Get a Demo
Under Attack?
API Custom Threat Detection

Upwind brings Custom Detection Policies for APIs

<br />
<b>Warning</b>:  Undefined variable $photo in <b>/nas/content/live/landing173/wp-content/themes/bricks/includes/elements/code.php(236) : eval()'d code</b> on line <b>24</b><br />
<br />
<b>Warning</b>:  Trying to access array offset on value of type null in <b>/nas/content/live/landing173/wp-content/themes/bricks/includes/elements/code.php(236) : eval()'d code</b> on line <b>24</b><br />
Danilo Michelucci July 17, 2026

Upwind brings Custom Detection Policies for APIs

Every API has a different risk profile. An internal billing endpoint and a public-facing authorization endpoint don’t fail the same way. They don’t get attacked the same way either. A generic ruleset can’t account for that. Custom rules can, and now those rules can see sensitive data too.

This new release brings two things together to improve API Security: custom runtime API rules, so your team defines what suspicious means for your own environment, and sensitive data detection inside those rules, so you can act on where sensitive data actually shows up in a request or response, not just that it showed up somewhere.

Here’s what’s new.

The problem with one-size-fits-all API detection

Most API security tooling ships with a fixed set of detection patterns. That catches the obvious stuff, but it misses the information that’s specific to your organization. 

API-Threat-Detection-mock-a-1024x690

Say your service mesh has an endpoint that should only ever be called by three other services. A generic ruleset doesn’t know that. A fourth caller showing up doesn’t look malicious in the abstract. It only looks wrong if you know your own environment.

Custom rules close that gap. And now they close a second one: knowing sensitive data is present isn’t the same as knowing where.

Custom runtime API rules

API is now a selectable rule type for Upwind’s runtime sensor. You define the logic: specific endpoints, request patterns, caller behavior, access that shouldn’t be happening.

APISecurity

A few examples:

  • Flag any request to an internal-only endpoint from outside its expected service group
  • Alert on abnormal request volume to a specific API path, tuned to what’s actually normal for that endpoint
  • Catch access attempts against deprecated or shadow endpoints that should see zero traffic
  • Detect unauthorized access to sensitive data endpoints, correlated with the process making the call

The rule runs at the sensor level, reading L7 traffic directly from the kernel. No traffic mirroring, no separate proxy. Write it once and it’s live.

Because it’s a sensor rule, it inherits the same runtime context as every other detection type: the process behind the call, the network path, what else was happening on that host. A custom API rule isn’t a filter bolted onto your traffic. It runs on the same runtime fabric as everything else.

Now with sensitive data detection, by location

In addition, custom API Security rules can now detect sensitive data in API traffic, and pinpoint exactly where it appears.

sensitive-data flags are surfaced per HTTP location. A rule can distinguish sensitive data in the URI or query string from sensitive data in the body, and from sensitive data in headers. 

Why that split matters: PII showing up in a response body is a different problem than PII showing up in a request URL. One might be expected behavior for a given endpoint. The other might be a real leak. Without location-level detection, both get flagged the same way, or neither does.

Now you can write a rule that alerts specifically on PII leaking in a response body, while staying silent on the same data category appearing legitimately in a request URL elsewhere in your environment. That’s the difference between an alert your team trusts and one they start ignoring.

Where it fits

Detections from these rules land alongside your process, network, and Kubernetes audit log detections, with the same investigation view: request details, the runtime context around it, everything in one place. You can also filter by detection type when you want to isolate everything your custom rules are identifying.

APISecurity2

Why this matters day to day

A rule that knows sensitive data exists is useful. A rule that knows whether it’s sitting in a header, a query string, or a response body is actionable. That distinction is what turns a compliance checkbox into a real detection your security team can act on without wading through noise.

Runtime context has always been the differentiator behind Upwind’s platform. This puts that logic directly into your hands for the API layer: not a predefined ruleset catching what everyone else catches, but rules built by the people who know what normal, and what sensitive, actually looks like for their own services.

Learn more about Upwind’s API Security capabilities here

Contents

Further Reading

upwind-identities

Introducing the Upwind Identity Graph: End-to-End Identity Security

Identity used to be treated as a directory problem: find the user, inspect the groups, review the assigned roles, and decide whether the account has too much access. That model no longer matches the cloud. A single person may authenticate through Okta, inherit permissions from multiple groups, receive role assignments in more than one cloud,…
AI-Graph

Introducing the Upwind AI Graph: Extending AI Inventory Beyond Cloud Infrastructure

As enterprise adoption of artificial intelligence accelerates, modern AI infrastructure has expanded far beyond traditional cloud perimeters. Securing enterprise AI today requires complete visibility across four distinct operational layers: Traditional cloud security tools stop at the cloud provider boundary. When enterprise teams connect directly to external AI Providers, security teams lose sight of access paths,…
ChatGPT Image Aug 4, 2026, 08_46_20 AM

Keyv Supply Chain Compromise: An npm Worm That Takes Its Orders From an Ethereum Smart Contract

Executive Summary On August 4, 2026 at 09:35 UTC, [email protected] was published to npm carrying a credential stealer, an npm worm, and a persistence mechanism designed to detonate during incident response.  Keyv ranks #274 by npm reach and is present in 84,759 customer environments, and the release shipped with valid GitHub OIDC provenance and a…
Add the Upwind RSS Feed to Slack
Connect the Upwind RSS Feed to your Slack.
Follow the how-to here.
Threat RSS
Add the Upwind RSS Feed to Slack
Connect the Upwind RSS Feed to your Slack.
Follow the how-to here.
Main RSS