CVE-2026-76717 in Analytics and Location Engine
Summary
by MITRE • 09/22/2026
A vulnerability exists in the Analytics and Location Engine (ALE) API that may allow for the disclosure of sensitive information. An unauthenticated remote attacker could exploit this vulnerability by providing specially crafted input to a specific API endpoint. Successful exploitation could result in the disclosure of sensitive user information, including password hashes, which could be used to facilitate further attacks.
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Analysis
by VulDB Data Team • 09/22/2026
The identified security flaw resides within the Analytics and Location Engine API, specifically affecting an endpoint that processes unauthenticated requests with insufficient input validation or access control mechanisms. This vulnerability allows a remote attacker who does not possess valid credentials to interact directly with the backend services responsible for aggregating user analytics and location data. The core technical issue stems from a failure in implementing proper authorization checks before processing sensitive queries, effectively exposing internal application logic and underlying database structures to external actors. By crafting specific HTTP requests that target this endpoint, an attacker can bypass standard authentication gates, leveraging the API's design oversight to extract data that should be restricted to authorized administrative or analytical processes only.
The operational impact of exploiting this vulnerability is severe due to the nature of the exposed data. Successful exploitation results in the disclosure of sensitive user information, most critically including password hashes stored within the system. The exposure of these cryptographic artifacts provides attackers with a significant advantage in offline attack scenarios. Since password hashes are designed to be computationally expensive to reverse but easily verifiable against known plaintexts or rainbow tables, their availability enables brute-force and dictionary attacks without triggering account lockout mechanisms typically associated with online login attempts. This capability significantly lowers the barrier for credential compromise, allowing attackers to recover plain-text passwords if weak hashing algorithms were used or if users have employed common password patterns.
From a threat modeling perspective, this vulnerability aligns closely with CWE-209, which describes the generation of an error message that includes sensitive information about the software, the host computer, or the network, although in this specific case it extends beyond mere error messages to direct data exfiltration via API endpoints. It also maps directly to CWE-862, representing a missing authorization check where access control is not enforced for critical resources. In terms of offensive security frameworks such as MITRE ATT&CK, this behavior corresponds to T1078, Valid Accounts, although exploited here without valid initial credentials by bypassing the authentication layer entirely, and potentially feeds into T1552, Unsecured Credentials, where gathered hashes are used for lateral movement or privilege escalation. The disclosure of location data further exacerbates privacy risks, potentially enabling physical surveillance or targeted social engineering attacks based on user habits and geographic patterns.
To mitigate this vulnerability, immediate remediation efforts must focus on implementing robust access control policies at the API gateway level. All endpoints within the Analytics and Location Engine that handle sensitive personal identifiable information (PII) or authentication-related data must require valid session tokens or OAuth2 bearer tokens before processing any request. Input validation should be strictly enforced to ensure that parameters conform to expected formats, preventing injection-based attacks that might exacerbate the exposure. Additionally, developers should review the hashing algorithms used for password storage; migrating from deprecated hashes like MD5 or SHA1 to modern standards such as bcrypt, scrypt, or Argon2 will significantly increase the computational cost required to crack any potentially exposed hashes. Regular security audits and penetration testing of API endpoints are essential to identify similar misconfigurations before they can be exploited in production environments.