01
Prompt injection
A support ticket, a résumé, a calendar invite — any text your AI reads is a delivery vehicle for instructions you never wrote. We craft the payloads before an attacker does.
AI Red Team · Now booking
You shipped AI.
You shipped AI.
Prove it can't be turned against you.
Every enterprise buyer now asks the same question before they sign: "How do you know your AI can't be broken?" Walk into that security review with the answer — a verified red-team report from the team that helped an AI security company clear a $400M acquisition.
5.0 ★ Gartner Peer Insights
99% Client audit pass rate
$400M AI company exit we helped secure
10/10 OWASP LLM Top 10 coverage
Trusted by teams shipping AI into the enterprise 
The Compliance Beast grew a new head
You beat the audits. You passed SOC 2. Then your product learned to talk — and your buyers' security teams added an AI section to every questionnaire. One jailbreak screenshot can undo two years of earned trust, and the average breach already costs $4.45M. This is the attack surface that ships with every model:
02
Data exfiltration
Your model saw customer data, secrets, and internal docs. We test whether the right conversation makes it repeat them to the wrong person.
03
Agent misuse
Agents with tools can send email, hit APIs, and move money. We probe how far yours can be pushed past its mandate — and what it takes to stop it.
04
RAG poisoning
One planted document in your knowledge base can rewrite your assistant's behavior. We test the pipeline, not just the prompt.
05
Guardrail bypass
Filters catch the obvious. We speak base64, roleplay, foreign languages, and 10,000 mutations per technique to find what slips through.
06
System prompt leakage
Your system prompt is IP, and it often includes things it shouldn't. We check what your model gives up under pressure.
None of this shows up in a traditional pentest. All of it shows up in your buyer's AI review.
Your red team
We've sat on your side of the security review
We've scaled startups and enterprises. We know the pain of a deal stuck in due diligence, a hiring search that won't close, and an AI feature the whole roadmap depends on. So we built the red team we always wished we could hire.
- Led by Volkan Kutal — who contributes to the research the industry uses to learn how to break AI systems.
- Operators trusted by Apple, Tesla, and Atlassian — ex-Apple, Robinhood, and Netflix security engineers.
- Battle-tested on the hardest target — we helped secure Robust Intelligence, an AI security company, through its $400M acquisition by Cisco.
- Transparent billing — 15-minute increments, task descriptions, optional monthly cap. No surprises.
★★★★★
"YSecurity delivered SOC 2 in 5 months, turning security into a sales enabler."
Three steps between you and a verified report
4 to 6 weeks end to end. 1 week minimum when a deal needs it.
- 1
Scope
Free 15-min call, then ~1 week.Tell us what you've built — chatbot, copilot, agent fleet, RAG stack — and which deal or security review is on the line. You get a written plan with attack scenarios, timeline, team, and price. If we're not the right fit, we'll say so.
- 2
Attack
2 to 4 weeks of adversarial testing.The AI red team goes after your system the way a motivated attacker would: automated mutation campaigns plus manual exploit chains, across the OWASP LLM Top 10 and beyond. Findings land in a private Slack channel as they surface — not in a surprise PDF at the end.
- 3
Report and retest
1 week + your remediation timeline.Every finding comes with reproduction steps, business impact, and a fix path. Remediate on your schedule — or hand the fixes to us — then we retest and verify. The verified report is the one your sales team hands to enterprise buyers when the deal needs to clear AI review.
The full OWASP LLM Top 10. Then we keep going.
The checklist is the floor, not the ceiling. Every engagement covers all ten categories, plus the exploit chains specific to your product that no checklist predicts.
LLM01 Prompt Injection
LLM02 Sensitive Information Disclosure
LLM03 Supply Chain Vulnerabilities
LLM04 Data & Model Poisoning
LLM05 Improper Output Handling
LLM06 Excessive Agency
LLM07 System Prompt Leakage
LLM08 Vector & Embedding Weaknesses
LLM09 Misinformation
LLM10 Unbounded Consumption
From risky bet to trusted AI partner
“How do we answer the AI section of the DDQ?” A verified red-team report attached before they ask.
Hoping the guardrails hold Knowing exactly where they held, where they didn't, and what got fixed.
AI as the risky line item in the deal AI security as the reason you win it.
Risky bet Trusted partner
The people breaking your AI (with permission)
Click any photo to read their full bio.
Direct line
Get your free AI attack surface review
Tell us what you've built and what deal or review is on the line. We'll map the surfaces a buyer cares about and reply by email — usually within a day.
Aug 1–6
At Black Hat USA 2026? The red team is at Mandalay Bay all week. Grab time with us in Vegas →
Got it. Your review is in the queue.
Check your email — we'll reply shortly.
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Last questions before the call
What exactly is an AI pentest?
A structured adversarial engagement against your AI systems: LLM apps, copilots, agents, RAG pipelines, and the APIs and infrastructure around them. We combine automated attack campaigns (thousands of mutated payloads per technique) with manual exploit chains built for your specific product. You get findings with reproduction steps, business impact, and remediation guidance — then a retest that verifies the fixes.
We already did a regular pentest. Why do we need this?
A traditional pentest covers your app, cloud, and network. It does not cover prompt injection, agent misuse, RAG poisoning, or data leakage through the model — the exact things your enterprise buyer's AI review now asks about. Most pentest firms don't touch this surface. It's where our red team lives.
Do enterprise buyers and auditors actually accept the report?
Yes. The report is built for both readers: the auditor checking a box for SOC 2 or ISO 42001, and the buyer's security team that actually reads the findings. The verified retest version — original findings, fix dates, verification — is the document that clears security review.
What do you test — the model or the whole system?
The whole system. Attackers don't stop at the model, so neither do we: prompts, tools, function calling, RAG ingestion, vector stores, output handling, rate limits, and the trust boundaries between your AI and the rest of your stack.
How long does it take?
Most engagements run 2 to 4 weeks of active testing, with about a week of scoping before and a week of reporting after. If a deal is on a tighter clock, tell us — the shortest we've delivered end to end is 1 week.
What does it cost?
It depends on scope — how many AI surfaces, how deep, and how fast. We bill in 15-minute increments with task descriptions and an optional monthly cap, so you know the upper bound before we start. The $1,000 checkbox scans on the market don't find exploit chains. Ours do.
Who runs the engagement?
An embedded red team led by Volkan Kutal, who contributes to the research shaping how modern AI systems are tested, alongside operators whose findings are trusted by Apple, Tesla, and Atlassian. The same team that helped Robust Intelligence — an AI security company — reach its $400M acquisition by Cisco.
Can you start before Black Hat is over?
Probably. Scoping usually takes a week, and we can often run it in parallel with a conference schedule. If you're at Black Hat USA 2026 (Aug 1–6, Mandalay Bay), grab time with the team there — or just send the form and we'll reply by email either way.
Someone is going to red-team your AI. The only question is whether they send you the report.
Break it first.
Book your free 15-minute AI security strategy call and walk into your next enterprise deal with the answer.