Jungle Labs
AI-native cybersecurity

Defense with teeth.

Jungle Labs gives your team an AI with the attacker's reach, under your command.

It maps your organization inside and out, attacks it to prove what's really exposed, and keeps watch over how your people use AI.

See how it works
  • Google Cloud for Startups partner
  • Built in Israel
  • Design partners in live environments
01 · Why now

Right now, the organization is working for the attacker.

AI lowered the bar for beginners and gave advanced attackers rich context, speed and autonomy. At the same time, companies adopt AI tools, AI vendors and local AI agents faster than they can secure them.

Generative AI reached most surveyed organizations within two years. Cloud and SaaS took more than a decade to get there.

Share of companies using it, by years since first mainstream product

25%50%75%100%051015202530Years since first mainstream productCloudSaaSOpen sourceGenerative AI

Each wave comes from a different survey and population, so read the lines for pace rather than exact levels. Open source data begins in 2014, 16 years after launch; earlier surveys used different questions.

  1. [1] McKinsey, The state of AI (2023–2025 editions)
  2. [2] Eurostat, cloud computing services by enterprises (isoc_cicce_use)
  3. [3] INE Spain, ICT usage in enterprises

Launch dates: OpenAI, ChatGPT launch post (30 Nov 2022) · Amazon, "Amazon Web Services Launches" (14 Mar 2006) · Salesforce IPO prospectus, SEC (2004) · Open Source Initiative, history

02 · The blind spots

Five blind spots attackers already use.

Invisible AI

AI tools, agents and AI vendors wired into company data, credentials and systems. Adopted fast, watched by no one.

Unknown exposure

Internet-facing endpoints the organization doesn't know it has.

The "internal means secure" myth

Core internal services left unprotected because they're "inside."

Unknown attack paths

No real picture of what an attacker can reach from each network segment or device.

Too much security, too little visibility

So many tools that no one sees what's really happening.

Fragmented tools see fragments, and attackers live in the gaps between them.

03 · Our approach

Built like a predator, not an immune system.

Most defenses wait for something to get in, then react. Against attackers that move at machine speed, that's too late. Jungle Labs hunts for the way in before the attacker finds it, from outside and from within.

04 · How it works

See it the way an attacker does. Prove it the way an attacker would.

  1. 01

    Map

    Every system on and inside your network, including forgotten endpoints and "safe" internal services.

  2. 02

    Attack

    Continuous attacks from outside and inside, within the scope you authorize.

  3. 03

    Prove

    Real attack paths, not theoretical vulnerabilities, so you fix what matters first.

  4. 04

    Act

    Task it, and let it act on your command.

See how it works
MapAttackProveAct

What Jungle Labs does.

Built for lean teams with a lot to protect.

For companies in regulated and high-stakes sectors, such as fintech, health and SaaS companies that hold sensitive data, that adopt AI fast and run lean security teams.

CISOs

See what can actually hurt you, proven rather than guessed.

CTOs

A live map of what's really running and how it connects.

GRC teams

Continuous testing and vendor evaluation you can show an auditor.

Privacy engineering

Where your data goes, especially into AI tools.

Your operators stay in command.

Every action is inspectable.

Attacks run only within the scope you authorize.

Nothing disruptive runs without approval.

Jungle Labs works alongside the stack you already run. It gives your team better tools; it doesn't replace them.