Challenge the whole system.
Introduce malicious inputs, service outages, lost acknowledgements and degraded approval context across the agent, its tools and dependencies in an authorised test environment.
OPERATIONAL ASSURANCE FOR AI AGENTS
You know how your agents work.
Do you know how they fail?
We’re building RiskStriker to test complete AI agent systems under attack and service degradation. Measure what actually happens, verify which controls reduce the impact, and establish the tested conditions under which an agent remains within your risk tolerance.
THE ASSURANCE LOOP
01Set the red lineCONTEXT
02Attack and degradeSCENARIO
03Trace the impactCONSEQUENCE
04Retest the controlEVIDENCE
CYBER + OPERATIONAL FAILURESSYSTEM-LEVEL TESTINGCONTROL VERIFICATION
BEYOND THE FINDING
A prompt can fail.
What did the system do?
RiskStriker's proposed approach connects agent behaviour to downstream consequences, then tests what changes after remediation.
Separate intent from impact.
Track what the agent tried to do and what actually happened after the controls operated.
Run it again. Compare.
After your team changes a control, restore the starting conditions and rerun the identical scenario to measure whether impact falls.
THE QUESTIONS THAT MATTER
Evidence for your
agent risk decisions.
The planned assessment connects system context, stress testing and control verification to six practical questions.
Which agents are operating?
Discover agents through connected sources and record the limits of discovery coverage.
What can each agent affect?
Map the systems, data, permissions and actions within its reach.
What outcomes are unacceptable?
Define risk tolerance and red lines for the specific agent and use case.
What happens under pressure?
Measure actual consequences under attack, failure and service degradation.
Which controls reduce the impact?
Compare the same scenario before and after customer remediation.
Under which conditions is risk acceptable?
Record the tested configuration, autonomy and controls, alongside unresolved failures and inconclusive results.
TEST SCENARIOS
One agent.
Several ways to fail.
Explore three illustrative examples from fictional Department X covering data access, duplicate actions and approval failure. Each follows the fault, the consequence and the control to test.
Inside the test scenarios ↗EVIDENCE YOU CAN EXAMINE
Know what was tested.
Know what wasn't.
The planned evidence pack records configuration, autonomy, controls, test coverage, observed impact and remaining uncertainty. Results apply only to the conditions and scenarios assessed. Your organisation decides whether the remaining risk is acceptable.
Explore the evidence approach ↗