CVE-2026-105664 in EseeCloud App
Summary
by MITRE • 10/16/2026
The endpoint exposes an observable response discrepancy when processing ID values. A request submitted with a nonexistent ID returns a distinct error response code from one submitted with a valid, registered ID, allowing an attacker holding a valid access token - but without further authentication or authorization - to distinguish valid ID values from the full 10-digit numeric search space. Combined with the absence of meaningful rate limiting on this endpoint, this discrepancy constitutes an enumeration oracle, enabling an attacker to discover registered devices at scale.
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Analysis
by VulDB Data Team • 10/16/2026
The vulnerability described represents a classic information disclosure flaw rooted in inconsistent error handling mechanisms within an application programming interface. Specifically, the endpoint exhibits a response time or status code disparity when processing identifier values that do not exist compared to those that correspond to valid, registered entities. This behavioral difference creates what is technically known as an enumeration oracle. An attacker possessing a valid access token can exploit this discrepancy by submitting requests with varying ID values and analyzing the server's responses. If the response for a nonexistent ID differs significantly from that of a valid ID in terms of HTTP status codes or timing, the attacker gains a reliable signal to distinguish between registered and unregistered identifiers within the search space.
This flaw fundamentally undermines the principle of least privilege by allowing unauthorized enumeration despite the presence of authentication tokens. While the token authenticates the user's identity, it fails to enforce proper authorization checks that would restrict access based on whether the requested resource belongs to or is accessible by that specific user. The absence of meaningful rate limiting exacerbates this issue significantly. Without throttling mechanisms in place, an attacker can automate requests at high velocity, systematically iterating through the 10-digit numeric search space. This capability transforms a minor information leak into a scalable data harvesting tool, enabling the discovery of registered devices or users on a massive scale with minimal effort and detection risk.
From a standards perspective, this vulnerability aligns directly with CWE-204, which defines Responsive Discrepancy as an observable difference in response that allows for inference of internal state. It also relates to CWE-613, Insufficient Session Expiration, if the token remains valid during enumeration, and more critically CWE-770, Allocation of Resources Without Limits or Throttling, due to the lack of rate limiting. In terms of offensive security frameworks such as MITRE ATT&CK, this behavior facilitates the Reconnaissance phase, specifically under techniques like T1592 Gather Victim Host Information or T1589 Collect Client IP Addresses and Device IDs, depending on the specific data exposed. The ability to map valid identifiers effectively aids attackers in subsequent phases of an attack chain, such as targeted exploitation or credential stuffing against known active accounts.
The operational impact of this vulnerability is severe, particularly for systems managing sensitive IoT devices or user profiles. Successful enumeration allows adversaries to build a comprehensive database of active targets. This intelligence can be leveraged to prioritize attacks on high-value assets, bypass security controls that rely on obscurity, and conduct more efficient phishing or social engineering campaigns by confirming the existence of specific entities. The scalability enabled by the lack of rate limiting means that even low-severity individual requests accumulate into a critical systemic risk, potentially leading to significant data breaches or service disruption if combined with other exploitation techniques.
Mitigation strategies must address both the information leakage and the resource exhaustion aspects of this flaw. First, developers should ensure consistent error responses for all invalid inputs regardless of whether the underlying ID exists in the database. The application logic must abstract away existence checks from the public API response to prevent inference attacks. Second, robust rate limiting mechanisms must be implemented at the gateway or application level to restrict the number of requests a single token can make within a given time window. This limits the speed and volume of enumeration attempts. Additionally, implementing CAPTCHA challenges for suspicious activity patterns or requiring re-authentication after multiple failed lookups can further deter automated attacks. Regular security testing should include specific checks for timing side-channels and response code discrepancies to ensure these vulnerabilities do not persist in production environments.