Agent red teaming
Break your agents
before attackers do.
Continuously red-team the AI agents and agentic workflows you ship, the fastest-growing and least-tested part of your attack surface.
The chain
surface → inject → chain → harden
Break your agents, end to end. Injection in, credentials out.
Map the agent surface.
Agents don't have one input; they have many. Pensar maps everything reachable: the system prompt, every tool the agent can call, its retrieval and RAG surface, and any MCP servers it talks to. That whole ring is what a real attacker probes.
Land an injection.
A smuggled instruction hidden in a retrieved document or support ticket rides the retrieval feed straight into the agent's context. No direct access required. This is indirect prompt injection, and it's where most agent attacks begin.
Follow the chain to real impact.
A risky-looking reply isn't a finding. Pensar pursues the landed instruction end to end, from tool-call hijacking to SSRF through unbounded fetches to cross-tenant isolation breaks, until real credentials leave your network. The full chain, proven, not a single-turn guess.
Report and harden.
Each chain comes back as a step-by-step finding with the leaked payload and a drafted patch, like an allowlist on the abused tool or a tightened schema, so the hijacked call is refused while legitimate calls still pass.
The product
One injected instruction, a full credential leak.
Pensar runs adversarial conversations against your agents and follows the chain wherever it leads, from a smuggled prompt to tool-call hijacking to exfiltrated secrets.
Tool-call hijack → SSRF → access-token exfiltration
The agent followed an instruction smuggled into a retrieved support article, redirected its fetch_url tool at the AWS instance-metadata endpoint, and posted the IAM session credentials it received to a webhook the attacker controls.
"SecretAccessKey": "****************",
"Token": "FwoGZXIvYXdzEPL…",
"Expiration": "2026-05-26T19:12:04Z" }
Why it's different
Coverage that keeps pace
Agentic surface changes every release. Continuous red-teaming tracks new tools and prompts as you ship them, instead of a one-off audit that ages out in a sprint.
Full-chain, not single-turn
Anyone can flag a risky reply. Pensar proves the end-to-end consequence, from injected instruction to real credentials leaving your network.
Built on a real offensive engine
The same frontier offensive agents that test your apps test your agents, with lab-direct model access and custom payloads per engagement.
FAQ
04 entries
Frequently Asked Questions
Q.01What kinds of agents can you test?
Any agent or agentic workflow you expose: customer-facing assistants, internal copilots, RAG pipelines, and multi-tool agents. Pensar attacks the tools, system prompts, and retrieval surface, whatever model or framework sits underneath.
Q.02What attacks do you run?
Indirect prompt injection, jailbreaks, tool-call hijacking, SSRF through unbounded fetches, cross-tenant isolation breaks, and data exfiltration, plus custom payloads tailored to your specific tools and threat model.
Q.03How do you test without breaking the agent or leaking real data?
Engagements run against non-production environments you scope, and the credentials and data Pensar reaches are the ones you choose to expose to the test. The exfiltration you see in a finding is proof of reachability, run under your control.
Q.04Does this keep pace as we ship new agent features?
Yes. Red-teaming is continuous, so new tools and prompts are tested as you release them, instead of a one-off audit that ages out within a sprint.
Test the agents before they reach production.
Connect an agent or agentic workflow and see the chains a real attacker would find.