9.9 CVE-2025-20286

 

A vulnerability in Amazon Web Services (AWS), Microsoft Azure, and Oracle Cloud Infrastructure (OCI) cloud deployments of Cisco Identity Services Engine (ISE) could allow an unauthenticated, remote attacker to access sensitive data, execute limited administrative operations, modify system configurations, or disrupt services within the impacted systems. This vulnerability exists because credentials are improperly generated when Cisco ISE is being deployed on cloud platforms, resulting in different Cisco ISE deployments sharing the same credentials. These credentials are shared across multiple Cisco ISE deployments as long as the software release and cloud platform are the same. An attacker could exploit this vulnerability by extracting the user credentials from Cisco ISE that is deployed in the cloud and then using them to access Cisco ISE that is deployed in other cloud environments through unsecured ports. A successful exploit could allow the attacker to access sensitive data, execute limited administrative operations, modify system configurations, or disrupt services within the impacted systems. Note: If the Primary Administration node is deployed in the cloud, then Cisco ISE is affected by this vulnerability. If the Primary Administration node is on-premises, then it is not affected.
https://nvd.nist.gov/vuln/detail/CVE-2025-20286

Categories

CWE-259 : Use of Hard-coded Password
The product contains a hard-coded password, which it uses for its own inbound authentication or for outbound communication to external components. This weakness can be detected using tools and techniques that require manual (human) analysis, such as penetration testing, threat modeling, and interactive tools that allow the tester to record and modify an active session. Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.) For outbound authentication: store passwords outside of the code in a strongly-protected, encrypted configuration file or database that is protected from access by all outsiders, including other local users on the same system. Properly protect the key (CWE-320). If you cannot use encryption to protect the file, then make sure that the permissions are as restrictive as possible. For inbound authentication: Rather than hard-code a default username and password for first time logins, utilize a "first login" mode that requires the user to enter a unique strong password. Perform access control checks and limit which entities can access the feature that requires the hard-coded password. For example, a feature might only be enabled through the system console instead of through a network connection. Distributed Control System (DCS) has hard-coded passwords for local shell access Telnet service for IoT feeder for dogs and cats has hard-coded password [REF-1288] Firmware for a WiFi router uses a hard-coded password for a BusyBox shell, allowing bypass of authentication through the UART port

References


 

CPE

cpe start end

REMEDIATION


EXPLOITS

Exploit-db.com

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No known exploits

POC Github

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Other Nist (github, ...)

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CAPEC

Common Attack Pattern Enumerations and Classifications

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No entry