Offensive Security
AI Security Testing
Cyberus evaluates agreed misuse cases and control boundaries without making claims about every model or future behavior.
- AI-enabled application and integration boundary
- Prompt, data and authorization misuse cases
- Supporting APIs and control paths
- Reproducible evidence and qualified findings
The proposition
Test AI misuse across the stack
Test how an AI-enabled system handles selected misuse cases across the model, application and data boundary. The work focuses on ai-enabled application and integration boundary and records where evidence or authorization limits the conclusion.
The application around the model matters
AI features can introduce new interaction patterns while still depending on familiar identity, authorization, data and software controls. Testing therefore considers the full agreed workflow rather than treating model output alone as the system.
Probabilistic behavior and provider changes affect reproducibility. Cyberus records inputs, configuration and observed results, then states where conclusions are limited or need repeated sampling.
Misuse paths through an AI feature
- Crafted input. A user or document supplies content designed to steer the model away from its intended role.
- Application guardrails. Validation, permissions and isolation decide how far that influence can travel.
- Connected tools and data. If guardrails fail, the model may reach records or trigger actions it should not.
- Consequential outcome. An unsafe disclosure or action affects a customer, employee or business process.
Why it matters
- Business risk: An AI feature can expose data or take unwanted actions through its connections, even if the model itself seems well behaved.
- Decision it supports: Product and risk owners can decide what to launch, restrict or monitor, and which controls deserve investment first.
- What you receive: You receive a boundary map, misuse-case results with reproducibility notes and a backlog of supported fixes.
Evidence for an evolving system
System boundary
Maps models, prompts, retrieval sources, tools, identities and downstream actions in scope.
- Why it matters
- Unclear boundaries let risky tools, data sources or identities go unreviewed.
- Supports
- Agreeing what is tested and what is excluded
Misuse-case results
Documents selected prompt, data, authorization and workflow tests with reproducibility notes.
- Why it matters
- Reproducible examples help engineers fix problems rather than debate whether they exist.
- Supports
- Evidence developers can repeat and act on
Control analysis
Reviews validation, isolation, permissions, monitoring and human decision points.
- Why it matters
- Model behavior is one layer; the surrounding permissions and checks often decide the real impact.
- Supports
- Strengthening layered controls, not only prompts
Risk backlog
Prioritizes supported fixes and identifies cases that need operational monitoring or retesting.
- Why it matters
- Teams have limited time, and AI behavior shifts as models and prompts change.
- Supports
- Sequencing fixes and deciding what to monitor or retest
How AI security testing runs
Why choose Cyberus for AI security testing
Make selected AI risks concrete enough to act on. Testing can reveal reproducible weaknesses and control assumptions in the agreed build. It cannot prove that a probabilistic system will never produce an unsafe result.
AI Security Testing
Frequently asked questions
Is this only prompt-injection testing?
No. Scope may include identity, authorization, data handling, retrieval, tool use, APIs and monitoring as well as prompt behavior.
Can testing use production data?
Only when explicitly approved and appropriately protected; synthetic or sanitized data is preferred where it can answer the question.
Will results stay valid after a model update?
Not necessarily. Model, prompt or integration changes can alter behavior, so material changes may need targeted retesting.
Team certifications
Individual qualifications held by members of the Cyberus team. They are not company accreditations, and not every consultant on an engagement holds every badge.
OSCP
Hands-on penetration testing skills, from enumeration to exploitation and privilege escalation.
OSWE
Web application security skills, including source code review and exploiting complex web vulnerabilities.
OSED
Exploit development skills, including analysing Windows software and writing custom exploits.
OSCP+
Hands-on penetration testing skills, from enumeration to exploitation and privilege escalation.
CRTA
Red team analysis skills, including adversary tactics and techniques.
eWPT
Web application penetration testing skills, from assessment method to exploiting common web flaws.
eWPTX
Advanced web application penetration testing skills, including complex attack techniques.
eMAPT
Mobile application penetration testing skills for Android and iOS applications.
BTL1
Defensive security skills across security operations, phishing analysis, forensics and incident response.
eCIR
Incident response skills, including investigating, containing and analysing security incidents.
CRTE
Red teaming skills focused on Windows environments and the tradecraft used against them.
CCT
EC-Council's Certified Cybersecurity Technician (CCT) validates foundational security, network, and defense skills.
Security+
CompTIA Security+ validates core skills in baseline cybersecurity, risk management, and threats.
Scope an AI security assessment
Share the AI workflow, data boundary and misuse cases that matter to your application.