Attack your AI before someone else does.
AI red teaming is the process of running systematic adversarial attacks against your LLMs, chatbots, and AI agents to find security vulnerabilities — prompt injection, jailbreaks, data exfiltration, and agent abuse — before real attackers do. It produces a graded findings report and a prioritized fix list.
SecuritAI runs extensive adversarial testing against your LLMs, chatbots, and AI agents — uncovering prompt injection, jailbreaks, data exfiltration, and system-prompt abuse — then hands your team a prioritized list of fixes.
Built for AI — not generic scans rebranded.
Generic scanners check infrastructure, not whether your chatbot can be talked into leaking data or ignoring its rules. SecuritAI probes your AI the way a real attacker would, covering every category in the OWASP Top 10 for LLM Applications.
What we test for
Prompt injection
Direct and indirect instruction hijacking.
Jailbreaks
Bypassing safety and policy guardrails.
Data exfiltration
Extracting secrets, PII, and system prompts.
Agent abuse
Manipulating tool-using agents into unauthorized actions.
System-prompt leakage
Exposing your hidden instructions.
Canary detection
Plant a secret value; confirm if the model ever reveals it.
How it works
Groq, OpenAI, Mistral, Anthropic, or any custom endpoint.
a broad library of attack prompts, automatically.
An analysis engine scores every response and flags real weaknesses.
Clear mitigation guidance, then schedule recurring scans.
AI red teaming questions
What is AI red teaming?
AI red teaming is the systematic process of simulating adversarial attacks against an AI system — LLMs, chatbots, or AI agents — to find exploitable vulnerabilities before real attackers do. It covers prompt injection, jailbreaks, data exfiltration, system-prompt leakage, and agent manipulation, producing a graded findings report with prioritized fixes.
How is AI red teaming different from traditional penetration testing?
Traditional pen testing targets infrastructure — servers, networks, and software vulnerabilities. AI red teaming targets the model’s behaviour: whether it can be talked into ignoring its rules, leaking data, or taking unauthorized actions. A network is secure or it isn’t; an AI model has a spectrum of exploitability that only adversarial prompt testing reveals.
How long does an AI red team scan take?
An automated scan with SecuritAI runs in minutes. You point the platform at your AI endpoint, it fires a library of adversarial prompts across all attack categories, and returns graded results immediately. Full engagement-style red teaming with a human analyst layer is scoped by project size.
What AI providers does SecuritAI red team against?
SecuritAI works with any LLM endpoint: OpenAI (GPT-4 and above), Anthropic (Claude), Groq, Mistral, Meta (Llama), and any custom or self-hosted model via API. The attack library is provider-agnostic — vulnerabilities like prompt injection exist across all providers.
Is AI red teaming required for compliance?
AI red teaming is increasingly expected under frameworks including NIST AI RMF (Measure function), Canada’s CCCS guidance, and Bill C-8 cybersecurity program requirements for critical infrastructure. For ISO 27001 and SOC 2, documented adversarial testing evidence strengthens your control set. For regulated and government deployments, it is becoming a procurement requirement.
Choosing a vendor? See why SecuritAI is independent to Lakera Guard on red-teaming depth and compliance-ready reporting.
See what an attacker would find.
Extensive adversarial testing across five providers.