The AI Red Teaming Reality Check: How DeepKeep Delivers on OWASP

Generative AI requires more than testing basic chatbots. With the release of the OWASP Vendor Evaluation Criteria for AI Red Teaming Providers & Tooling v1.0, the industry finally has a rigorous, standardized benchmark for enterprise AI resilience. DeepKeep tackles these standards head-on with an automated platform built specifically to evaluate the security, safety, and trustworthiness of complex, agentic workflows.

Here is a pragmatic look at how DeepKeep delivers on these new AI red teaming standards without the fluff.

The OWASP AI Red Teaming Compliance Matrix

OWASP Evaluation Pillar

The OWASP Requirement

DeepKeep's Solution

System & Workflow Coverage

Evaluate the entire AI system and workflow, rather than only testing the isolated model endpoint.

Performs deep workflow scanning to relentlessly test agentic systems, APIs, and tool-enabled models for unauthorized actions and vulnerabilities.

Adversarial Creativity

Generate novel, adaptive attack scenarios rather than relying solely on predefined prompt lists.

Uses context-aware testing and Bring Your Own (BYO) seed datasets to dynamically breed novel, multi-turn attack simulations tailored to your specific application.

Data Governance

Protect sensitive data used during testing and support secure enterprise deployment models.

Gives you total control over sensitive testing data with flexible deployments including SaaS, on-premises, and fully air-gapped environments.

Operational Integration

Integrate seamlessly with development workflows and operational pipelines for continuous testing.

Plugs directly into your CI/CD pipelines via robust APIs, running automated regression testing to verify vulnerabilities stay fixed as your code evolves.

Reproducibility & Insights

Provide clear evidence of vulnerabilities, enable reproducibility, and deliver actionable remediation guidance.

Logs every step for deterministic replay, delivering actionable fixes like downloadable fine-tuning prompts and automatic guardrail configurations.

Delivering on the Standard

Dynamic Generation Over Static Scripts

OWASP demands adaptive testing scenarios. DeepKeep abandons static lists of generic jailbreaks in favor of dynamic, context-aware testing. By ingesting your specific application context and custom seed datasets, the platform dynamically generates complex, multi-turn adversarial interactions that accurately reflect the actual threat distribution of your unique environment.

Securing the Entire Agentic Chain

Attackers target the tools your AI uses. DeepKeep performs deep workflow scanning to evaluate your entire agentic architecture. Rather than just analyzing an LLM in a vacuum, it actively probes your system for unauthorized tool invocation, excessive data retrieval, denial-of-service (DoS) patterns, and privilege escalation via external APIs and databases.

Deterministic Replay and Immediate Remediation

Finding a flaw is only half the battle; fixing it requires precision. DeepKeep logs every prompt, response, and intermediate agent step, allowing your engineers to perform a deterministic replay of the exact attack sequence. To bridge the gap to remediation, the platform provides downloadable prompts for model fine-tuning and instantly generates automatic guardrail configurations based on the evaluation findings.

Uncompromising Sovereignty and Cost Control

AI testing inherently involves your most sensitive application and tool-access data. DeepKeep ensures this data remains strictly under your control by supporting standard SaaS, on-premises, and fully air-gapped deployments. Furthermore, as testing scales, DeepKeep provides transparent, configurable testing parameters so you can efficiently manage compute resources and control costs during continuous retesting.

Stop guessing what your AI might do. Test it against the standard that matters.

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