AgentFence Feature
Red-team your agents, get a resilience score
AgentFence, Red Team
Example figures- RESILIENCE
- 72 / 100
- this run
- SCENARIOS
- 24
- executed
- FAILURES
- 5
- to remediate
- Prompt-injection scenario
- passed
- Data-exfil via tool-call
- failed
- Scope-escalation attempt
- passed
- Forbidden-target reach
- failed
- POST /api/v2/redteam/run
- deterministic
What AI red teaming does here
AI red teaming exercises your agents against adversarial scenarios (prompt injection, data exfiltration, scope escalation, forbidden-target reach) and measures how well they resist. AgentFence ships a scenario library (GET /api/v2/redteam/scenarios), runs it (POST /redteam/run) to produce a resilience score, and stores results (GET /redteam/results) so you can track improvement release over release.
The scenarios
| Scenario | What it probes | A pass looks like |
|---|---|---|
| Prompt injection | Does the agent follow embedded instructions? | Injection ignored / gated |
| Data exfiltration | Can a tool-call move sensitive data out? | Flow blocked by boundary |
| Scope escalation | Can the agent exceed its granted scope? | Out-of-scope action denied |
| Forbidden target | Can it reach a target it must not? | Call to forbidden target blocked |
The resilience score
- A single 0–100 score summarizing how the agent resisted the scenarios
- Deterministic: re-running the same set reproduces the same score
- Per-scenario pass/fail so you know exactly what to remediate
- Trackable over time as a release-over-release quality signal
How it connects
Red-team failures point straight at governance fixes: a data-exfil failure is a data-boundary gap, a scope-escalation failure is a guardrail gap. Because the same guardrails and boundaries govern production, hardening them to pass a scenario hardens the live agent too, and the run results become evidence for your AI risk program.
Questions people ask
What is AI red teaming?
AI red teaming is adversarial testing of AI agents: running scenarios like prompt injection, data exfiltration, and scope escalation to see how well the agent resists. AgentFence runs a scenario library against your agents and returns a resilience score, with per-scenario pass/fail so you know what to fix.
Is this a live penetration test?
No. AgentFence red teaming is deterministic, scenario-based scoring, repeatable and useful for measuring and improving agent resilience, not a live external penetration test against production infrastructure. It is designed to be run continuously and tracked over time; pair it with real pentesting where that is required.
What is a resilience score?
The resilience score is a single 0–100 measure of how well an agent resisted the adversarial scenarios in a run. Because it is deterministic, the same agent and scenarios reproduce the same score, so improvements are attributable to specific governance changes you made.
How do I improve a low resilience score?
Look at the per-scenario failures. A data-exfiltration failure points to a data-boundary gap; a scope-escalation failure points to a guardrail gap. Tightening those policies and re-running raises the score, and because the same controls govern production, the agent is genuinely hardened, not just test-tuned.
Keep reading
Guides
Calculators
One finance briefing a week
New guides, checklists and benchmarks, by email. Unsubscribe from any issue.
Measure how your agents hold up
Run adversarial scenarios and track a resilience score over time.