CIO & CISO — GenAI Governance, Red Teaming & Guardrails | TestSavant.AI

SOLUTIONS — BY ROLE: CIO / CISO

Executive Control for GenAI.
Kill Unknown Risk. Ship with Evidence.

TestSavant.ai closes the loop between Red Teaming (hybrid), Nero (autonomous attacker), Auto-tune (Airflow retraining), and guardrail models served via the TestSavant API on Ray—producing exportable evidence for audits and board reporting.

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Reduction in High-Risk Incidents

Guardrail models block jailbreaks, injection, and exfiltration discovered by Red Teaming/Nero.

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Audit Readiness Acceleration

Evidence bundles of tests, diffs, and lineage mapped to AI-specific frameworks.

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Improved Third-Party Coverage

Black-box testing for external models; runtime guardrails enforce policy at the edge.

What You Get as CIO/CISO

Start with outcomes; the platform adapts as threats evolve.

Executive Governance & Evidence

  • Export artifacts: attack results, guardrail hits, model diffs, lineage
  • Mappings support: ISO/IEC 42001, ISO/IEC 23894, NIST AI RMF, GDPR Art 22/15(1)(h)
  • Board-ready summaries with residual-risk acceptance trails

Threat-Led Testing & Readiness

  • Hybrid Red Teaming + Nero generated attacks
  • Regression packs for releases; fail gates on criticals
  • Post-incident learnings fed into Auto-tune retraining

Privacy & Data Controls

  • PII/PHI detection → mask/tokenize before external calls
  • Lineage of sources/tools/policies per conversation
  • Zero-retention and residency routing options

Third-Party/Closed-Model Oversight

  • Black-box probing; attach guardrails at the orchestration edge
  • Telemetry to Aggregator; evidence for vendor reviews
  • Continuous hardening via Auto-tune

From Threat Model to Enforced Control

Executive-level view of failures and the controls that stop them.

Threat / Failure Mode Guardrail Decision (Runtime) Test Method (Red Teaming + Nero) Result
Prompt injection / jailbreakBlock or transform; quarantine artifactLure suites; indirect injections via files/linksTakeover blocked; evidence logs
PII/PHI exfiltrationDetect → mask/tokenize before external callsAdversarial PII payloads; RAG/log path probesLower leakage; masking proofs
Unsafe tool/action executionDeny/transform risky function callsFunction-call abuse; spoofed intentsNo unsafe actions; policy hits recorded
Cross-tenant data bleedScoped retrieval; minimum-necessary reducersMulti-org corpus tests; cross-program suitesNo cross-program artifacts in lineage
Drift & robustness regressionsTrigger Auto-tune; redeploy hardened guardsScheduled regression packs; challenger runsControlled updates; tracked diffs

Architecture & Controls

Discover with Red Teaming/Nero → synthesize data → Auto-tune retrain → redeploy via API on Ray → feed telemetry back.

Deployed Guardrail Models

  • Served by TestSavant API on Ray
  • Categories: prompt-injection, toxicity, privacy/PII, tool-safety
  • Telemetry per request feeds Aggregator

Red Teaming (Hybrid)

  • Automated + manual attack suites
  • Continuously updated from Nero & real incidents
  • Findings drive retraining & evaluation

Auto-tune (Airflow)

  • Ingest → retrain → validate → redeploy
  • Human sign-off optional; diffs & metrics stored
  • Rapid, automated hardening cadence

Nero (Autonomous Attacker)

  • Learns from traces & knowledge base
  • Generates novel, effective attack samples
  • Self-play + feedback from guardrail performance

Attack Knowledge DB

  • Patterns/signatures + human/AI examples
  • Seeds Nero for zero/few-shot attack creation
  • Continuously updated from research & incidents

Data Synthesizer & Aggregator

  • Fuses telemetry, Red Teaming, Nero, synthetics
  • Produces clean datasets for training & tests
  • Supports external sources (papers, HF, CSVs)

Evidence Support for AI-Specific Frameworks

Export artifacts aligned to ISO/IEC 42001, ISO/IEC 23894, NIST AI RMF, GDPR Art 22/15(1)(h).

NIST AI RMF 1.0

  • ✓Risk registers populated from attack results, drift metrics, guardrail performance.

ISO/IEC 42001 (AIMS)

  • ✓Artifacts for PDCA: model diffs, validation metrics, incident learnings.

ISO/IEC 23894:2023

  • ✓Evidence of identification → analysis → treatment → monitoring/re-test.

GDPR (Automated Decisions & Rights)

  • ✓Explainability excerpts; user-facing disclosures; human-in-the-loop records where applicable.

Frequently Asked Questions

Do you require changes to our existing LLM stack?

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No. We operate at the orchestration edge via the TestSavant API. We can probe third-party/closed models and attach guardrails without model internals.

How do you keep pace with new attacks?

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Nero generates novel attacks; Red Teaming harvests real incidents and research; Auto-tune retrains hardened guardrails; the loop never stops.

Deployment options?

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Private VPC patterns, customer-managed keys (KMS/HSM), zero-retention modes, and evidence mirroring to your trust portal.

Make GenAI Board-Ready

See how the adaptive loop (Red Teaming → Auto-tune → API on Ray) reduces risk and produces audit-grade evidence.

TestSavant.ai provides technology and evidence to support AI security and governance programs. Nothing on this page constitutes legal advice.

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