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AI Security Assessment.

Identify vulnerabilities in your AI systems before attackers do.

The problem

AI systems create attack surfaces that conventional security testing overlooks. Prompt injection, training-data poisoning, model theft, and insecure API integrations behave nothing like the bugs traditional pentests are tuned for.

Standard pentests lack expertise in systems that accept natural-language input and make probabilistic decisions. The result is coverage gaps right where the new risk lives.

What’s included

—Architecture review of AI systems and integrations
—API security assessment
—Prompt injection and jailbreak testing
—Data pipeline security review
—Access control assessment
—Integration security across third-party services
—Compliance mapping to SOC 2, HIPAA, and PCI-DSS

What you get

—Technical findings report with severity ratings
—Remediation guidance for each finding
—Executive summary for leadership
—90-minute technical debrief with your engineering and security teams

Who this is for

—Companies building AI products
—Organizations deploying AI internally across the workforce
—Security teams preparing for audits or customer due diligence
—Engineering teams seeking expert review before launch
Timeline
2–4 weeks
Structure
Fixed fee

Methodology

1. Scoping

Define targets, success criteria, and rules of engagement. Establish escalation contacts and reporting cadence.

2. Assessment

Hands-on testing across architecture, APIs, prompt-layer attacks, data pipelines, access control, and third-party integrations.

3. Analysis

Consolidate findings, assign severity, and develop remediation guidance grounded in your environment and stack.

4. Delivery

Findings report, executive summary, and a 90-minute technical debrief with engineering and security.

FAQ

Is this a penetration test?

It goes beyond a traditional pentest. The assessment includes architecture review, AI-specific attack vectors like prompt injection and jailbreaking, and integration security across third-party services that conventional pentests do not cover.

Do you need access to our source code?

Source code access is not required. Most assessments are conducted against running systems and APIs. Source review can be added when it materially improves coverage.

Which AI platforms do you cover?

OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, Azure OpenAI, and self-hosted models. Custom integrations are evaluated as part of architecture review.

Will testing affect production?

Production testing follows agreed rules of engagement set during scoping. High-impact tests run against staging environments where staging mirrors production, with explicit go/no-go on any production-touching activity.

What happens if you find a critical vulnerability?

Critical findings are escalated to the agreed contact immediately under a responsible-disclosure protocol, with a remediation pathway proposed before the formal report is delivered.

Book a 30-minute call to scope an assessment for your AI systems.