DeepKeep has launched Vibe AI Red Teaming, a new capability described as the first-of-its-kind for human-steered, dynamic testing and attack simulation on AI applications and AI agents. The feature moves beyond traditional automated red teaming by allowing security teams to actively guide the testing process using natural language commands, real-time refinements, and domain-specific objectives.
Unlike fully automated red teaming tools that run predefined attacks, Vibe AI Red Teaming lets CISOs and security teams intervene at key decision points, adapt attack plans based on emerging findings, and introduce custom scenarios mid-execution. This human-in-the-loop approach combines the speed and scale of agent-driven testing with the contextual intelligence that only experienced security professionals can provide.
The capability is built to address the growing complexity of AI systems. As organizations deploy more autonomous agents and generative AI applications, the attack surface expands significantly. Traditional red teaming methods often fall short because they lack the flexibility to test nuanced, context-specific risks that arise in real enterprise environments. Vibe AI Red Teaming aims to close that gap by giving security teams an interactive tool that can test for data exposure, compliance violations, and other high-impact vulnerabilities in a controlled yet dynamic way.
This launch reflects a broader shift in AI security toward more intelligent, adaptive testing methods that keep pace with the rapid evolution of AI applications and agents.
Key Terms
Vibe AI Red Teaming — DeepKeep’s new human-steered capability that combines agent-driven execution with real-time human guidance for dynamic attack simulation on AI systems.
Human-in-the-Loop Testing — Security teams actively steer and adapt red teaming attacks using natural language commands during execution.
Agent-Driven Execution — AI agents that autonomously carry out testing scenarios while remaining under human oversight and direction.
Dynamic Attack Simulation — The ability to refine attack types, depth, and objectives in real time based on findings during the testing process.
Conditions Driving This Change
Several converging pressures are making advanced, human-steered red teaming essential for AI security programs today.
AI applications and agents are becoming more autonomous and complex, expanding the attack surface in ways traditional automated red teaming tools cannot fully address.
Security teams need to test for nuanced, context-specific risks such as data leakage, compliance violations, and subtle manipulation that automated tools often miss.
The speed of AI development means new vulnerabilities can appear faster than static testing methods can keep up with.
Regulatory frameworks like the EU AI Act and industry standards such as OWASP and NIST increasingly require organizations to demonstrate proactive risk assessment and mitigation for AI systems.
Many CISOs report low confidence in their ability to protect sensitive data in AI environments, with only 14% of CEOs believing their systems are adequately secured.
Manual red teaming is effective but extremely time-consuming and expensive, limiting how frequently organizations can test their AI systems.
Fully automated red teaming lacks the flexibility and domain knowledge that human experts bring to the process.
Enterprises and managed service providers need scalable solutions that combine the efficiency of automation with the intelligence of human oversight.
These conditions created the exact need for a capability like DeepKeep’s Vibe AI Red Teaming that bridges the gap between manual and automated approaches.
What Security Looked Like Before
Before Vibe AI Red Teaming, security teams relied on two main approaches for testing AI systems: manual red teaming and automated red teaming tools. Manual red teaming involved experienced professionals designing and executing attacks based on their expertise, but it was slow, expensive, and difficult to scale across large numbers of AI applications and agents.
Automated red teaming tools could run large volumes of tests quickly, but they were limited to predefined attack patterns and lacked the ability to adapt based on real-time findings or incorporate human domain knowledge. Many organizations found themselves stuck between these two options — either spending significant resources on infrequent manual tests or accepting the limitations of rigid automated scans.
The result was a testing gap. Subtle vulnerabilities, context-specific risks, and emerging attack techniques often went undetected until they were exploited in production. Compliance teams struggled to produce meaningful evidence of proactive risk assessment, and security leaders had limited confidence that their AI systems were truly resilient. This created ongoing tension between the desire to adopt AI quickly and the need to manage the expanding risk surface effectively.
What’s Changing Now
DeepKeep’s Vibe AI Red Teaming introduces a new middle ground that combines the speed and scale of agent-driven execution with the flexibility and intelligence of human steering. Security teams can now use natural language commands to guide testing sessions, refine attack scenarios in real time, select specific objectives such as data exposure assessment or compliance validation, and intervene at key decision points during the process.
The capability allows for dynamic adaptation — if a particular line of testing reveals interesting behavior, the team can immediately adjust the attack depth, introduce new prompts, or explore related risks without starting a new session. This makes red teaming far more efficient and effective than either purely manual or purely automated methods.
The platform also generates actionable outputs including recommendations, mitigation options, and customized reports tailored for different stakeholders. This helps security teams not only identify vulnerabilities but also communicate findings clearly to executives and compliance groups. By making red teaming more interactive and adaptive, DeepKeep is helping organizations test their AI systems more frequently, more thoroughly, and with greater relevance to their specific risk environment.
Our Take
AI Security Take
DeepKeep’s launch of Vibe AI Red Teaming marks an important evolution in how organizations test and secure AI systems. By combining agent-driven execution with real-time human guidance, the capability bridges the gap between slow, expensive manual red teaming and rigid automated tools that often miss context-specific risks.
For security and governance teams, this is a practical advancement. It enables more frequent, more intelligent testing of AI applications and agents while keeping human expertise firmly in control of the process. As AI systems become more autonomous and complex, the ability to steer red teaming dynamically will become increasingly valuable for identifying subtle vulnerabilities before they can be exploited.
If you’re responsible for AI security or governance in your organization, go to the GAIG marketplace right now. There you can compare the platforms and vendors that deliver advanced red teaming, runtime controls, and visibility capabilities needed to secure AI systems effectively at scale.
