Continuous AI Security Validation

Your AI changes continuously. Its security testing should too.

Ongoing security validation for AI applications and agents through automation, repeatable test suites and scheduled human adversarial testing.

Continuously Validate Your AI Email Us
Detect security driftSee when change alters the attack surface.
Prevent regressionConfirm fixed weaknesses stay fixed.
Test real behaviorChallenge agents, tools and permissions.
Maintain assuranceGive leaders a current security view.

The Customer Problem

A successful assessment is a baseline—not a permanent answer.

Models change. Prompts evolve. RAG content is updated. Agents gain permissions. New tools and MCP servers are connected. A security assessment performed months ago may no longer represent the system operating today.

01

Constant change

Application releases, model updates and integration changes continuously reshape AI behavior and exposure.

02

Security regression

Previously remediated findings can return as prompts, retrieval sources, tools and authorization logic evolve.

03

Point-in-time blind spots

Automated scanning alone cannot reliably evaluate contextual abuse, novel attack paths or emerging agent behavior.

What RedSkope Validates

Continuous assurance across the changing AI attack surface.

Testing is tailored to the system and combines repeatable validation with specialist-led adversarial reviews. This is not simply automated scanning.

  • Recurring attack testingRepeatable security tests mapped to the application and its threat model.
  • Prompt-injection regressionDirect and indirect injection paths, controls and known bypass conditions.
  • Sensitive-data leakageDisclosure paths across prompts, retrieval, outputs, memory, tools and logs.
  • Authorization boundariesIdentity, object, tenant, role and action boundaries under manipulation.
  • Agent behaviour and agencyPlanning, delegation, approval requirements and actions beyond intended authority.
  • MCP and tool validationTool descriptions, server trust, unsafe invocation, contextual integrity and privilege.
  • Change-triggered testingFocused validation after material changes to high-risk system components.
  • Human adversarial reviewsPeriodic deep testing for novel attack techniques and complex abuse paths.

Engagement Workflow

Baseline. Monitor change. Test again.

A repeatable validation lifecycle designed to keep pace with the way AI products actually evolve.

01 / BASELINE

Establish the posture

Document architecture, threat scenarios, attack surface, controls and initial findings.

02 / VALIDATE

Build repeatable tests

Create validation suites for critical controls, attack paths and previously discovered issues.

03 / DETECT CHANGE

Track material evolution

Identify relevant changes to models, prompts, RAG, agents, tools, permissions and integrations.

04 / TEST

Challenge the system

Run targeted regression tests and scheduled human adversarial assessments.

05 / REMEDIATE

Prioritize correction

Translate results into clear technical fixes, ownership and a managed security backlog.

06 / RE-TEST

Confirm the outcome

Validate remediation and ensure security controls remain effective after further change.

How It Works

Automation plus human adversarial expertise.

Repeatable tests provide consistency and speed. Human-led testing finds contextual, creative and system-level attack paths that automated checks may miss.

01 / AUTOMATION

Consistent coverage

Scheduled and change-driven checks create a dependable signal across frequent releases.

02 / TEST SUITES

Application-specific regression

Tests are grounded in the system’s actual architecture, controls, threat model and prior findings.

03 / HUMAN TESTING

Novel adversarial challenge

RedSkope specialists periodically investigate emerging techniques, complex interactions and new attack paths.

Recurring Outputs

A current security view for builders and leadership.

Reporting shows what changed, what was tested, what failed and what should happen next.

  • 01
    AI security posture reportCurrent attack surface, posture score, new findings and material changes.
  • 02
    Regression and validation resultsTest outcomes, recurring vulnerabilities and confirmation of previously remediated findings.
  • 03
    Change history and remediation backlogSecurity-relevant changes, technical recommendations, priorities and assigned follow-up.
  • 04
    Monthly and executive reportingOperational updates with periodic leadership reporting on material risk and progress.

Who It Is For

Teams building and operating AI-enabled products.

Designed for organizations whose AI systems change frequently, connect to meaningful data or tools, and require assurance beyond a one-time security review.

AI-enabled software companiesSaaS vendors deploying copilotsAgent development teamsEnterprise AI platformsRAG application teamsMCP server operatorsPrivileged workflow ownersProduct security teams

Security That Keeps Pace

Make continuous validation part of your AI lifecycle.

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