Threat and abuse-case modelling
Model plausible misuse, prompt, retrieval, tool, identity, data and integration failure paths.
AI assurance
Test the system around the model.
Structured assurance for prompts, tools, data paths, permissions, integrations and misuse cases.
Request a scoping callWho this helps
Built around a buying situation.
- AI product and platform owners
- Security teams reviewing AI-enabled systems
- Buyers requiring technical AI assurance
Useful when
The trigger is already visible.
- An AI system can call tools or access business data
- A release needs misuse and failure-case challenge
- Model testing has not covered the surrounding application
The position
Test the system around the model.
Real exposure often sits in orchestration, permissions, retrieval, plugins, data handling and human assumptions. Pegasus scopes authorised testing around the complete AI-enabled service and links technical findings to business consequence and control ownership.
01
A defined scope and accountable decision owners
02
Controls matched to the real operating context
03
Evidence that can be reviewed, tested and improved
Scope
What the work includes.
Every engagement is scoped around authority, operating context, available evidence and the decision that must be made.
Authorised technical testing
Execute authorised tests against the agreed environment and rules of engagement, preserving decision-useful evidence.
Control and remediation verification
Translate findings into owned remediation, verify material fixes and record residual limitations.
Method
A controlled route from exposure to evidence.
Decision points, responsibilities and verification stay visible from the start.
Discover
Define the exposure, context, evidence, owners and decision that matters.
Design
Select proportionate controls and make responsibilities and hold points visible.
Implement
Embed the agreed system into the real operating workflow.
Verify
Test whether controls work and whether the evidence supports the conclusion.
Improve
Close actions, learn from exceptions and strengthen the system over time.
Outputs
Evidence designed for use.
Scope and evidence map
Prioritised findings and action ownership
Practical control or implementation pack
Verification record and next-step roadmap
Professional boundaries
Precision includes saying what the work does not claim.
- Testing proceeds only with written authorisation and agreed rules of engagement.
- No claim of exhaustive security or zero residual risk is made.
Questions answered
Before you scope the work.
Is AI security testing the same as penetration testing?
They overlap, but AI-enabled systems add model interaction, prompt and retrieval behaviour, tool orchestration and AI-specific misuse cases. Scope should cover both the conventional application and the AI control plane.
Will testing prove an AI system is safe?
No finite test can prove the absence of all failure or misuse. Testing provides time-bound evidence against an agreed scope and supports better risk decisions.
Start the conversation
Bring the exposure. Leave with a controlled route forward.
A first conversation is used to understand context, authority and the decision required—not to force a predetermined package.
Request a scoping call