Voice Agent Adversarial Testing

• Founder or CTO, Voice AI Company
• Head of Conversational AI
• CISO at a company deploying voice agents
• QA Lead, Voice Platform

Voice agents now verify callers, take payments, book appointments and handle complaints. They combine speech recognition, an LLM, text-to-speech and tool calls in real time, and each layer can fail in ways a text chatbot test will not catch. Callers also behave differently on the phone: they interrupt, switch languages and apply social pressure.

We build and run adversarial test calls against your voice agent. Synthetic callers, driven by multi-turn playbooks and spoken through text-to-speech with different voices, accents and noise levels, call or stream into your agent the same way customers do. Playbooks cover verification bypass attempts, social engineering, requests for other customers' data, pressure to make unauthorised commitments, attempts to make the agent ignore its rules, abusive callers, switching between English, Hindi and Hinglish, and interruption patterns. Each call is recorded, transcribed and scored against your policy, then reviewed by a tester. Findings are graded PASS, RISK or FAIL and mapped to OWASP LLM and agentic risks, MITRE ATLAS and NIST AI RMF, with recordings as evidence.

• Multi-turn adversarial playbooks for verification bypass, social engineering and data disclosure
• Synthetic callers with varied voices, accents, noise and interruption patterns
• English, Hindi and Hinglish code-switching scenarios
• Checks for unauthorised commitments and policy breaches
• Tool-call checks where the agent books, takes payments or updates records
• PASS, RISK and FAIL evidence with recordings, mapped to OWASP, MITRE ATLAS and NIST AI RMF

1. 01Capture the policyWe record what the agent may and may not say or do: verification steps, disclosures, commitments and escalation rules.
2. 02Design playbooksMulti-turn adversarial playbooks are written for each risk area and language mix.
3. 03Place test callsSynthetic callers run the playbooks against a test number or streaming endpoint.
4. 04Score the callsAudio, transcripts and tool calls are scored against the policy automatically.
5. 05Tester reviewA tester listens to RISK and FAIL calls, confirms findings and rates severity.
6. 06Report and retestYou receive evidence and fixes, and failed playbooks are rerun after changes.

1. Playbooks
   • Policy rules for verification, disclosure and commitments
   • Multi-turn adversarial playbook library
   • Language and persona variations
2. Caller simulation
   • Text-to-speech with voice and accent variation
   • Noise and interruption injection
   • SIP or WebRTC call placement
3. Capture
   • Call recording
   • Transcription
   • Tool-call log from the agent platform
4. Scoring and review
   • Policy scorer
   • Tester review console
5. Reporting
   • PASS, RISK and FAIL evidence pack
   • Framework mapping

A tester listens to every RISK and FAIL call before it becomes a finding, because tone, timing and partial disclosures are hard to judge from a transcript alone. Your team decides on fixes and release timing.

• Voice platforms such as Vapi, Retell, LiveKit or Pipecat-based stacks, or in-house telephony
• SIP trunk or cloud telephony test numbers
• Staging CRM or booking system
• Issue tracker such as Jira or Linear
• CI for scheduled regression calls

• Calls only to test numbers or endpoints you provide
• Synthetic personas and test data only
• Recordings encrypted and kept for an agreed period
• Call volume limits agreed to control telephony cost
• No testing against third-party numbers

• Evidence can support TRAI and DPDP Act 2023 reviews for Indian calling use cases, and GDPR reviews where EU callers are involved.
• Test categories map to the OWASP Top 10 for LLM Applications and MITRE ATLAS.

• SaaS & AI Product Companies

  AI Agent Red-Teaming (Tool Misuse and Goal Hijack)

  Red-team your AI agents for goal hijacking, tool misuse, excessive agency, privilege abuse and memory poisoning, in a sandbox that records every tool call and decision.

• SaaS & AI Product Companies

  Continuous AI Security Regression in CI

  Run versioned prompt-injection, jailbreak and data-leakage suites in CI on every prompt, model, tool or index change, and block releases that regress past agreed severity thresholds.

• Telecom & Contact Centres

  Voice Agent Red-Teaming and Jailbreak Testing

  Adversarial phone calls against your voice agent in Hindi, Hinglish and English, testing verification bypass, data leakage, prompt injection and off-script promises, with recorded evidence.

• NBFCs & Lending

  Conduct Testing for Collections Voice Agents

  Test collections voice agents, in-house or vendor-built, for harassment, third-party disclosure, misrepresentation and vulnerable-borrower handling in Hindi and Hinglish, with audio evidence.