Red-Team - Agentic Warfare for AI Resilience

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 & operational stress-tests to identify vulnerabilities across AI systems before attackers exploit them.

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Features

1.

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.

2.

Extensive Signature Attacks:

10k+ continuously updated prompts systematically test for weaknesses in model responses, targeting established attack techniques like prompt injection, crescendo, etc.

3.

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.

4.

Continuous Assessment:

Supports automated, recurring tests to maintain ongoing governance over evolving AI models and systems.

Benefits

Maximize Efficiency with Minimal Resources

Automated AI security testing eliminates the need for specialized teams, freeing resources for priority initiatives.

Accelerated Time to Value

With same-day setup, discover vulnerabilities in minutes, delivering actionable insights immediately.

Proactive Detection

Stay ahead of threats by uncovering vulnerabilities early with continuously evolving attack scenarios.

Efficient Collaboration and Reporting

Share clear, actionable findings that streamline handoffs across teams and prioritize high-impact issues for faster remediation.

Automated Assessments

Leverage automated, scheduled assessments to ensure AI defenses stay ahead of evolving threats.

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.

If you’re not testing AI, attackers will.

Get Inference Red-Team today.

Speak to the Team Request a Demo