Adversarial campaign design
Plans focus on agent surface.
Adversarial AI testing focused on the models, prompts, tools, and user journeys your agents actually use. No generic checklist, no evals leaderboard.
AI penetration testing
AI red teaming for agents in production
AI red teaming services for AI agents in production. Averta's AI red team simulates the prompt injection, tool abuse, and data exfiltration paths your agents will actually face.
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Trusted by teams securing AI in production
Offensive AI pentesting, built for agents in production.
AI red teaming should produce evidence your security, risk, and engineering teams can act on, not a slide full of theoretical model failures.
100%
Execution-path coverage
Campaigns include prompts, context, tool calls, outputs, and effects.
24/7
Regression replay
Exploit cases run as prompts, tools, models, and policies change.
0
Black-box findings
Each issue includes context, replay steps, impact, and control to close it.
1
Remediation loop
Findings inform classification, policy, audit, and release gates at Averta.
Red-team campaigns for agents that can act.
Averta RED turns offensive testing into a repeatable workflow: scope the agent, attack the execution path, capture evidence, and feed the fixes back into classification and policy.
Exploit-chain simulation
Full attack monitoring.
Averta tests whether an attacker can chain prompt injection into real tool execution: reaching sensitive data, changing state, or coercing downstream systems.
Regression guardrails
Prevent future exploits.
Findings become repeatable tests for classifier updates, policy changes, and model migrations, so old failures stay closed.
Attack surface
Prompt injection (RAG)
poisoned document
Tool abuse: payments
unauthorized transfer
Data exfiltration
records via tool output
System prompt leak
jailbreak probe
AI penetration testing
Find the attack vectors before attackers do.
Averta RED runs AI penetration testing across prompts, tools, retrieval, and the connections between them. Prompt injection, jailbreaks, and unsafe tool calls all surface with a reproducible trace.
Exploit chain
1
Prompt injection
hidden in support ticket
2
payments.transfer()
attacker-controlled args
3
Blocked by policy
tool call denied
Agentic AI red teaming
Exploit the tool calls, not just the prompt.
Most AI testing stops at the chat box. Averta RED red-teams the agent itself, chaining prompt injection into real tool execution to show whether an attacker can move money, read records, or change state.
Release coverage
1
Release v2.3
model upgrade
2
Replayed 1,284 attacks
prior exploit corpus
3Caught
3 regressions caught
before deploy
4
Coverage held
gate passed
Continuous AI red teaming
Testing that does not stop at launch.
A one-time pentest goes stale the moment you change a prompt or upgrade a model. Averta RED runs continuous AI red teaming against every release, replaying past attacks and probing for new ones.
Cyfrin secures its production AI agents with Averta.
Book a demo“Averta gave our agents enforceable boundaries for the dev environment, so instructions like 'don't read .env files' became policy instead of polite suggestions.”
M
Mikhail Karan, Head of Engineering at Cyfrin
Read our AI red teaming guides
Research and playbooks for teams deploying AI agents in production.
Red teaming, specifics
What teams ask when they evaluate AI guardrails against their own production traffic.
AI red teaming is adversarial testing for AI systems and agents. Instead of looking for software vulnerabilities, it simulates the prompts, tool-call chains, and data-exfiltration paths an attacker would use to manipulate the model or its actions, then turns each finding into a reproducible trace and a remediation control.
Traditional penetration testing focuses on systems, networks, and application vulnerabilities. AI red teaming focuses on agent behavior: prompt injection, tool abuse, data exfiltration, unsafe outputs, and whether an attacker can chain model behavior into real actions.
Prompt testing stops at model responses. Averta RED tests the full agent execution path, including retrieved context, tool calls, downstream effects, output handling, and the policy controls that should stop unsafe behavior.
Yes. Campaigns are scoped with your team, run with safe targets and guardrails, and produce reproducible traces without causing real customer, financial, or operational impact.
You receive prioritized findings with replay steps, affected agent surfaces, impact, evidence, and recommended controls. Findings can become regression tests for future releases.
Yes. Campaigns can include your internal abuse cases, product-specific policies, regulator concerns, and known incident patterns alongside Averta's agent attack library.
No. Averta RED can test customer-facing agents, internal copilots, back-office automations, support workflows, onboarding agents, and any agent with access to tools or sensitive context.
See Averta OS in action
Book a demo and see how Averta OS secures your AI agents from input to execution.
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