03 / TEST · Continuous AI security validation
Prove how your AI fails, before an attacker does.
Continuously discover, reproduce, remediate, and retest exploitable weaknesses across AI systems and agents.
AI Security Testing
Illustrative product view
AUTHORIZED TARGET / SUPPORT-AGENT-STAGING
Map the system before choosing the attack
TARGETSupport agentStaging / reviewed scope
CONTINUOUS ADVERSARIAL VALIDATION
Prove models and agents withstand realistic attacks before release and after every material change.
Point-in-time prompt tests miss system context, identities, tools, multi-agent paths, and the changes that introduce new failure modes. Teams need repeatable evidence that a control stops the exact attack that previously succeeded.
Unknown attack surface
System prompts, tools, identities, retrieval paths, agent handoffs, and hidden interfaces may be reachable before the test understands them.
Shallow test coverage
Single-turn payloads can miss multi-step exploitation, tool misuse, privilege paths, data exfiltration, and behavior that emerges over time.
Unproven remediation
A closed finding is not proof of protection unless the original attack is replayed against the changed system and control.
REPRODUCIBLE SECURITY TESTING
Move from attack activity to a verified security outcome.
Testing connects the target, system context, attack path, consequence, remediation, and exact replay.
AI TESTINGProof chainTarget to verified change
Target truth
System, version, environment, interfaces, owner, authorization, exclusions, and safe test boundary
System context
Model, prompt, guardrails, identities, tools, MCP servers, data paths, memory, and workflows
Attack evidence
Technique, exact steps, observations, control responses, achieved outcome, and affected asset
Verified change
Reviewed remediation, changed version, exact replay, resulting control decision, and regression case
OUTCOMES
Evidence that directs a fix and proves whether it worked.
Every output remains attached to the target, attack path, observed consequence, system version, and control decision.
Context-led testing
Use reconnaissance and real asset relationships to select attacks that match the system, authority, data, and blast radius.
Reproducible proof
Preserve the attack path, trace, affected assets, severity rationale, and evidence required to reproduce the weakness.
Actionable remediation
Translate findings into specific policy, permission, configuration, prompt, guardrail, or architecture changes.
A permanent regression set
Turn successful attacks into versioned tests that run after model, prompt, tool, data, or application changes.
HOW SECURITY TESTING WORKS
Recon. Attack. Prove. Remediate. Retest.
The workflow turns a discovered weakness into a reviewed change and a permanent regression case.
- 01Recon
Understand before attacking
Fingerprint models, system prompts, guardrails, tools, identities, data paths, interfaces, and observable behavior.
- 02Attack
Exercise realistic failure paths
Test prompt, agent, MCP, tool, RAG, identity, leakage, extraction, safety, multimodal, and multi-agent scenarios.
- 03Prove
Preserve the exploit evidence
Connect the reproducible trace, affected asset, attack path, severity, and successful outcome in one finding.
- 04Remediate
Give the team a precise next move
Recommend the control, configuration, permission, prompt, or architectural change that addresses the observed mechanism.
- 05Retest
Verify the control continuously
Replay the attack in CI/CD or an approved test window and keep the case as a regression test after the fix.
TEST RESULT
Make the failure reproducible, consequential, and retestable.
A finding must show more than an unsafe response. It should establish what was tested, exactly how it failed, why that matters, and whether the same path survives remediation.
- 01
Bounded target
The exact system, model, prompt, tools, data, control configuration, environment, version, and authorized scope.
- 02
Reproducible attack path
Starting state, technique, payload or action sequence, intermediate observations, required permissions, and achieved outcome.
- 03
Consequence and severity
The affected asset, reachable business impact, control failure, assumptions, uncertainty, and evidence supporting prioritization.
- 04
Remediation and exact replay
The reviewed change, changed system version, original attack executed unchanged, observed result, and durable regression case.
PRODUCT CAPABILITIES
Five capabilities working as one AI Security Testing product.
CORE Cloud, Attack Atlas, automation, CI/CD assurance, and managed expertise support one testing outcome.
Recon
Attacker-style mapping and fingerprinting of the application, agent, model, tools, identities, data paths, and controls.
Automated Red Teaming
Continuous, scheduled, or on-demand attacks across single-turn, multi-turn, high-agency, and multimodal paths.
Attack Atlas
Versioned techniques, attack paths, payload families, regression cases, and control mappings that evolve with the target.
CI/CD Assurance
Release gates and triggered retesting after model, prompt, dependency, guardrail, tool, or application changes.
Managed RTaaS
A managed delivery tier for scoping, expert escalation, validation, evidence review, and remediation partnership.
TECHNICAL DECISION SYSTEM
From an authorized target to an exact replay.
Security Testing is the assurance system. It must preserve the target, system context, attack path, consequence, remediation, and replay as one versioned proof chain.
PRODUCT ROLEReconnaissance, attack simulation, reproducible findings, remediation guidance, and continuous regression assurance.
Available product · deployment scopedWHERE THIS PRODUCT CHANGES THE DECISION
Move from product mechanism to the operating outcome.
A product may lead one solution and provide context or evidence in another. Its role is stated explicitly on each path.01 / GOVERNEvidence
Govern AI Adoption
Govern AI adoption with current evidence, accountable ownership, and risk-based approval.
Explore the solution →02 / CONTROLEvidence
Secure Agentic Operations
Authorize every consequential agent action with identity, purpose, context, and policy.
Explore the solution →03 / ASSURECo-lead
Assure AI Releases
Release AI systems with version-bound attack, control, and artifact evidence.
Explore the solution →TEST SCOPE
Understand exactly what the result establishes.
Target, version, environment, attack limits, safeguards, and validity period define the meaning of every result.
Authorization comes first
Every test requires an approved target, owner, scope, environment, interfaces, exclusions, data rules, rate limits, stop conditions, and escalation contacts.
Coverage is bounded, not universal
Results reflect the selected techniques, corpus and version, observable attack surface, time, access, environment, and agreed operating constraints.
A prompt is not an impact
Severity must connect an observed behavior to a reproducible consequential outcome, affected asset, reachable action, or security-control failure.
Automation does not replace expertise
Automated testing supports repeatability and scale; expert scoping, interpretation, novel research, validation, and manual escalation remain necessary.
Findings are version-specific
A result applies to the tested model, prompt, tools, data, guardrails, configuration, environment, permissions, and application version.
Production needs separate safeguards
Some techniques may be inappropriate in production. Any production-safe test requires explicit constraints, monitoring, isolation, and recovery planning.
TECHNICAL FAQ
Targets, safeguards, and operating fit.
How is this different from a vulnerability scanner?
AI and agent testing must reason across prompts, behavior, identities, tools, retrieval, and multi-step outcomes. The product preserves a reproducible attack path rather than reporting only a pattern match.
Can testing run continuously?
Yes. AI Security Testing supports on-demand, scheduled, change-triggered, and approved production-safe testing. Cadence and boundaries depend on the target environment and risk tolerance.
What does a team receive for each finding?
A useful finding includes the affected asset, attack path, evidence, severity rationale, reproducible trace, likely impact, and a concrete remediation and retest path.
What is Managed RTaaS?
Managed RTaaS is the expert-led delivery tier of this product, combining automation with human scoping, escalation, interpretation, remediation support, and validation.
How does testing connect to the Firewall?
The closed-loop design turns a confirmed exploit into a candidate runtime or guardrail policy, deploys it through the approved process, and replays the original attack to prove whether the control works.
START WITH ONE AUTHORIZED TARGET