AI Red Teaming. Every Finding Proven and Replayable.
AI red teaming is adversarial testing of LLM apps and AI agents: prompt injection, jailbreak, and data-leak attempts that show what an attacker can make them do or reveal. Simbian reports only the findings it can replay, each as a request and response your developers can rerun.
In production across 300+ enterprise environments
<1%Finding false-positive rate
OWASPLLM01 and LLM02 risks tested
Same dayRule written when an attack raised no alert
How Does AI Red Teaming Work?
AI red teaming works by sending adversarial prompts at an AI app, then checking which instructions it follows and what data it gives up. Simbian's AI Red Teaming Agent, part of the AI Pentest Agent, runs parallel attackers, and a separate validator replays each success before it counts.
Attack
Prompt Injection Testing and Jailbreaks
Parallel attackers try to override your app's system prompt or talk it past its guardrails, the risk OWASP ranks first as LLM01.
Data Leak Testing for AI Agents
Each run tests whether your AI app or agent can be made to give up sensitive data, and every leak it proves arrives with the exact exchange that exposed it. OWASP lists this as LLM02, Sensitive Information Disclosure.
Scope Enforced Outside the Model
Only targets you approve get tested. Scope is enforced in software, outside the model, and newly discovered assets wait for your approval.
Prove
Replayable Proof per AI Finding
Every finding ships with the exact request and response that proved it, as a cURL command a developer can paste and rerun.
Independent Validator on Each Flaw
The validator works independently of the attackers, and any flaw it can't reproduce never reaches your report. The false-positive rate is under 1%.
Thought Traces and a Separate Action Log
Each finding carries its Thought Trace (the reasoning the Agent followed) and a log, kept outside the Agent, of every request the attackers sent.
Human Sign-Off Before Export
A person reviews and signs off every finding before a report is exported, so the technical report carries only approved findings.
Close
Detection Rules From Proven Attacks
If your monitoring missed a proven prompt injection, the AI Detection Engineering Agent writes a detection rule for it the same day. You choose whether it deploys automatically.
One-Click Retest of the Fix
Once your team ships a fix, a one-click Retest runs the original attack again and shows whether it still works.
Context Lake™ Shared With Your SOC
Findings land in Context Lake™, where your AI SOC and AI Threat Hunt Agents see which attacks worked against your AI apps.
Where AI Red Teaming Fits in Security Operations
A proven attack that raised no alert becomes a detection rule for your SOC, and the AI Threat Hunt Agent looks for earlier attempts at it.
AI Red Team
Approve Scope
Attack AI Apps
Validate & Prove
Report
Fix & Retest
AI Red Team
Approve Scope
Attack AI Apps
Validate & Prove
Report
Fix & Retest
PenTestLearn & Plan
Scan & Enumeration
Assess Vulnerability
Exploit & Validate
Report
Remediate & Retest
PenTestLearn & Plan
Scan & Enumeration
Assess Vulnerability
Exploit & Validate
Report
Remediate & Retest
SOCDetection Eng.
Triage
Investigate
Contain
Incident Response
Client Comms
SOCDetection Eng.
Triage
Investigate
Contain
Incident Response
Client Comms
Threat HuntHypothesis
Hypothesis Validation
Remediation
Update Detection Rules
Threat HuntHypothesis
Hypothesis Validation
Remediation
Update Detection Rules
Simbian AI
Your team
Why Is AI Red Teaming Hard to Keep Up With?
The Reality
1 in 5 Breached Firms Had an AI Model or App Incident
Red teaming AI apps falls behind because the attack surface shifts whenever a prompt, model, tool, or data source changes, and a booked engagement tests only one version. A prompt injection you fixed in March can work again after an April prompt edit.
- 21% of breached organizations had an AI model or app incident in IBM's 2026 Cost of a Data Breach Report, up from 13% in 2025
- Prompt injection showed up in 25% of those incidents, per the same report
- OWASP's 2025 guidance says it's unclear whether fool-proof prevention for prompt injection exists
With Simbian
AI Red Teaming That Keeps Up With Every Release
Run it as often as the app changes, so the version your users reach is the one that's been attacked. Good moments to run it:
- Before each release
- After a fix, to confirm it held
- Whenever a prompt or model changes
Manual vs Automated AI Red Teaming
SimbianEvidence per finding
Manual AI Red Teaming Services
Written up by hand after testing ends
Simbian
Replayable request and response
When an attack raised no alert
Manual AI Red Teaming Services
Left for your SOC to work out
Simbian
Detection rule the same day
Retest after a fix
Manual AI Red Teaming Services
Scoped per contract
Simbian
One click
AI Security Testing That Reports Into Tools You Run
Findings open as two-way tickets in Jira or ServiceNow, and detection rules go to the SIEM your SOC already watches.
AI Red Teaming FAQs
Red teaming in AI means attacking an AI system on purpose, the way an adversary would, to find out whether it will follow injected instructions, drop its guardrails, or leak data. OWASP ranks prompt injection first in its 2025 Top 10 for LLM Applications. Simbian reports an AI finding only after a separate validator replays it.
An AI red team tests whether a generative AI app can be steered away from its instructions or made to reveal what it should protect. Most programs work from the OWASP Top 10 for LLM Applications, which includes prompt injection (LLM01), sensitive information disclosure (LLM02), data and model poisoning (LLM04), excessive agency (LLM06), and system prompt leakage (LLM07). Simbian's AI red teaming covers LLM01, jailbreaks included, and LLM02.
AI red teaming tests what an AI app can be talked into doing, such as overriding its system prompt or leaking data. A penetration test looks for exploitable flaws in your apps, APIs, and network. Simbian's AI Pentest Agent covers both. It chains flaws into proven attacks, and its AI red teaming covers your LLM apps and AI agents.
Four frameworks guide most AI red teaming: the OWASP GenAI Security Project's Top 10 for LLM Applications, MITRE ATLAS, the CSA Agentic AI Red Teaming Guide, and the NIST AI Risk Management Framework (AI RMF). OWASP's 2025 list runs from LLM01 Prompt Injection to LLM10 Unbounded Consumption, ATLAS catalogs adversary tactics against AI systems, CSA covers agent risks like permission escalation, and the AI RMF sets out how to govern AI risk. Use them to choose what to test.
AI red teaming is safe to run against production AI apps when testing stays inside limits you set. Simbian uses non-destructive payloads, logs every request, and tests only approved targets. Scope is enforced in software outside the model, and newly discovered assets wait for your approval. You can stop any test, and the private model never trains on your data.
Red team an AI application whenever its prompt, model, tools, or data sources change, because any of those can reopen a finding you already fixed. Simbian runs on demand, and after a fix, a one-click Retest confirms it held. Test before each release to catch a regression ahead of your users.
What Our Customers Say
Simbian's AI Agents consistently deliver precise and accurate responses, significantly easing our workload. What used to take days now takes minutes, and we're thrilled with how seamlessly it integrates into our existing processes. It's not just about saving time; it's about maintaining the highest standards of security and accuracy, which is exactly what Simbian enables us to do.
Matillion
Suchit Mishra
Director of Information Security
Security is a domain of ever-increasing complexity. Every day a security incident brings new variables. Simbian is building a fully autonomous security platform. We are excited to partner with them as it allows us to be strategic in our security goals, leaving mechanics of security to Simbian.
Axelar
Sergey Gorbunov
Co-founder
Security partners, especially MSSPs and MDRs, are at a critical juncture. Attacks are getting accelerated with AI. We must use AI on defense side too. We have gotten great support from Simbian with its fully autonomous security. It allows us to do more with less, directly impacting both our top and bottom lines.
Cybalt
Khirodra Mishra
CEO
Simbian's platform takes a straightforward approach to solving core problems we see every day in the SOC. The power in the platform, their AI agents, is in its simplicity. They are not adding steps and processes to achieve results. The Security Accelerator platform drives efficiency without sacrificing efficacy. It allows us to shift the role of the analyst; to give them the time to use human insight, because well trained AI that we can review, and audit, is immensely powerful. It sets a whole new bar for security operations.
SMT
Mohammad Qasas
SOC Lead
Simbian's AI agents augment and automate many security services resulting into better efficiencies and increased precision.
Wipro
Siva VRS
Vice President
What Simbian's doing in that space has really been a differentiator and a game changer for how my team's thinking about these problems. We're no longer thinking about a pipeline of work that we've got to have 20 people to solve.
Bottomline
Blaine Brennecke
Director of Security Operations