Why Red-Team?
Untested AI Applications Leave Enterprises Exposed.
New AI-specific attacks emerge daily, requiring continuous testing to stay ahead of evolving threats.
Inference Red-Team delivers the industry’s most advanced adversarial testing, leveraging Agentic Warfare,
extensive signature attacks and operational stress-tests to identify vulnerabilities across AI systems before attackers exploit them.
Features
Features
Agentic Warfare:
Run real-world adversarial interactions by engaging the model in conversations that adapt dynamically, uncovering deeper vulnerabilities that surface only during prolonged interactions.
Agentic Fingerprints:
Gain deep observability into how CalypsoAI’s Red-Team agents behave in real time to understand what decisions they make, why they make them, and how they execute an attack.
Signature Attack Packs:
Every month, 10k+ new, high-impact prompts are generated by CalypsoAI agents with the latest threat vectors to systematically test AI systems against advanced attacks.
Operational Attacks:
Evaluate vulnerabilities across the entire AI system, identifying weak points that could allow an attacker to crash the system, cause latency, or consume excessive resources.
Continuous Assessment:
Supports automated, recurring tests to maintain ongoing governance over evolving AI models and systems.
Benefits
Looking for On-Premise Options?
We’re opening an early access program to on-prem installations of our Inference Red-Team product.
Fill in this form and our team will reach out to discuss setting you up.
If you’re just looking for a demo of our red-team product, SaaS or on-prem, you can fill in our demo request form at the bottom of this page.
Use Cases for Red-Team
Unvetted AI Model Selection
Teams adopt AI models without fully assessing their security risks and suitability for enterprise use.
- Evaluates Model Security: Identifies vulnerabilities before deployment.
- Ensures Suitability for Use Case: Assesses risks based on organizational needs.
- Reduces Risk Exposure: Prevents adoption of unsafe or unreliable models.
Insecure AI Development & Deployment
AI-driven applications are built without security testing, increasing vulnerabilities throughout the SDLC.
- Tests AI Applications for Vulnerabilities: Identifies weaknesses before production.
- Strengthens AI Security Posture: Reduces risks in AI development workflows.
- Ensures Compliance from the Start: Aligns AI security with regulatory standards.
Rapidly Evolving AI Threats & Attacks
New AI-specific vulnerabilities emerge constantly, requiring continuous testing to stay secure.
- Continuously Tests AI Systems: Integrates security into CI/CD pipelines.
- Detects Emerging Threats: Informs defense controls for the strongest security posture
- Enhances AI Resilience: Ensures models remain secure over time.
The agentic nature of this solution ensures teams can confidently select the safest models while deploying applications that are rigorously tested for use case-specific vulnerabilities and secured against both existing and emerging GenAI threats.
The agentic nature of this solution ensures teams can confidently select the safest models while deploying applications that are rigorously tested for use case-specific vulnerabilities and secured against both existing and emerging GenAI threats.
