AI Voice Agent Security Checklist: 25 Questions to Ask Every Vendor

Security questions are where AI voice agent vendor evaluations separate the serious from the superficial. Every vendor will tell you their platform is secure. Few can answer detailed questions about prompt injection defenses, subprocessor chains, key rotation cadences, or how they handle an LLM provider incident. The buyers who ask the right questions get straight answers and can make informed decisions. The buyers who do not ask end up signing agreements that expose them to risks nobody mentioned in the sales cycle.

This guide is the 25-question security interrogation list we use with AI voice agent vendors. It covers the traditional security basics (encryption, access control, audit logs), the voice-specific concerns (call recording, transcript handling, telephony), and the AI-specific risks (prompt injection, jailbreaks, model provider incidents). A vendor who cannot answer at least 22 of the 25 questions clearly is not ready for your business.

Key takeaways

• AI voice agent security extends beyond traditional SaaS security into prompt injection, model provider dependencies, and voice-specific risks.
• Encryption at rest and in transit is the baseline, not the full answer.
• The subprocessor chain matters: the vendor, the LLM provider, the STT provider, the TTS provider, and the telephony provider all need security posture.
• Prompt injection defenses are now a critical vendor capability that did not exist in security checklists two years ago.
• CallSphere's enterprise tier covers the full 25-question checklist with written responses.

The 25-question security checklist

Encryption and data handling (5 questions)

1. What encryption is used at rest and in transit?
2. Where are call recordings stored and how are they encrypted?
3. How are encryption keys managed and rotated?
4. Are transcripts stored separately from recordings?
5. Is customer data used for model training? (Answer must be no.)

Access control (4 questions)

6. What authentication methods are supported (SSO, MFA)?
7. Is role-based access control available with custom roles?
8. How is vendor-side access to customer data controlled?
9. How are privileged actions audited?

Audit and logging (3 questions)

10. What audit logs are maintained and for how long?
11. Can audit logs be exported to customer SIEM?
12. Are logs tamper-evident?

Subprocessors (3 questions)

13. Which LLM providers are used and under what terms?
14. Which STT and TTS providers are used?
15. Which telephony providers are used and what is their security posture?

AI-specific risks (4 questions)

16. How does the platform defend against prompt injection?
17. How are jailbreak attempts detected and blocked?
18. What happens when the LLM provider experiences an incident?
19. How are model updates tested before rollout?

Voice-specific risks (3 questions)

20. How is caller identity verified?
21. How are deepfake voice attacks detected?
22. How is sensitive information (SSN, credit card) handled if spoken?

Compliance (3 questions)

23. What certifications does the vendor hold (ISO 27001)?
24. Is the vendor willing to sign the required BAAs and DPAs?
25. What is the incident response and breach notification process?

Side-by-side comparison table

Category	Weak vendor	Strong vendor
Encryption	TLS in transit only	TLS + AES-256 at rest + key rotation
Access	Username/password	SSO + RBAC + MFA
Audit	Limited logs	Tamper-evident + SIEM export
Subprocessors	Not disclosed	Full list with BAAs
Prompt injection	Not addressed	Active defenses documented
Certifications	None or pending	ISO 27001

The prompt injection problem

Prompt injection is the AI-specific security risk that most traditional security checklists miss. A determined caller can attempt to manipulate the LLM behind the voice agent into doing things it should not: revealing system prompts, bypassing escalation logic, impersonating authorized users, or executing unintended function calls.

flowchart LR
 REQ(["Inbound request"])
 PII["PII detection<br/>regex plus NER"]
 POL{"Policy engine<br/>OPA or rules"}
 REDACT["Redact or mask"]
 LLM["LLM call"]
 OUT["Response"]
 AUDIT[("Append only<br/>audit log")]
 BLOCK(["Block plus<br/>notify DPO"])
 REQ --> PII --> POL
 POL -->|Allow| REDACT --> LLM --> OUT --> AUDIT
 POL -->|Deny| BLOCK
 style POL fill:#4f46e5,stroke:#4338ca,color:#fff
 style AUDIT fill:#ede9fe,stroke:#7c3aed,color:#1e1b4b
 style BLOCK fill:#dc2626,stroke:#b91c1c,color:#fff
 style OUT fill:#059669,stroke:#047857,color:#fff

Strong vendors address prompt injection through multiple layers:

• Input filtering and anomaly detection
• Separation between system prompts and user input
• Function-calling scoping so the agent cannot execute arbitrary actions
• Monitoring for unusual LLM output patterns
• Human review of flagged calls

Ask every vendor to walk you through their prompt injection defense. "We are secure" is not an answer. "We filter input against these patterns, we isolate system prompts from user input using these techniques, and we flag anomalous outputs for review" is an answer.

Worked example: financial services firm

A financial services firm evaluating AI voice agents runs the 25-question checklist against three vendors.

Vendor A answers 15 of 25 clearly. Gaps on prompt injection, deepfake detection, and subprocessor disclosure. Not ready.

Vendor B answers 21 of 25 clearly. Strong on traditional security, weaker on AI-specific risks. Potentially ready with gap remediation.

Vendor C (CallSphere enterprise) answers 24 of 25 clearly with written responses backed by the prompt injection defense documentation, and full subprocessor list. The one gap is deepfake detection, which is on the roadmap. Ready for deployment with a documented mitigation plan for the gap.

CallSphere positioning

CallSphere's enterprise tier is built to pass this security checklist. Encryption at rest and in transit, SSO with SAML and OIDC, custom RBAC, tamper-evident audit logs with SIEM export, full subprocessor disclosure with BAAs, prompt injection defenses, and certification are all part of the enterprise engagement. The pre-built vertical solutions (14-tool healthcare, 10-agent real estate, 4-agent salon, 7-agent after-hours escalation, 10-agent IT helpdesk + RAG, and the ElevenLabs + 5 GPT-4 sales stack) all operate within the same security posture.

Security is not a layer added after the demo. It is part of the vertical solution from day one.

Decision framework

1. Send all 25 questions to every vendor on the shortlist.
2. Require written responses, not verbal commitments.
3. Validate claims through the report and BAA language.
4. Pilot the vendor with a penetration test included.
5. Red-team the voice agent with prompt injection attempts.
6. Verify subprocessor chain end-to-end.
7. Include security commitments in the contract.

Frequently asked questions

Is required for every AI voice deployment?

For enterprise buyers, yes. For SMB buyers, it is a strong preference but not always mandatory.

How often should vendors perform penetration testing?

At minimum annually, ideally quarterly for critical workloads.

What is the biggest AI voice agent security risk?

Prompt injection leading to unauthorized actions or data disclosure.

Do all vendors disclose their subprocessors?

Not all. Require disclosure as a contract term.

Does CallSphere support customer-specific penetration tests?

Yes during enterprise evaluation with coordination.

What to do next

• Book a demo and request the enterprise security documentation.
• See pricing for enterprise tiers with full security coverage.
• Try the live demo before the formal security review.

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