Detect catastrophic failures in enterprise agent deployments
Examples include leaking proprietary IP, leaking sensitive customer data, or performing unauthorized actions. Recurring tests identify high-risk failure modes specific to the customer's system.
What's at stake
- Enterprise AI agents handle sensitive IP, customer data, and critical business processes
- A single catastrophic failure can result in data breach notification, regulatory action, or competitive harm
- Failures may lurk undetected until triggered by specific user inputs or conditions
- Enterprise customers require evidence that agents have been tested for high-risk scenarios
- The cost of a production failure far exceeds the cost of thorough pre-deployment testing
How to solve this
Enterprise agent deployments face three categories of catastrophic failure:
- Data leakage: The agent exposes proprietary IP, customer data, or internal secrets
- Unauthorized actions: The agent performs operations it shouldn't—modifying data, accessing restricted systems, or taking actions outside policy
- Compliance violations: The agent outputs content that violates regulatory requirements or contractual obligations
These failures often don't appear in normal testing. They're triggered by adversarial inputs, edge cases, or unusual combinations of context that regular QA doesn't cover.
The solution is systematic adversarial testing that specifically targets high-risk failure modes. Tests should be customized to your system, your data, and your threat model.
How Superagent prevents this
Superagent provides guardrails for AI agents—small language models purpose-trained to detect and prevent failures in real time. These models sit at the boundary of your agent and inspect inputs, outputs, and tool calls before they execute.
Superagent's Adversarial Tests identify catastrophic failure modes before they reach production. Tests are designed to trigger the worst-case scenarios:
- Prompts that attempt to extract proprietary IP or internal knowledge
- Injection attacks that try to exfiltrate customer data
- Scenarios that probe for unauthorized action capabilities
- Edge cases that might bypass normal guardrails
Tests run continuously or on-demand. Results show exactly which failure modes exist in your system, with evidence of the triggering inputs and outputs. Your security and compliance teams can address each failure before deployment.
Recurring tests ensure that model updates, prompt changes, or new capabilities don't introduce regressions. Every change is validated against your known high-risk scenarios.