Key Takeaways
- Researchers identified 175,000 publicly exposed APIs, many returning sensitive or production-level responses.
- Exposures were found across cloud platforms, mobile apps, enterprise systems, and IoT devices.
- Many APIs had no authentication at all, enabling anonymous access.
- The findings highlight severe risks: data leakage, account takeover, workflow manipulation, and supply-chain compromise.
- The incident reinforces the need for governance in API-driven AI systems—linked to broader industry risks also seen in TechyKnow’s coverage of the Ex Google engineer convicted case.
- API security is now a core part of enterprise AI and cloud spending trends, as discussed in AI Investments 2026.
Introduction
A recent investigation revealed that 175,000 APIs are publicly accessible on the open internet, many without authentication, exposing sensitive business data and backend functionality.
These exposed APIs span multiple industries and platforms, underscoring how API sprawl and rapid digital development have outpaced organisational security controls.APIs now form the backbone of modern digital systems—including systems built by companies such as Google, cloud providers, SaaS platforms, and IoT manufacturers. Improper exposure is no longer an edge-case—but a structural vulnerability.
Where researchers found the exposed APIs
The 175,000 exposed endpoints were located across:
- cloud environments
- enterprise web applications
- mobile app backends
- IoT devices and embedded systems
- hybrid and multi-cloud deployments
- legacy or deprecated API endpoints
- staging/test environments accidentally made public
Many of these APIs returned live production data or internal system metadata without requiring a key or token.
Q: Are all publicly exposed APIs dangerous?
Not always. Some return non-sensitive metadata.
However, even low-risk endpoints can be chained with others, allowing attackers to map systems, escalate privileges, or identify weaknesses.
The root cause: authentication failures
Researchers found consistent patterns across the exposed APIs:
- missing or disabled authentication
- outdated or test API tokens left active
- hard-coded credentials in mobile applications
- no IP allowlisting
- no rate-limiting or throttling
- leftover endpoints from legacy systems
These issues are particularly concerning as organisations adopt large-scale AI systems, where backend APIs frequently connect to model inference endpoints, training pipelines, and data orchestration layers.
Why the exposure matters now
Today’s systems rely on APIs for everything: authentication flows, transactions, analytics, and AI model interactions. A single insecure endpoint can provide:
- direct access to user data
- manipulation of backend logic
- extraction of application secrets
- reconnaissance opportunities for larger attacks
- corruption of AI inputs used for decision-making
Attackers continuously scan for such endpoints, often automating the reconnaissance process.This trend mirrors broader concerns around AI safety and IP governance. For example, TechyKnow’s analysis of the Ex Google engineer convicted case outlines how internal technical assets—including model architectures and systems—can be compromised when security oversight fails.
Factors driving API exposure in 2026
Three major forces are accelerating the risk surface:
1. API-driven architectures
Microservices and cloud-native designs multiply APIs across environments.
2. Shadow development and rapid prototyping
Teams deploy staging endpoints, preview builds, and internal utilities that are never formally catalogued.
3. AI and automation reliance
APIs now power automated workflows, model endpoints, AI agents, and data pipelines—creating more points of failure.
According to industry spending analysis, enterprises are now shifting budgets toward governance, infrastructure, and security layers to address these concerns—seen in TechyKnow’s AI Investments 2026 overview:
Q: Why do companies lose track of their API footprint?
Because development velocity outpaces documentation and governance, leading to forgotten endpoints that remain exposed for years.
How attackers typically exploit exposed APIs
Once an exposed endpoint is discovered, attackers commonly attempt:
- data extraction through unauthenticated GET requests
- probing for parameter manipulation
- replaying requests or brute-forcing IDs
- sending malformed input to test backend logic
- targeting administrative endpoints
- chaining small leaks to access deeper systems
Even if the initial response seems harmless, attackers gather incremental information and use it to escalate further.
Recommended actions for organisations
TechyKnow’s recommended framework:
1. Conduct a full API inventory
Most companies underestimate how many endpoints they have.
2. Enforce authentication across all endpoints
OAuth, JWT, short-lived access tokens, and zero-trust designs.
3. Apply continuous discovery tools
Tools must run weekly or daily—not annually.
4. Route APIs through central gateways
Gateways provide auditing, throttling, policy enforcement, and unified logging.
5. Remove unused or legacy APIs
Deprecated endpoints often pose the highest risk.
6. Align API security with AI system governance
In AI-heavy environments, API security must protect model inputs, orchestration logic, and data flows.
Conclusion
The discovery of 175,000 publicly exposed APIs reflects a growing structural gap in the security of modern digital ecosystems. As companies scale cloud architectures, automation pipelines, and AI-driven services, APIs become both essential and vulnerable.
To protect their systems, organisations must build a comprehensive governance strategy—inventorying all endpoints, enforcing authentication by default, and continuously monitoring exposure. API security is no longer optional; it is a foundational requirement for protecting data, maintaining trust, and ensuring safe AI operations.
