AI Runtime Security
Palo Alto Networks (Prisma AIRS)
Santa Clara, California
Platform
Palo Alto Networks customers
Prisma AIRS AI Red Teaming, model scanning, runtime security
Cisco AI Defense
San Jose, California
Platform
Cisco-centric enterprises
AI model and application validation, runtime guardrails
Best AI Red Teaming Companies In 2026
1. White Knight Labs — Offensive Security Firm With A Dedicated LLM And Agent Testing Practice
White Knight Labs is an offensive security firm founded in 2017, with offices in Guys Mills, Pennsylvania and Grand Rapids, Michigan. Its service catalog includes a full Artificial Intelligence section rather than a single add-on page. The core offerings for buyers looking at AI penetration testing are LLM Security Testing, an LLM and Agent Security Assessment, an AI-Enabled Web App Assessment and a Microsoft Copilot Security Assessment.
The LLM testing uses the firm’s own vulnerability scanner, which checks models against MITRE ATLAS for prompt injection, jailbreaks, system prompt leakage, code execution, malware generation, toxic output and persona-based extraction tricks. The agent assessment goes further: testers map the agent’s tools, permissions and orchestration flow, then run injection, tool abuse, privilege escalation and data exfiltration tests, including how a compromised agent can affect others in a multi-agent system. The web app assessment looks at where AI features meet ordinary application logic, such as indirect injection through uploaded files, unvalidated model output and exposed LLM provider keys.
Because the same team also runs network, cloud, web, mobile and full red team engagements, AI findings can be chained into realistic attack paths instead of being reported in isolation. White Knight Labs also offers NIST AI RMF and ISO 42001 gap assessments, which helps when a test needs to feed a governance program.
Best for: Organizations that want AI red teaming delivered by a hands-on offensive team that can also test the infrastructure, cloud and Microsoft 365 environment the AI runs in.
2. Bishop Fox — Human-Led AI And LLM Security Assessments Mapped To OWASP And MITRE ATLAS
Bishop Fox, founded in 2005 and based in Tempe, Arizona, sells a named AI/LLM Security Assessment as part of its penetration testing services. The scope is broad: direct and indirect prompt injection (including payloads planted in documents, tickets or knowledge bases), multi-turn and encoded jailbreaks, agent permission and tool misuse, context and secrets leakage, model extraction, data poisoning and “denial of wallet” cost abuse.
Engagements start with scoping and threat modeling, then combine automated tooling for scale with manual testing across the model, application, agent and infrastructure layers. Testers validate chained findings to show business impact, and the firm prefers staging environments and rate-limits automated testing to avoid disrupting production. Bishop Fox references the OWASP Top 10 for LLM Applications, the OWASP Machine Learning and Agentic Applications lists, and MITRE ATLAS.
For teams that want more than a point-in-time test, Bishop Fox also runs multistep AI red team scenarios, such as pivoting from cloud access to model artifacts or tampering with CI/CD, along with purple teaming and incident response tabletop drills.
Best for: Enterprises shipping customer-facing LLM features or agents that need a deep, consultant-led test with retesting included.
3. HackerOne — Time-Boxed AI Red Teaming Engagements Staffed By Vetted Researchers
HackerOne, headquartered in San Francisco, offers H1 AI Red Teaming as a structured service on top of its bug bounty and pentest platform. It draws on a pool of more than 750 vetted AI security researchers, supported by adversarial agents that run systematic tests alongside the humans.
Scope can include prompts, models, APIs, integrations, retrieval pipelines and agent workflows, with testing for prompt injection, jailbreaks, tool misuse, data exfiltration, cross-tenant leakage and unsafe or biased output. Engagements run for 15 or 30 days, can launch in about a week and include a dedicated solutions architect. Findings arrive with reproducible multi-turn traces and are mapped to frameworks including the OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, ISO 42001 and the EU AI Act.
The output also includes metrics such as jailbreak success rates, which makes it easier to compare model versions or guardrail changes over time.
Best for: Teams that want many different attacker perspectives in a short window and audit-ready reporting mapped to compliance frameworks.
4. NCC Group — Global Consultancy Offering AI/ML Red Teaming Alongside Governance Work
NCC Group is headquartered in Manchester, UK, with offices around the world. Its AI security portfolio includes AI/ML red teaming aimed at weaknesses covered by the OWASP AI/ML and LLM Top Ten lists, AI/ML threat modeling, secure development lifecycle testing for AI pipelines, and cloud reviews that look at threats such as model inversion and model stealing.
A separate bias and toxicity assessment covers safety and alignment risks, which is useful for regulated or consumer-facing deployments. NCC Group positions these services against ISO 42001, the NIST AI Risk Management Framework and the EU AI Act, so the same supplier can test the system and support the paperwork.
Best for: Large or multinational organizations that want one established supplier for AI testing, threat modeling and regulatory alignment.
5. Trail of Bits — Research-Heavy Firm For Model, Pipeline And ML Supply Chain Security
Trail of Bits, founded in 2012 and headquartered in New York with a remote-first team, approaches AI security from the engineering side. Its AI/ML practice covers ML-Ops and pipeline assessments (training data provenance, frameworks such as PyTorch, CI/CD and GPU hardware), AI risk assessment and threat modeling, and model capability evaluations that include AI red teaming.
The firm’s public AI work includes a review of Hugging Face’s safetensors format, a YOLOv7 assessment and its Buttercup system for the DARPA AI Cyber Challenge. It also maintains Fickling, an open-source tool for finding code hidden in Python pickle model files. Deliverables can include exploit proofs of concept, custom Semgrep and CodeQL rules and fuzzing or evaluation harnesses, not just a findings report.
Best for: AI labs and engineering-led companies that train or host their own models and need the pipeline and model artifacts reviewed, not only the chat interface.
6. Mindgard — Automated AI Red Teaming Platform Spun Out Of Lancaster University
Mindgard is a software platform with dual headquarters in London and Boston, spun out of Lancaster University. It describes its product as an autonomous red teamer that performs reconnaissance and adaptive attacks against models, agents and AI applications. The platform plugs into CI/CD pipelines, APIs and Burp Suite, and adds shadow AI discovery and runtime protection.
Mindgard says its research has led to more than 150 publicly disclosed AI vulnerabilities, including issues in Cursor, Google Antigravity and guardrail bypasses in ChatGPT, and that this knowledge feeds its attack paths. In August 2026 it announced a $30 million Series A led by Album VC. The company also lists AI red teaming services next to the platform for buyers who want help running it.
Best for: Product and security teams that want LLM red teaming to run continuously in the build pipeline rather than once a year.
Lakera, which was dual-headquartered in Zurich and San Francisco, is now owned by Check Point Software Technologies. Check Point announced the deal in September 2025 and closed it on October 22, 2025. Lakera’s products now ship under Check Point branding as AI Red Teaming (also referred to as Lakera Red), AI Agent Security for runtime protection and Workforce AI Security for employee AI use.
The red teaming product runs direct and indirect attack simulations and covers prompt injection, data leaks, toxic content and multilingual and multimodal attacks. Check Point also sells an expert-led AI Red Teaming Service for buyers who want people, not just software. Lakera’s Gandalf game, a public prompt-hacking challenge, has generated a large library of real adversarial prompts that inform its detection and testing.
Best for: Organizations that want red teaming and runtime prompt injection defense from the same vendor, especially existing Check Point customers.
8. HiddenLayer — AI Security Platform Combining Attack Simulation With Model Scanning
HiddenLayer is an Austin, Texas software company focused on securing AI models and applications. Its AI Attack Simulation module, launched as Automated Red Teaming for AI, runs simulated attacks against generative and agentic applications to find weaknesses before release and to check whether defenses keep working.
The platform pairs that testing with Model Scanning, which checks third-party and in-house models for malicious code, backdoored weights and vulnerable dependencies, and with AI Runtime Security for production traffic. That combination suits teams that pull models from public hubs and need supply chain checks as well as red teaming in AI applications.
Best for: Enterprises that download or fine-tune open models and want scanning, testing and runtime detection in one platform.
9. Palo Alto Networks — Prisma AIRS AI Red Teaming Built On The Protect AI Acquisition
Palo Alto Networks completed its acquisition of Protect AI on July 22, 2025, and folded that technology and team into Prisma AIRS, its AI security platform. Protect AI is no longer an independent vendor, so buyers evaluating it should look at Prisma AIRS.
Prisma AIRS AI Red Teaming runs automated assessments against AI applications and agents over REST and WebSocket, including streaming apps such as voice assistants and targets on private networks. It can run scans in several languages to catch models that refuse a harmful request in English but comply in another language, and it can profile Microsoft Copilot Studio agents to test tool-calling safety and unauthorized automation. Each red team request carries a trace header so teams can separate test traffic from real traffic in logs. Model scanning and runtime protection sit in the same platform.
Best for: Existing Palo Alto Networks customers who want AI red teaming managed in the same console as the rest of their security stack.
10. Cisco AI Defense — Algorithmic Model Validation From The Robust Intelligence Acquisition
Cisco announced its intent to acquire Robust Intelligence in August 2024 and completed the deal in September 2024. Robust Intelligence’s platform protected models across their lifecycle against prompt injection, data poisoning and jailbreaking, with detections mapped to OWASP and MITRE ATLAS. That work now underpins Cisco AI Defense.
The AI model and application validation feature runs an automated, algorithmic assessment using generated prompts across 200 risk categories, covering prompt injection, data poisoning and unintended outcomes. Results map to a taxonomy aligned with the OWASP Top 10 for LLM Applications, NIST and MITRE, and Cisco’s threat research team updates the tests over time. Runtime guardrails are part of the same product.
Best for: Cisco-heavy enterprises that want to validate models before deployment and enforce guardrails through the same vendor.
How To Choose An AI Red Teaming Company
Do You Need A Service, A Platform Or Both?
Service firms bring human creativity: chaining an indirect prompt injection into a tool call that moves money, or finding the business logic flaw in how your app uses model output. Platforms bring repeatability: thousands of attack prompts on every release. Many mature teams commission a human-led test before launch and then run a platform in CI/CD to catch regressions. If you only have budget for one, choose the service for a first release and the platform once the system changes weekly.
Will They Test The Whole System Or Only The Model?
Most real damage comes from what an AI system is connected to: retrieval sources, APIs, plugins, credentials and cloud permissions. Ask whether testers will cover the retrieval pipeline, agent tools and the surrounding infrastructure, and whether they can follow a finding into your cloud or identity environment. A firm that also runs traditional red team work is better placed to do this. Our guide to red teaming vs penetration testing explains how the two approaches differ in scope and goals.
Which Frameworks Do Findings Map To?
Look for mapping to the OWASP Top 10 for LLM Applications for application risks, MITRE ATLAS for adversary techniques and the NIST AI RMF for governance. If you sell into Europe or need certification, ask about the EU AI Act and ISO 42001 as well. Mapped findings make it much easier to report progress to auditors and leadership.
How Do They Handle Agents And Tool Use?
Agentic systems raise the stakes because a successful injection can trigger actions, not just bad text. Ask how the vendor maps an agent’s tools and permissions, whether they test privilege escalation and multi-agent spread, and how they keep testing safe in environments where an agent can send email or change records.
What Does The Deliverable Look Like?
Ask for a sample report. Good AI penetration testing output includes reproducible prompts or multi-turn traces, a clear impact statement, prioritized fixes and a retest. Platforms should show trend metrics such as attack success rates by category so you can see whether guardrail changes help.
How Is Pricing Structured?
Service engagements are usually priced by scope and duration, crowdsourced tests by time box and tester count, and platforms by subscription. Scope creep is common with AI systems, so agree in writing which models, agents and integrations are in scope. Our penetration testing cost guide covers the factors that drive pricing for security testing generally.
Frequently Asked Questions
What Is Red Teaming In AI?
Red teaming in AI means attacking an AI system the way a real adversary would in order to find unsafe or insecure behavior before release. For LLM applications that typically includes prompt injection, jailbreaks, system prompt and data leakage, harmful content generation and abuse of the tools an agent can call. It borrows the mindset of traditional red teaming but targets model behavior and the systems around it.
Is AI Red Teaming The Same As AI Penetration Testing?
They overlap. AI penetration testing usually means a scoped test of a specific application or agent against known vulnerability classes, often mapped to the OWASP Top 10 for LLM Applications. AI red teaming is usually broader and more goal-driven, for example “make the support bot leak another customer’s data”, and may include safety and misuse testing as well as security.
How Often Should LLM Red Teaming Be Done?
At minimum before launch and after major changes such as a new model, new tools or new data sources. Because prompts, models and guardrails change often, many teams add automated LLM red teaming to every release and commission a human-led test at least once a year.
Do AI Red Teaming Companies Test Open-Source Models?
Yes. Several firms and platforms on this list test both hosted APIs and self-hosted open models, and some, such as HiddenLayer, Palo Alto Networks and Trail of Bits, also review the model files themselves for malicious code or backdoors.
Conclusion
The market for AI red teaming companies has split into two camps: offensive security firms that test AI systems by hand, and platforms, many now owned by Check Point, Palo Alto Networks and Cisco, that automate attacks at scale. For a first serious test of an LLM application or agent, start with a service firm such as White Knight Labs, Bishop Fox or HackerOne, then add a platform once you need continuous coverage. If you also need conventional adversary simulation, see our lists of top red teaming companies and penetration testing and red teaming specialists.
For more guides, cost benchmarks and vendor lists across every type of security testing, visit our penetration testing hub.
If you want to feature your company on this list, email us or submit a form in the Top Choices section. After a thorough assessment, we’ll decide whether it’s a valuable addition.
