CVE-2026-24715 in QuRouter
Summary
by MITRE • 10/15/2026
An observable timing discrepancy vulnerability has been reported to affect QuRouter. If exploited, the vulnerability could allow remote attackers to obtain sensitive data.
We have already fixed the vulnerability in the following version: QuRouter 2.7.2.113 and later
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Analysis
by VulDB Data Team • 10/15/2026
The disclosed security issue within QuRouter represents a classic side-channel attack vector known as an observable timing discrepancy, which falls under the broader category of Timing Attacks. This type of vulnerability exploits the fact that cryptographic operations or authentication checks often take varying amounts of time to complete depending on the input data provided by the user. In many secure implementations, systems are designed to perform constant-time comparisons for sensitive values such as passwords, session tokens, or API keys to prevent attackers from deducing information based on how long a comparison takes. When this optimization is absent or implemented incorrectly, an attacker can send multiple requests with slightly different inputs and measure the response time of the server. By analyzing these minute differences in latency, it becomes possible to iteratively determine correct characters of secret data one by one until the full value is reconstructed. This method allows remote attackers to bypass authentication mechanisms or extract sensitive configuration details without needing direct access to memory dumps or database contents, effectively turning a performance characteristic into an information leak channel.
From a technical perspective, this flaw likely resides in how QuRouter handles credential verification or token validation routines. If the software uses standard string comparison functions that short-circuit upon finding the first mismatched character rather than comparing all characters regardless of position, it creates a measurable time differential between correct and incorrect guesses at each byte or character position. For instance, if an attacker sends a request with one correctly guessed character followed by random data, the server will process slightly longer before rejecting the input compared to a completely wrong guess because more comparisons succeed before failure occurs. Over hundreds or thousands of requests, this statistical advantage allows for high-precision reconstruction of secrets such as administrative passwords, encryption keys, or session identifiers. The vulnerability is particularly dangerous in network-facing applications like routers where remote exploitation does not require physical access or prior authentication privileges beyond what is needed to initiate a connection and send HTTP or protocol-specific requests.
The operational impact of this timing discrepancy extends significantly beyond simple unauthorized access. If an attacker successfully extracts sensitive data through these side-channel observations, they may gain full control over the router’s configuration interface. This could lead to comprehensive network compromise including interception of traffic via man-in-the-middle attacks, redirection of users to malicious sites for phishing or malware distribution, and disruption of critical network services by altering routing tables or firewall rules. Furthermore, compromised routers often serve as entry points into internal corporate networks, allowing lateral movement to more valuable assets such as databases, file servers, or industrial control systems. The stealthy nature of timing attacks also means that traditional intrusion detection systems may not immediately flag the activity as malicious since the requests appear normal from a protocol standpoint, making early detection difficult without specialized behavioral analysis tools capable of measuring microsecond-level response variations.
To mitigate this vulnerability and prevent similar side-channel exploits in future developments, it is imperative to implement constant-time comparison algorithms for all sensitive data comparisons including passwords, hashes, MACs, and cryptographic keys. Developers should utilize established libraries that guarantee execution time independence from input values rather than relying on standard language-specific string equality operators which often optimize away timing variations at the cost of security. Additionally, introducing random delays or jitter into authentication responses can help obscure any remaining timing signals although this is generally considered a secondary defense compared to algorithmic fixes. Organizations running affected versions must upgrade immediately to QuRouter version 2.7.2.113 or later where these implementation flaws have been corrected. Network administrators should also consider implementing rate limiting on login endpoints and monitoring for anomalous patterns in request timing that might indicate active exploitation attempts while ensuring that all software dependencies are kept up-to-date with security patches aligned with industry standards such as CWE-208 which specifically addresses observable timing discrepancies and ATT&CK technique T1539 related to Steal Web Session Cookie.