Voice Agent Red-Teaming and Jailbreak Testing

• Chief Information Security Officer
• Head of Conversational AI
• Fraud Risk Manager
• Contact Centre Technology Head

A voice agent connected to account systems is a new front door for fraud. Callers can try to talk it past verification, coax out another customer's details, trigger a SIM replacement request or get it to promise a waiver it has no authority to give. They can also switch language or talk over it to slip past guardrails that were only tested in English text.

We test your voice agent the way a determined caller would, over the same phone line or SIP endpoint your customers use. We build multi-turn attack playbooks for your agent's scope: verification bypass and impersonation, account and personal data leakage, prompt injection through spoken instructions, system prompt disclosure, unauthorised actions such as SIM replacement or plan changes, off-script offers and refunds, and abusive responses. Synthetic caller voices run the playbooks in Hindi, Hinglish, English and agreed regional languages, with accents, background noise, interruptions and DTMF input. Every call is recorded, scored PASS, RISK or FAIL and verified by an engineer, and you keep a regression suite to re-run after changes.

• Attack playbooks for verification bypass, impersonation, data leakage, prompt injection and unauthorised actions
• Calls over real telephony or SIP with synthetic voices, accents, noise, barge-in and DTMF
• Language-switching attacks across Hindi, Hinglish, English and agreed regional languages
• PASS, RISK and FAIL scoring with call audio, transcript and the turn where the failure occurred
• Findings mapped to OWASP Top 10 for LLM Applications and MITRE ATLAS techniques
• Re-runnable regression suite for testing after prompt, model or tool changes

1. 01Agree scope and rulesTest numbers, synthetic accounts, call windows and in-scope behaviours are agreed in writing.
2. 02Build attack playbooksMulti-turn playbooks are tailored to the agent's intents, tools, languages and fraud risks.
3. 03Place adversarial callsSynthetic callers run the playbooks over SIP or phone lines, with noise, interruptions and DTMF.
4. 04Score and verifyEach call is scored PASS, RISK or FAIL, and an engineer listens to every ambiguous or failing call.
5. 05Report findingsFindings with audio, transcripts, framework mapping and fix suggestions go to your product and security teams.
6. 06RetestAfter fixes, the same playbooks run as a regression suite to confirm closure.

1. Test design
   • Scope and threat model
   • Attack playbook library
   • Synthetic test accounts
2. Call execution
   • SIP and telephony caller
   • Multilingual synthetic attacker voices
   • Noise, barge-in and DTMF injector
3. Evaluation
   • Call transcription
   • LLM judge with rule checks
   • Engineer verification of audio
4. Reporting
   • Evidence store with call audio
   • OWASP LLM and MITRE ATLAS mapping
   • Regression suite runner

Engineers verify every RISK and FAIL call by listening to the audio before it is reported. Your security and product owners decide severity, fixes and go-live readiness.

• SIP trunks and test phone numbers
• In-house or vendor voice agent platforms
• CI pipeline for regression runs
• Jira or similar for findings tracking

• Tests run only against test numbers and synthetic accounts agreed in writing
• No real customer data used or requested
• Call rates and windows limited to avoid disrupting operations
• Production fraud controls tested only with explicit approval
• Evidence encrypted and shared with named contacts only

• Results are mapped to the OWASP Top 10 for LLM Applications and MITRE ATLAS to help your team evidence testing; they do not certify the agent.
• Test evidence can support DPDP Act 2023 expectations for reasonable security safeguards in systems that handle customer data.

• Telecom & Contact Centres

  Compliance Evidence for AI Calling (TRAI and DPDP)

  Test and document how your AI calling handles consent, DND preferences, calling hours, disclosures, opt-outs and personal data, and give compliance teams and clients an evidence pack.

• Telecom & Contact Centres

  Multilingual Inbound Voice Agent for L1 Support

  A voice agent that answers routine L1 calls in Hindi, Hinglish and regional languages, resolves what it safely can through your systems and hands the rest to an agent with full context.

• SaaS & AI Product Companies

  Voice Agent Adversarial Testing

  Adversarial test calls to your voice agent in English, Hindi and Hinglish: identity bypass, data disclosure, off-script promises and speech-layer flaws, with PASS, RISK and FAIL evidence.

• Banking

  Red-Teaming for Bank Chatbots and Voice Agents

  Adversarial testing of bank chatbots and voice agents for prompt injection, data leakage, account-takeover social engineering and unsafe advice, in English, Hindi and Hinglish.