Services/AI Security
OffensiveApplication & CloudDetection & ResponseManaged Detection & ResponseIncident Response & DFIRSecurity Program & RiskAI
05
Service 05Model red teaming · Prompt injection

AI Security

We test the security of your AI systems: models, agents, and guardrails.
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At a glance
Typical duration2–4 weeks
Engagement shapesPoint-in-time · Retainer
Led bySenior AI security engineer
OutputFindings and guardrail design
§ 01Overview
AI Security

AI systems are a new attack surface. We test models, agents, tool use, and RAG architectures against the latest known attack techniques, and help design effective guardrails.

§ 02What's included

What the service covers.

Engage any item on its own, or combine them into a single engagement.
01
Model red teaming
Systematic testing of model behavior: jailbreak techniques, harmful output, and guardrail bypasses.
02
Prompt injection testing
Direct and indirect prompt injection attacks against your application and the data sources it uses.
03
Agent and tool-use review
We assess what happens when an attacker attempts to steer the actions an AI system can take.
04
RAG architecture assessment
We examine RAG systems for data leakage, source poisoning, and context manipulation.
05
Guardrail design
We help design and validate the controls that keep AI system behavior within defined boundaries.
06
AI policy and governance
Policies aligned with the NIST AI RMF and the EU AI Act, adapted to how your organization actually operates.
§ 03How we approach it

A clear methodology, every time.

1
System mapping
We document the models, agents, data sources, and the trust boundaries between them.
2
Attack testing
We run prompt injection, tool abuse, and other attacks against the live system.
3
Guardrail validation
We measure the effectiveness of existing controls under real attack.
4
Recommendations and documentation
We deliver concrete fixes, guardrail recommendations, and governance documentation.
§ 04What you get

Results you can act on.

Every engagement ends with documented findings and evidence, written for the technical team and for the board.
01Findings with reproducible attack examples
02Agent and tool-abuse analysis
03Guardrail recommendations
04AI risk and governance guidance
05Retest after controls are implemented
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Offensive Security

Independent and vendor-neutral. We don't resell the tools we test.

Our only product is expertise and evidence, so our advice has no agenda but yours.
Independent
Vendor-neutral. No licences to sell, no conflicts of interest.
Senior-led
Every engagement is run by senior engineers, not handed to a queue.
Evidence-led
Reproducible findings and documented proof, not severity labels.
Regulator-ready
Built to satisfy NIS2, DORA, ISO 27001, and GDPR by design.
FAQ

Questions, answered

How is the security of an AI system tested?
We map the trust boundaries in the system and test them with attacks, with recommendations made at the architecture level. Prompt injection, tool abuse, and data exfiltration are structural problems and are not solved by rephrasing the prompt.
Can prompt injection be fixed with a better system prompt?
No. A model processes untrusted text with the same level of trust as its own instructions. Effective controls sit outside the prompt: scoped tool permissions, output validation, and complete activity logging.
Do you test only the model, or the whole application?
The whole application. We test the system as a whole: data retrieval, tools, and the data paths an attacker would actually try to exploit.
How does this connect to the EU AI Act?
Directly. We align the testing and documentation with the obligations that apply to your system, so the results also serve as evidence of regulatory readiness.
Further reading

Related articles

Ready to scope ai security?

Our team will help you define the scope on a 30-minute call.
Book a scoping call or email contact@raptoric.com