Doppel runs realistic, continuous social engineering tests against employees, help desks, and AI agents. Find where people and agents break, then retest as defenses evolve.
Attackers increasingly manipulate the same interfaces customers and employees trust: people, contact centers, voice agents, and conversational systems. One-time manual assessments can’t keep pace as models, prompts, workflows, and social engineering tactics change continuously.
Test employees, helpdesks, contact centers, and AI agents against realistic social engineering designed to break business rules, bypass verification, expose sensitive data, or trigger unauthorized actions.
Use AI-driven conversational red teaming to run repeatable, dynamic tests across large populations and workflows, while human-led conversations bring expert judgment and creativity to bespoke, high-value scenarios.
Move beyond point-in-time engagements with repeatable red teaming that can validate fixes, expose regressions, and reveal new weaknesses as people, agents, policies, and workflows evolve.
Doppel combines AI-driven conversational testing, human-led engagements from your security team or our managed service, and multichannel simulation infrastructure to pressure-test the people and agents that attackers target. Define the objective and guardrails, run realistic conversations at scale, capture the decisions and rule violations that matter, then retest to verify whether defenses actually improved.
1. Choose the target
2. Decide how to engage
3. Test real business rules
4. Retest continuously
The same attack can expose very different weaknesses depending on who or what is on the other end. Doppel runs realistic social engineering attacks against both humans and agents to see whether people follow the process and whether AI agents stick to their rules.
Human judgment and process
Agent guardrails and business logic
To learn how Doppel can help scale your red teaming and pen testing, connect with our team.
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Red teaming is a security testing practice that simulates realistic attacker behavior to uncover weaknesses in people, processes, systems, and controls before a real adversary can exploit them.
In social engineering, that can include testing how employees, helpdesks, contact centers, and AI agents respond to manipulation, impersonation, and high-pressure requests.
Doppel helps organizations run realistic, repeatable social engineering red-team exercises across humans and AI agents. Teams can use AI-driven conversational testing for scale and consistency, human-led testing for bespoke or high-value scenarios, or combine both approaches.
Doppel also supports multichannel testing across voice, SMS, email, collaboration tools, and other supported communication surfaces.
No, though they are closely related. Penetration testing typically focuses on finding and validating technical vulnerabilities in systems, applications, or networks. Red teaming takes a broader, adversarial approach and tests whether an attacker can achieve a real-world objective by combining multiple techniques, including social engineering.
Doppel focuses on the human and conversational side of red teaming: testing how people, AI agents, and business workflows respond under realistic attack conditions. Some describe their work with Doppel as pen testing for AI agents, as they blur the line between technology and behavior. Explore our recent blog post to learn more.
Doppel’s agents engage AI voice agents in realistic, multi-turn conversations with a defined adversarial objective. The goal is to determine whether the target agent can be manipulated into breaking a business rule: for example, bypassing verification, disclosing sensitive information, misusing a workflow, or taking an unauthorized action. Findings can then be used to improve guardrails and retest the agent as its prompts, policies, and capabilities evolve.
Yes. Doppel can red team human targets such as employees, executives, helpdesks, contact centers, and outsourced teams, as well as AI voice agents. The same red-team program can test different targets using AI-driven or human-led conversational approaches, helping security teams understand where both people and automated systems are vulnerable to social engineering.
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