A unified cognitive layer for modern security.
A shift away from alert-based tooling — toward unified, context-rich, AI-driven security. Jungle-labs builds Canopy: an adaptive and "learning" cyber organism that fuses offense and defense into a single reasoning layer. It doesn't just watch and respond — it probes, validates, and hunts.
Four layers. One adaptive security system.
Canopy is organized as a living architecture: a cognitive core in the cloud, an adversarial reconnaissance fabric on the outside, reasoning-capable agents inside the customer environment, and small AI models on every endpoint — tied together by Predator, a native offensive-security language.
Canopy brain
Correlates telemetry from XDR, EDR, CNAPP, identity, Git, cloud, and ticketing. Continuously builds a living model of the organization, enriched with darknet and leak intelligence.
Mycelium Net
An adversarial outside-in fabric. Adaptive reconnaissance, exploit validation, API reconstruction, shadow asset discovery, and deep secrets extraction via agentic browsing.
Sloth machines
Reasoning-capable agents deployed inside the customer environment. Assess assets, lateral paths, and threats in real time — and execute live response including isolation, mitigation, and deception.
Macaw
Small AI models running on endpoints, in parallel to the EDR. Macaw secures everything related to AI use on the device — prompts, copilots, agentic tooling, model calls, and the data flowing through them — and reports into Canopy.
One living security architecture
Canopy sits at the center as the cognitive core. Mycelium surrounds it as the external adversarial fabric. Sloth machines operate inside the customer environment as internal reasoning agents, while Macaw models sit on the endpoints themselves securing AI use. Predator, our native offensive-security language, powers execution across the system.
The full Jungle-labs skillset
From darknet monitoring to live in-environment response — every capability lives under one cognitive layer and feeds the same model of your organization.
Canopy · beyond the perimeter
Underground markets & actor chatter.
Credentials & data surfacing externally.
Unmanaged services & infrastructure.
Live behavior, not just disclosures.
Mycelium Net · outside-in offensive
Evolves with the attack surface.
Confirms what's actually reachable.
Shadow APIs · auth surface mapping.
Adversarial probing, fed back into Canopy.
Deep secrets extraction
Navigates apps like a user/attacker.
AI reasoning over runtime responses.
Secrets inferred from timing & context.
Unsanctioned AI tools & services in use.
Sloth · baremetal crisis-aware
What's running, how it connects.
Reachable paths from any foothold.
Isolation · mitigation · deception.
On-the-fly tools compiled in-env.
Where attackers hunt, we hunt first.
A native language for offense, forensics, and investigation
Predator is our custom security programming language — built for offensive operations, forensic analysis, and live investigation under one substrate. It powers Mycelium's adversarial logic, drives in-environment forensics, and compiles into live response actions executed by Sloth machines — a differentiated technical foundation built for operators, not adapted from general-purpose tooling.
Rust-based core
Memory-safe foundation with LLVM JIT compilation.
Native offensive primitives
First-class constructs for reconnaissance, exploitation, and post-exploitation logic.
Integrated AI reasoning
AI-assisted execution paths that adapt to target behavior in real time.
Compiled into live response
Predator programs execute inside Sloth machines for isolation, mitigation, and deception.
target "acme.corp" {
recon = adaptive
validate = true
}
task extract_secrets {
agent browser.agentic
reason semantic.v2
surface api + runtime + ui
}
on_detect lateral_path {
sloth.isolate(asset)
sloth.deceive(actor)
}A thousand hands at machine speed.
Sloth is the super arm of the security operator — not a replacement, a force multiplier. Where a human reaches once, Sloth reaches a thousand times: drafting Predator logic on the fly, running parallel investigations, executing isolation across the environment in the time it takes to blink.
Reach of a thousand operators
Parallel reasoning across every asset, identity, and path — simultaneously. One operator, organization-wide grip.
Writes its own tools, live
When the playbook breaks, Sloth drafts Predator on the fly — monitors, scanners, isolation logic — compiled in-environment.
Glass-box, not black-box
Every action is an inspectable Predator program. Operators read it, tune it, re-run it. Nothing hidden.
Always under operator command
Isolation, mitigation, deception — Sloth executes only what the operator has authorized it to execute.
Correlates across the enterprise stack
Canopy ingests signal from the systems security teams already operate — XDR, EDR, CNAPP, identity providers, Git repositories, cloud environments, ticketing, and more — and turns them into a single coherent model.
- CrowdStrike
- SentinelOne
- Defender
- Wiz
- Prisma
- Orca
- Okta
- Azure AD
- Ping
- GitHub
- GitLab
- Jenkins
- AWS
- Azure
- GCP
- Splunk
- Sentinel
- Elastic
- Jira
- ServiceNow
- Linear
- Snowflake
- Databricks
- S3
Laws of the jungle. Be prepared.
Jungle-labs operates the way the jungle does — adaptive, patient, and unsentimental about what actually works. We don't sell comfort. We build the tools operators reach for when comfort runs out.
Google Cloud for Startups partner
Jungle-labs is a signed partner of the Google Cloud for Startups program — giving Canopy enterprise-grade cloud infrastructure, scale, and security posture from day one.
Bring your environment under one canopy
See how Jungle Labs can help your team unify exposure discovery, signal correlation, and security context in a more controlled operating model.