Aikido

Pentest your AI features before someone talks them into a breach.

Aikido's AI agents map the LLM features in your app, then keep attacking them over long conversations. You get proof for each issue they confirm and a report your auditor can use.
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Trusted by 150k+ orgs
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Loved by 300k+ devs
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4.7/5
Lovable
Pendo
Revolut
Soundcloud
Niantic
n8n
Deel
Visma
Handshake
Joe & the juice
Runway
Too Good To Go
NiCE
Belfius
Lovable
Pendo
Revolut
Soundcloud
Niantic
n8n
Deel
Visma
Handshake
Joe & the juice
Runway
Too Good To Go
NiCE
Belfius

If your AI can reach it, so can anyone who chats with it.

Every LLM feature you ship comes with instructions and access to data, and often tools that act on your systems. Anyone typing into that chat box gets to use them too.
One poisoned document ticket can turn your assistant against your own users.
Your AI can read data and call tools. Anyone who takes over the chat gets direct access to that.
Most AI testing stops at restricting the model’s speech patterns, but misses the model’s permissions to data and tools.

From the first chat message to a proven exploit.

Aikido's AI agents map how your LLM features actually work, then attack them like a creative attacker and prove what they can reach.

Maps your AI entry points

Connect your code and agents read it to see where your AI features live and what they can reach. Can't provide code access? Agents can also understand your app by using it.

Keeps attacking, conversation after conversation

Some guardrails hold at first, then break after a few tries. So agents test yours in fresh chats and long ones, to find out if it holds. They'll also slip instructions into things your AI reads, like an uploaded PDF.

Follows the exploit past the model

A prompt injection on its own tells you the model can be tricked. Agents push it further, into tool calls and your APIs, to see what data it can reach.

Scope your pentest with an expert

In 30 minutes we learn what your AI features do and scope your price.

Multiple checks across your prompts, tools, data and agents.

Aikido covers everything from the OWASP Top 10 for LLM Applications (LLM codes) to the OWASP Top 10 for Agentic Applications (ASI codes).

Direct prompt injection and jailbreaks

Instruction overrides, role-play jailbreaks and encoded or obfuscated payloads that make the model ignore its rules.
LLM01
ASI01

Indirect prompt injection

Instructions planted in documents, web pages, files, emails and tool output the model reads, to see whether they take over.
LLM01
ASI01

System prompt leakage

Pulling out your system prompt, hidden instructions and guardrail setup, which often hold secrets or a map for the next attack.
LLM07

Guardrail and safety filter bypass

Obfuscation, translation, payload splitting and slow multi-turn manipulation to get past content filters.
LLM01

Goal manipulation

Redirecting the agent's objective or plan halfway through a task.
ASI01

Sensitive information disclosure

PII, credentials, internal data and other users' conversations leaking through model output, including across sessions and tenants.
LLM02

Memory and context poisoning

Poisoning persistent memory, conversation history and session state to steer future answers or leak data later.
ASI06

RAG (retrieval-augmented generation) and vector weaknesses

Cross-tenant leaks through retrieval, poisoned documents, unauthorized content and embedding inversion.
LLM08

Data and model poisoning

Feedback loops, user-contributed content and fine-tuning inputs that change the model's behavior in ways you can see.
LLM04

Excessive agency

An agent with more tools, permissions or autonomy than its job needs.
LLM06

Tool and function misuse

Getting the agent to call tools with malicious parameters or chain tools into something you never intended.
ASI02

Insecure tool and plugin integration

Following tool calls into your backend to find SSRF, command injection, path traversal and other injection.
ASI02

Unsafe autonomous actions

Payments, deletions or external calls that run without human confirmation, or with a confirmation step that can be skipped.
LLM06

Multi-agent communication poisoning

Spoofed or poisoned messages between agents that spread malicious instructions across your agent network.
ASI07

Privilege compromise and confused deputy

Getting your AI to use its own credentials and permissions on the attacker's behalf.
ASI03

Broken authorization on AI features

Unauthenticated access to AI endpoints, missing per-user checks on agent actions and IDOR through the agent.
ASI03

Identity spoofing

Impersonating a user, another agent or a trusted service to gain influence it shouldn't have.
ASI03

Improper output handling

Model output reaching other components unsafely, leading to XSS, SQL injection, command injection, SSRF or template injection.
LLM05
ASI05

Unbounded consumption and denial of wallet

Missing rate and quota limits that let someone run up your token bill, exhaust resources or extract your model through volume.
LLM10

Model and supply chain exposure

Exposed or unauthenticated model endpoints and vulnerable AI framework and plugin dependencies.
LLM03
ASI04
Attack chains

One poisoned file is all it takes to leak customer data

Real attackers use one weakness to reach the next, and our agents work the same way.
  • A hidden instruction in an uploaded file gets your assistant to call an internal tool, the tool skips a permission check, and another tenant's invoices show up in the chat.

  • Agents follow that chain as far as it safely goes and show you every step.

  • If agents confirm a web or API issue while testing your AI features, you'll find that in the report too.

Start your pentest

LLM red teaming frameworks vs a real AI Capabilities pentest

Open-source red teaming frameworks fire attack prompts at your model and score its answers, but setup and reporting stay on you. An AI Capabilities pentest goes further: agents find your AI features on their own and follow each attack into the tools and data behind the model. After testing, you get validated findings with proof.
Red teaming frameworks
Aikido AI Capabilities pentest
Setup
You write the target config, pick attack plugins and wire them to your app.
Agents find your AI features from your code or by using your app.
What gets tested
Mostly the model's answers to attack prompts.
The model plus the tools, data, memory and permissions behind it.
How far it goes
Findings stop at what the model said.
Agents follow a finding as far as it goes, often into data that belongs to another customer.
Results
Attack success rates, often graded by another LLM.
Validated findings with proof of exploit and fix guidance.
Reporting
Raw results you turn into a report yourself.
An audit-ready report for SOC 2 and ISO 27001.
Your other pentests
AI only.
Runs in the same product as your other Aikido pentests.
How it works
Runs a fixed set of attacks you pick in advance.
Agents adapt each next attack to what they find in your app.

AI Capabilities Pentest or a Web App Pentest?

Every Aikido web and mobile pentest already tests the AI features inside your app. Pick the AI Capabilities pentest when AI is the part you most want tested.
Web app pentest

Your whole application, AI features included

  • Hundreds of agents audit one app

  • Logic, roles, APIs and AI features get tested

  • You provide: your app, plus code or test users if you're going the white-box route

Start a web pentest
AI Capabilities pentest

Your copilots, chatbots and AI agents

  • Agents spend the whole run on your LLM features only

  • Prompts, tools, memory, retrieval and AI permissions get tested

  • You provide: a staging URL, test users and ideally your code

Start an AI Capabilities pentest

Built your app using Lovable or Supabase?

Connect your Lovable project or Supabase backend and pentest the app in a few clicks. Lovable sends your repository along, so every Lovable pentest runs white-box.
Start your pentest

Pentest your AI features today

Point Aikido at your staging app and add a few test users. Agents take it from there.

Everything included - One fixed price - From start to remediation
Trusted by 150k+ orgs
Faq

FAQs about LLM and AI agent pentesting

What is AI Capabilities pentesting?

AI agents attack the LLM features in your application, like copilots, chatbots, RAG search and tool-using agents, the way an attacker would. They look for prompt injection, data leaks, tool misuse, memory and retrieval poisoning, and broken authorization on AI actions, then prove each finding with a working exploit.

What's the best way to pentest an LLM application?

If you've built an LLM feature into your product, you need a test that covers the model together with the tools, data and permissions behind it. Aikido's AI Capabilities pentest does that and gives you proof of exploit and an audit-ready report.

How is this different from open-source LLM red teaming frameworks?

Frameworks give you building blocks: attack prompts, orchestrators and graders. You still need to set up targets, run the tests, judge the results and write the report. Aikido's agents find your AI features on their own, test everything including tools and data, validate every finding and hand you the report.

Does Aikido cover the OWASP Top 10 for LLM Applications and the OWASP Top 10 for Agentic Applications?

Yes. Aikido tests the main risks from both lists, including prompt injection, sensitive information disclosure, excessive agency, tool misuse, memory poisoning, system prompt leakage, vector and embedding weaknesses and unbounded consumption.

Do you test multi-turn jailbreaks?

Yes. Agents run several separate conversations, each with many turns and several attempts, so they catch guardrails that only give way after a long back-and-forth.

Can you test indirect prompt injection?

Yes. Agents plant instructions in the content your AI reads, like uploaded files, retrieved documents, web pages, emails and tool output, and check whether those instructions take control.

Can Aikido pentest AI agents that use tools or MCP servers?

Yes. Agents test what your AI agent can do through its tools, including whether an attacker can make it call a tool with malicious parameters or reach systems it shouldn't.

Is it blackbox or whitebox?

Both. Connect your repositories and agents read the code to map chat entry points, prompts, tools, memory and retrieval, which finds more for the same credits. Without code, agents work from your app and any context you give them.

What do I need to give Aikido?

A staging URL with your AI features, domain verification, test users for each role you want tested and Aikido's IP addresses on your allowlist. Connecting your code is optional, but recommended.

Can I run it on production?

Run it on staging. Agents use your AI features like a real user would, and that includes tools that can create, change or delete data. Use a test instance with non-production data and switch off destructive tools like payments or outgoing email where you can. You can stop every agent instantly with the panic button.

Does my web app pentest already test AI features?

Yes. Every Aikido Web and Mobile Pentest includes the AI features in scope. The AI Capabilities Pentest makes agents focus only on AI features, and keeps the report focused on AI risks.

Can I use the report for compliance?

Yes. You get an audit-ready report with validated findings, proof of exploit and fix guidance, covering technical controls for SOC 2 Type II, ISO 27001 and HIPAA.

Can you pentest apps built with Lovable or Supabase?

Yes. Aikido connects to Lovable and Supabase, so you can pentest an AI-generated app or an app with a Supabase backend in just a few clicks.

How is pricing calculated?

Pentests run on credits. You see the exact price before anything starts. Check our pentest pricing for the details.

How does this compare to a human AI red team?

Agents use the same techniques a human red teamer would, from slow multi-turn manipulation to chaining a jailbreak into a tool call. Because they run many conversations at once, you can rerun the whole test every time you change a prompt, a model or a tool.