Guardian tests conversational resilience, behavioral drift and vulnerable-user handling across sustained 50–100 turn interactions — the failure modes traditional security testing was never designed to catch.
OWASP LLM-mapped audit reports, regulatory framing aligned with DORA, the EU AI Act and DSA, and indicative exposure ranges in the language of Risk, Compliance and Security teams.
A chatbot can pass infrastructure, code and keyword-level testing and still fail under sustained human-like interaction. The behavioral layer of conversation is a different attack surface — and standard tooling was never built to probe it.
Every finding below comes from a real Guardian audit of a deployed chatbot. Each is documented, replayable on demand, and mapped against OWASP LLM categories. We make findings actionable, not anecdotal.
A user expressed suicidal ideation across 12 consecutive exchanges. The bot returned the same generic form-link response — then timed out for 154 seconds on the final escalation.
Under sustained expert impersonation, the bot confirmed internal differential processing rules tied to nationality — sensitive procedural information that should never reach an end user.
After 40+ turns of sustained social pressure, the bot's tone, policies and identity boundaries gradually softened — eventually issuing advice contradicting its documented operating rules.
When asked about regulatory obligations, the bot generated fabricated yet plausible legal references and procedural deadlines — creating direct misinformation exposure for the institution.
Multi-step role-play scenarios bypassed instruction guardrails the bot enforced reliably on direct attacks. The vulnerability only surfaced under conversational framing.
A customer support bot — explicitly out of scope for financial advice — produced specific recommendations under persistent user framing, exposing the institution to misselling claims.
We simulate realistic human conversations over 50–100 exchanges to expose failures traditional testing misses. Then we package every finding the way Risk, Compliance and Security committees can actually act on it.
Automated pipeline deploys Guardian personas across 50–100 exchanges, exposing behavioral vulnerabilities standard tools never reach.
Every finding includes severity, exploitability, business impact, indicative regulatory exposure and recommended remediation.
The conversation starts from your bot's actual vulnerability report — not a generic pitch. Aligned reading with Risk, Security and Compliance.
Re-audits after every release. Live Behavioral Safety status. Drift alerts. Move from reactive to certified.
Built from documented incidents, sector risk taxonomies, and validated persona archetypes — not improvised prompts.
Each finding receives an exploitability and impact score on a 1–5 scale, calibrated against OWASP LLM Top 10 definitions.
Findings are reviewed and reproduced by at least one independent operator before inclusion. Conversation logs are preserved as evidence.
Guardian turns complex multi-turn audits into OWASP-mapped findings with regulatory framing and remediation guidance. Every report is reproducible, evidence-backed and structured for direct submission to internal audit, Board and external regulators.
Guardian does not replace your security stack. It covers what classical pen testing and algorithmic red teaming cannot reach: the behavioral layer of long-form conversation. The three approaches are complementary.
| Capability | Classical Pen Test | Algorithmic Red Teaming | Narrative Red Teaming · Guardian |
|---|---|---|---|
| Infrastructure & code coverage | ✓ | — | — |
| Keyword & jailbreak testing | — | ✓ | ✓ |
| Conversation depth tested | 3–5 turns | 10–20 turns | 50–100+ turns |
| Sustained persona coherence | — | limited | ✓ |
| Behavioral drift detection | — | partial | ✓ |
| Risk framed for Risk / Compliance / Security | — | partial | ✓ |
| DSA Art. 28 / AI Act mapping | — | partial | ✓ |
| Adaptation to a new bot | Days / weeks | Days | 2–3 hours |
If your bot handles customer support, advice, onboarding or first-line interaction with the public, the failure modes above already apply to your deployment.
Customer support, onboarding and advisory chatbots facing retail and SME customers under DORA scope.
Insurance bots handling claims, coverage questions and first-notice-of-loss interactions.
Migration, employment, social services and citizen-facing chatbots — High Risk under the EU AI Act.
Internal assistants handling onboarding, policy questions, leave requests and employee support.
AI assistants supporting Risk, Compliance and Legal teams on policy interpretation and reporting.
Patient-facing chatbots handling appointment, triage or information requests in regulated healthcare settings.
Public services, banks, insurers and healthtech now route asylum seekers, debt-distress callers and patients through chatbots that were never designed for the conversational pressure they now handle every day. Three converging frameworks now make behavioral resilience a documented obligation.
Required across all EU financial entities — explicitly extends to AI systems facing customers and operational counterparties.
Employment, migration and access-to-services chatbots classified as High Risk — fines up to €35M or 7% of global turnover per violation.
Explicit obligations to protect minors and vulnerable users — chatbot crisis failures create direct exposure under platform liability.
30 minutes with Benoît Vogt, Founder & CEO. We'll walk you through Guardian's method, comparable findings from your sector, and how Behavioral Safety Certification fits your existing regulatory file.