Red Team AI
Finds behavioural vulnerabilities humans can't find
Harden your AI product
security ready for AI behaviours and post-quantum computing
Blue Team AI
Patches vulnerabilities & strengthens defences
Powered by our RL-SEC "Purple" loop that generates millions of adversarial simulations and automatic behavioural patches.
Automated behavioural security for Voice & Text AI
Audn uses adversary AI to continuously test, break and harden AI behaviour in production systems: the failures code-security tools can't see.
Think HackerOne + Burp Suite + a SOC, purpose-built for AI agents. Built for teams shipping voice, text, and multimodal agents.
Built by the team experienced in companies
Works with any infrastructure:AWSGoogle CloudMicrosoft AzureGithub ActionsAnthropicOpenAI
Safety for regulated industries
We keep your AI agents safe in regulated industries.
FinanceHealthcareTransportationEducationInsuranceLegalGovernment
Two Input Interfaces. Two Security Approaches.
We secure open-ended interfaces to intelligent systems through voice and text modalities, each with tailored security workflows.
FULLY AGENTIC
End-to-End Autonomous Security
Zero human-in-the-loop. Our voice AI red teaming is completely autonomous: from attack generation to vulnerability detection to report delivery.
- Autonomous adversarial voice calls
- Real-time deepfake & voice clone testing
- Automated vulnerability discovery
- Instant report generation
- No integration required, just your phone number
API + HUMAN-IN-LOOP
API Integration + Expert Review
Requires API connection or human oversight. Text-based AI security involves deeper integration and expert analysis for comprehensive coverage.
- API-based attack injection
- MCP tool integration for agent testing
- Expert-guided adversarial campaigns
- Custom attack scenario development
- Human review for business-specific risks
Audn Red + Audn Blue: Complete AI Behaviour Security
Audn Red
Attack & Penetration Testing
The fastest-growing attack corpus because it uses our proprietary Pingu Unchained LLM. We don't just test models; we stress-test real business scenarios your AI agent faces.
- Autonomous adversarial testing
- Voice, text & multimodal attacks
- MCP tool chain integration
- Millions of attack vectors
- Zero false positives with proof
Purpose-built for AI agent behavior testing, not just model vulnerabilities.
Audn Blue
Defense & Protection
Leverages what Audn Red detects to protect any AI agent or AI model from harmful inputs. Real-time guardrails that evolve with emerging threats.
- Real-time jailbreak blocking
- Deepfake & voice clone defense
- Data leak prevention
- Policy enforcement
- Continuous monitoring
Runtime protection powered by real-world attack intelligence from Audn Red.
We Test Business Risk, Not Just Model Vulnerabilities
A vulnerable model is unacceptable. Yes, it's the engine of the car. But your AI agent needs stress-testing against real possible scenarios. Businesses care about specific risks, not generic model weaknesses.
🎯
Specific Risk Testing
Not broad model scans
🤖
Voice AI: Fully Agentic
Zero human-in-loop
👤
Text AI: 1 Human-in-Loop
For real business risk protection
All tests, in one place
We unify and automate essential AI tests via Voice and Text interfaces: so you can protect your system faster.
How it works
Connect
Point us at your IVR or agent phone number. No code required.
Simulate
Run adversarial and emotion‑conditioned attacks at scale.
Report
CWE‑style findings with OWASP/NIST/MITRE mapping and fixes.
Why Audn.AI?
Audn.AI secures more than just voice interfaces. Built on our Pingu Unchained LLM, our platform stress-tests and protects any AI model or agent (voice, chat, or multimodal) across its full lifecycle.
By chaining real attack tools with advanced reasoning and mapping findings to industry frameworks, we offer red teaming and real-time guardrails for AI agents and behaviours, not just models. Our MCP-compatible tools extend these capabilities across sectors and infrastructures.
10x
More attack vectors tested
Zero
False positives with proof
🐧
Pingu Unchained LLM
Unrestricted LLM for High-Risk Research
GPT-OSS base model (120B) from OpenAI with no content filtering with unrestricted access. Answers any question without saying "I can't help with that." For vetted developers tackling edge-case reasoning and sensitive research.
🔓
Unrestricted
No content filtering or safety restrictions
🔬
Research Grade
120B parameters with long chain-of-thought
🛡️
Vetted Access
Identity & organization verification required
Our unrestricted LLM designed specifically for red teaming. Unlike consumer models with safety guardrails, Pingu Unchained thinks like an attacker, exploring jailbreaks, social engineering, and adversarial prompts that other models refuse to generate.
Trained on attack patterns
Vetted organizations only
🔒 Access after vetting process • SOC 2 compliant infrastructure
Solutions
Explore the same offerings from our solutions hub. Tailored security for voice, adversarial testing, and browser protection.
Audn Red
AI Penetration Testing & Attack Corpus
The fastest-growing attack corpus powered by our proprietary Pingu Unchained LLM. Autonomous adversarial testing for AI models, agents, and behaviors, not just code.
PentestingAttack CorpusBehavior Testing
Voice
Audn Red Voice
Voice AI Penetration Testing
End-to-end agentic voice AI security testing. Fully autonomous red-teaming for voice agents with no human in the loop. Tests jailbreaks, social engineering, and data exfiltration via voice.
Voice AIEnd-to-End AgenticNo Human Loop
Purple Team
Audn Purple
RL-SEC Continuous Hardening Loop
Red AI attacks while Blue AI defends: a self-running Purple Team. Both sides train each other through A2A real-world simulations, generating millions of adversarial dialogues humans could never enumerate.
RL-SEC LoopA2A SimulationsAutonomous Hardening
Defend
Audn Blue
Real-time AI Protection & Defense
Leverages Audn Red detections to protect any AI agent or model from harmful inputs. Defense guardrails that block jailbreaks, deep-fakes, and data leaks in real-time.
DefenseReal-time ProtectionGuardrails
Research Tool
Pingu Unchained
Attack-Tool Ready Adversary LLM
Autonomous AI red-teamer that chains real attack tools (nmap, sqlmap, dirsearch, ffuf) with LLM reasoning to unleash realistic penetration tests against voice, chat & agentic systems.
Unrestricted LLMMCP ToolsAgent Security
Coming Soon
Audn Blue Browser
Enterprise Browser Security Extension
Enterprise browser add-on that stress-tests & blocks prompt-injection, jailbreak and covert exfiltration channels across SaaS and internal web apps.
Browser ProtectionPrompt Injection DefenseEnterprise Ready
New
AI2 Compare
Prompt + Dual-Model Side-by-Side
Cousin of GitHub Gists for prompts. Compare pingu-unchained-1 with other models and see how attack paths appear side by side. Share adversarial prompts and evaluate model responses.
Prompt SharingSide-by-Side EvalAttack Showcase
Security Layer
MCP Defender Proxy
Universal MCP Security Gateway
Single MCP proxy with search_tools, describe_tools, and execute_tools that dynamically discovers and wraps all connected MCP servers with security scanning. Works on Windows and Mac.
MCP ProxyDynamic ToolsetCross-Platform
Alert Intel
Audn Alert Triage
EDR & SIEM False Positive Reducer
Do more with less. With 3.5M unfilled SOC positions, hiring isn't the answer. Reduce false positives by 90% so your L1 and L2 analysts can achieve 3x more.
EDR IntegrationSIEM Triage3x Efficiency
Guardrails observability for AI
Identify and fix agent failures automatically. Get deep traces of every turn, surface recurring failure patterns, and ship improvements with confidence.
Step‑level traces & tool callsPattern clustering of failuresRoot‑cause suggestionsVersion comparison & A/BRegression watchWorks with Langfuse/LangSmith
Results: 14 critical jailbreak paths closed, 37 medium risks triaged.
Time to value: First report in 48 hours.
Compliance: Evidence aligned to internal risk reviews and SOC 2 controls.
Traction & Security
0+ adversarial prompts generated · 0+ campaigns run · 0 vulnerabilities found · EU AI Act/ISO 42001/SOC2 · 3 platform integrations
Mapped to industry frameworks
OWASP Top 10 for LLMNIST AI RMF 1.0MITRE ATLASISO 42001TISAX
Export audit-ready evidence with policy mapping and remediation guidance.
Covers risks
Deepfake voicesSpeech based attacksUnauthorized AdviceOverconfident OutputMeaning DistortionFaulty ReasoningInconsistent OutputMulti-step DriftFalse RefusalTemporal InaccuracyToxicitySexual Content
Prompt ReflectionConfidential Data LeakMisinformationImplicit HarmMoral AmbiguityJailbreakingEmotional ManipulationCross-Session LeakSensitive Data LeakRe-identificationTraining Data LeakInstruction Override
Data PoisoningInvalid Tool UsePII LeakStructured Output HandlingPrivacy Regulation ViolationContractual RiskIllegal InstructionsMislabeled OutputCopyright WashingEscaped Meta InstructionsOutput InjectionTool Exposure
System Prompt LeakArgument InjectionDangerous Tool UseViolence & Self-HarmJurisdictional MismatchLocalization MismatchInappropriate HumourBiasBrand HijackStyle InconsistencyBrand Policy ViolationCopyright Violation
Internal ContradictionPrompt InjectionIdentity DriftModel ExtractionLooping BehaviorTone MismatchImagined CapabilitiesDefamationToken Flooding
About Audn.ai
Audn.ai - Huginn and Muninn
The Ravens of Intelligence
Our name audn.ai derives from Odin, the Norse god of wisdom and knowledge. Our logo features two ravens representing Huginn and Muninn, Odin's faithful companions who fly throughout the world gathering intelligence and reporting back to their master.
In Norse mythology, Huginn (thought) and Muninn (memory/will) serve as Odin's eyes and ears across all realms. Similarly, our AI red-teaming platform serves as your organization's vigilant watchers, continuously probing voice agents for vulnerabilities and gathering critical security intelligence.
Founded by a cloud security expert from a Softbank Funded Unicorn Autonomous AI Company with experience in ISO and TISAX compliance, Audn.ai emerged from the recognition that voice agents represent the future of human-AI interaction, from banking to autonomous vehicles. As these systems become ubiquitous, ensuring their security against sophisticated attacks becomes paramount.
Our philosophy embraces the yin-yang balance of security: we think like black hat hackers to build white hat defenses. By understanding how malicious actors exploit voice AI systems, we empower organizations to stay one step ahead. Just as Huginn and Muninn bring both dark tidings and wisdom to Odin, we reveal vulnerabilities not to harm, but to protect and strengthen your AI agents against real-world threats.
Vision
Welcome to post-quantum security research.
We aim to stress test your AI in infinite simulated universes where we train them to be secure before they enter reality.
We are in a finite state now for stress testing, but we aim to prepare the world's computing security for the post-quantum era.
Deepfake & Fraud Testing
Simulate voice‑clone takeovers and ensure KYC/AML compliance. Recreate the 2024 BBC and Arup attacks to stress‑test defences.
Risk Analytics & Audit Logs
Generate actionable reports when assistants leak data or break policy, complete with audit trails to satisfy regulators.
Custom Attack Scenarios
Tailor adversarial campaigns to your services, from prompt‑injection to wire‑transfer social engineering.
CI/CD Gates
Fail builds on high‑risk regressions and export artifacts for auditors.
Emotion‑Aware Attacker
Adaptive tactics based on emotional and behavioral cues unique to voice.
Compliance Mapping
OWASP LLM / NIST AI RMF / MITRE ATLAS mapping with remediation guidance.
Team
Ozgur (Oscar) Ozkan
Multi‑cloud: AWS · Azure · GCPKubernetes · Terraform · CI/CDAI/ML · LLM · Security
About the founder
- Built and operated cloud security at Softbank Funded Unicorn Autonomous AI Company; contributed to TISAX and ISO 27001 compliance.
- Scaled Keymate.AI to $1M ARR in 3 months; ~15% weekly growth; 300k users; top‑12 GPT Store.
- 10+ years across SRE/Platform/Backend; led CI/CD, DevSecOps, and Kubernetes in regulated environments.
- Generalist with deep backend, AI/ML, and platform engineering expertise.
Founder is backed by angels from:500 StartupsTurk Telekom VenturesStartershubITU Seed 2018 (1st in competition)
Startup is backed by:Palantir Foundry AI PlatformElevenLabs StartupsStartup Grind
For investors
Market: contact‑center AI adoption is accelerating; the attack surface is growing. Why now: frontier LLMs + voice spoofing increase fraud risk; compliance pressure is rising.
Frequently asked questions
Why do I need Audn.AI: Cursor for Cybersecurity?
We created a red teamer ethical hacker AI model that works behind the scene and we provide you an easy to use workstation to command and manage all your voice AI cybersecurity from one dashboard.
Why does my company need tests?
Every AI system carries risk, from data leaks to unsafe outputs to regulatory violations. We stress-test your voice AI model like an attacker would, then auto-fix the vulnerabilities, so you can stay safe without slowing down releases.
Which AI models and deployments do you support?
We're voice focused and model and infra-agnostic. You can test individual models like Elevenlabs or any other voice AI infra provider also supports if you use custom LLM behind it like GPT-4o, Claude, or Mistral, as well as full deployments including routed setups, fallback chains, and RAG pipelines. We also support internal-only systems and those with sensitive data access.
Do you test LLMs only, or can you also test RAG, tools, or agents too?
We test any system with a voice AI interface including agents, tool-using setups, RAG flows, and model chains.
How often should my Voice AI be tested?
We recommend daily per-deploy testing to catch regressions and stay ahead of new jailbreaks, policy bypasses, and emergent threats.
What happens after a vulnerability is found? Do you fix it too?
Yes. Findings from Test can be auto-patched through Blue Teamer recommendations our policy-based engine that intercepts and blocks unsafe outputs in real time. You go from detection to protection in one click.
Can you run on-premises or in our private cloud?
Yes. We support full on-premises and VPC deployments for enterprises with strict data or compliance requirements.
Do you support continuous testing or just point-in-time scans?
Both. You can run one-off test campaigns or set up continuous monitoring with alerts, diffs, and regressions tracked over time.
Can you test multilingual models or content?
Absolutely. We cover English, French, German, Spanish, Japanese, and more including prompt attacks and risks specific to each language.
Stress-test AI agents. Automatically validate and harden.
Audn.AI generates and simulates adversarial attacks against voice, text, and agentic AI systems, detecting policy vulnerabilities and fixing them automatically with Audn Blue guardrails.
Ready to secure your AI agents?
Sign up now and get started in minutes.
🎙️🛡️
Voice AI Red Teaming Report
Get a FREE Penetration Test for Your Voice AI
Fully autonomous, zero integration required. Just provide your voice AI phone number and we'll stress-test it with adversarial attacks: deepfakes, jailbreaks, social engineering, and more.
What's Included in Your Report
✓Deepfake voice clone attacks
✓Jailbreak & prompt injection tests
✓Social engineering scenarios
✓Data leak vulnerability scan
✓OWASP/NIST/MITRE mapping
✓Remediation recommendations
🔒 Your data is secure. Testing begins within 24-48 hours. Full report delivered via email.
Is Your AI Secure?
Get Your FREE AI Red Team Report Card
Reveal hidden behavioral flaws before they become incidents. Get actionable guidance from Audn.AI experts to strengthen your model's safety and trustworthiness.
🚀
Innovating with AI?
Building the next generation of custom AI applications and agents to transform your business?
🧠
Frontier or Custom LLMs?
Using frontier models or custom LLMs? Do you know whether they are exposed to real-world attacks?
🔍
Uncover Weaknesses
Would you like a free AI red team assessment to evaluate your AI model for behavioral weaknesses?
What You Get
✓
Comprehensive AI model testing
Testing for jailbreaks, adversarial robustness, PII leakage, code generation risks, misinformation, and more.
✓
Personalized feedback
One-on-one feedback from the Audn security team showing how results were generated and what they mean for your risk posture.
✓
Single-turn & multi-turn attacks
See how your model behaves under pressure from advanced single-turn and multi-turn adversarial attacks.
Find the weaknesses in your models before attackers do. First report delivered within 48 hours.
Book a Demo
Ready to harden your AI agents? Schedule a personalised walk‑through.
© 2025Audn.ai – Behavioural Security for AI Agents
2261 Market Street STE 5585 CA, USA · 483 Green Lanes, N13 4BS London, UK contact@audn.ai