Get listed

Upwind vs Sweet Security for Cloud Runtime CNAPP

Choose Upwind when you need an Inside-Out Cloud and AI CNAPP that pairs agentless scanning with runtime sensors, live inventory, and the AI Agentic Pack in one console. Choose Sweet Security when you need proactive runtime enforcement: Sweet Attack path proof, Learning Loop remediation, and blocking for cloud workloads and AI agents.

Monday cloud triage still fails in two familiar ways. Agentless posture dumps thousands of findings without live process, API, or identity context. Runtime alerts fire without a trustworthy inventory of what else is running. Operators then bounce between consoles while the same workload stays exposed.

Between these two the centers differ. Upwind productizes Inside-Out Cloud and AI security: agentless scanning plus runtime sensors, live inventory, high-signal exposures, and real-time protection, with the AI Security Platform and AI Agentic Pack generally available in May 2026. Sweet productizes proactive runtime enforcement for cloud and AI through the Learning Loop (Attack, Fix, Defend), with Sweet Attack launched 13 May 2026 to prove exploitable paths on runtime context. Both ride eBPF-class runtime. Both talk AI. For application runtime exploitability versus Sweet see Oligo vs Sweet Security. Broader CNAPP shortlists live under cloud security platforms. More pairs under Compare.

Upwind Upwind Sweet Security Sweet Security
JobRuntime-first Cloud and AI CNAPP: agentless posture plus runtime sensors, live inventory, detection/response, AI Agentic PackProactive runtime enforcement for cloud and AI: Learning Loop Attack / Fix / Defend, Sweet Attack path proof, blocking
How a bad day closesCorrelate runtime and cloud activity, prioritize reachable exposure, investigate with Blue / remediate with Green under Choppy coordinationValidate an exploitable path with Sweet Attack, remediate with Fix, block or contain with Defend / response playbooks
Operator morning unitLive inventory drift, high-signal exposures, runtime detections, agent-pack tasksVerified attack paths, runtime guardrail candidates, open response actions
DeployAgentless connectors plus runtime sensors / tracers on VMs, containers, serverlesseBPF runtime sensors across cloud workloads plus CNAPP connectors for posture, identity, API, AI
License/pricingDemo / sales quote; no public dollar SKU (checked 13 Sep 2026)Demo / sales quote; no public dollar SKU (checked 13 Sep 2026)
Who operates itCloudSec / SecOps / platform consolidating CNAPP and AI security into one consoleCloudSec / SecOps prioritizing runtime-proven paths and enforcement over alert volume

Both vendors in this pair compete in that runtime-leaning CNAPP conversation. The split is consolidation of agentless plus runtime with agentic ops (Upwind) versus enforcement-first Attack / Fix / Defend loops (Sweet).

We reviewed first-party documentation, pricing pages, product announcements, and live community threads. We did not test the products in paid production environments, so this is not a hands-on benchmark. This page does not include exploit proofs of concept.

Upwind

Upwind

Sweet Security

Sweet Security

Editions and pricing

Both are demo-led. Upwind markets one platform SKU that includes AI Security. Sweet markets runtime CNAPP plus AI enforcement modules on quote.

Upwind UpwindSweet Security Sweet Security
Packaging storyCloud and AI under one runtime fabric; AI Security described as part of the platform SKU on the May 2026 launchRuntime CNAPP plus Learning Loop modules; Sweet Attack GA to customers on the May 2026 launch
How you buy it nowGet a demo / enterprise quoteDemo / risk assessment path
Public unitsNo public dollar SKU (checked 13 Sep 2026)No public dollar SKU (checked 13 Sep 2026)
What the invoice coversAgentless plus sensor coverage, CNAPP modules in scope, AI Agentic Pack access per quoteRuntime sensors, Attack / Fix / Defend capabilities, AI blocking / response features per quote
Self-serve startDemoDemo

Price the operating model. Consolidation into one Cloud and AI console points at Upwind. Enforcement-first path proof and blocking points at Sweet.

Agentless plus runtime CNAPP coverage

Upwind UpwindSweet Security Sweet Security
Primary surfaceAgentless discovery plus runtime sensors for live inventory, exposure, CDR, API, identity, and AI workloads in one pictureRuntime-first CNAPP with strong enforcement and AI modules; agentless breadth is not the marketing center
AI add-on shapeView / Protect / Validate AI Security on the same fabric; Blue, Green, Red, Choppy agentsAI agent discovery, AI-DR style controls, Agentic AI Blocking; Sweet Attack uses runtime context for cloud and AI paths
Operator workflowInventory and exposure first, then runtime detect and agentic investigate/remediateProve the path, fix it, defend with guardrails and response from the same loop
What teams argue aboutWhether one Upwind SKU replaces separate CSPM, CWPP, and AI tools without gapsWhether Sweet’s runtime depth covers posture breadth the committee expects from a full CNAPP RFP

If the painful queue is fragmented cloud and AI findings across agentless and runtime tools, Upwind is the clearer hire between these two.

Runtime enforcement and attack-path proof

Upwind UpwindSweet Security Sweet Security
Primary surfaceReal-time protection and AI-DR style detections; Red agent validates exploitable paths inside the Agentic PackSweet Attack continuously validates exploitable chains on live runtime topology, then Fix and Defend close them
Enforcement shapeDetect, investigate, and remediate with people and agents; confirm blocking depth in the POCRuntime blocking and containment marketed as a product center, including rogue agent blocking
Evidence styleRuntime forensics correlated with cloud activity and inventoryAudit-ready attack-path reports with runtime conditions that made a path work
What teams argue aboutWhether agentic remediation replaces an enforcement-first Learning LoopWhether Attack / Fix / Defend replaces the need for a broad agentless CNAPP inventory

If the painful queue is proving and stopping exploitable runtime paths before the next alert storm, Sweet is the clearer hire between these two.

Where they overlap

Both sell runtime cloud security with AI coverage. Both use eBPF-class sensors. Both launched major AI runtime features in May 2026. Overlap is category language and sensor technology. It is not the same weekly queue: consolidating agentless plus runtime CNAPP operations versus enforcement-first attack-path proof and blocking.

When to use both

Running both is rarely the first design. Prefer one primary hire. A split can appear when AppSec or cloud SecOps already standardized on Sweet enforcement while a platform team still needs Upwind-class inventory consolidation, or the reverse. That is unusual and expensive.

Skip Sweet for this pair if the funded job is one Cloud and AI CNAPP console with agentless plus runtime and agentic ops. Skip Upwind for this pair if the funded job is runtime-proven attack paths and blocking with a Learning Loop, and posture breadth is already owned elsewhere.

Decide the weekly queue first. If the product must unify agentless posture with runtime sensors for Cloud and AI, that is Upwind. If the product must prove and enforce runtime attack paths for cloud and AI, that is Sweet Security. Only then open the quotes.

FAQs

Are Upwind and Sweet Security the same Runtime CNAPP?

No. Between these two, Upwind leads with an Inside-Out Cloud and AI CNAPP that pairs agentless scanning with runtime sensors and an AI Agentic Pack. Sweet leads with proactive runtime enforcement, Sweet Attack path proof, and Learning Loop remediation and blocking.

How is this different from Oligo vs Sweet?

Oligo vs Sweet is application runtime exploitability and exploit blocking versus Sweet’s Runtime CNAPP. This page compares two cloud-runtime CNAPP-leaning platforms: Upwind and Sweet.

Does either publish list prices?

Neither published a public dollar SKU on first-party pages checked 13 Sep 2026. Both are demo and sales quoted.

Do both use eBPF?

Both market runtime sensors with eBPF-class visibility. Sensor packaging and the surrounding CNAPP or enforcement modules still differ; confirm in a proof of concept.

Is this a scored bake-off?

No. Order is editorial.