CVE-2026-89314 in KeyPont
Summary
by MITRE • 10/23/2026
`jwkFields.CheckConsistency` detected duplicate `key_ops` entries with a pairwise nested loop, making validation cost grow with the **square** of the entry count. Because the check runs on every JWK and JWKS unmarshal, a modestly sized but hostile JWKS document could occupy a CPU core for many seconds.
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Analysis
by VulDB Data Team • 10/23/2026
The vulnerability described involves an inefficient algorithmic complexity issue within the JSON Web Key (JWK) parsing logic of a cryptographic library or framework. Specifically, the function responsible for validating JWK fields, identified as jwkFields.CheckConsistency, employs a pairwise nested loop to detect duplicate entries in the key_ops array. This implementation choice results in quadratic time complexity relative to the number of elements in the input data. While this approach may be acceptable for small datasets with minimal performance impact under normal conditions, it becomes critically problematic when processing untrusted or maliciously crafted inputs designed to exploit this inefficiency.
In practical terms, a moderately sized but hostile JWKS document can cause significant CPU consumption by triggering extensive computational work during the validation phase. Since JWK and JWKS parsing occurs frequently in applications handling cryptographic operations such as authentication, token verification, or key exchange protocols, an attacker could craft input that forces repeated execution of this inefficient check across multiple requests. This leads to a denial-of-service scenario where system resources are exhausted due to excessive CPU usage rather than memory exhaustion or network saturation typically associated with more common DoS attacks.
From a technical perspective, the root cause lies in poor algorithmic design for duplicate detection within arrays containing potentially large numbers of elements. A more efficient approach would involve using hash-based data structures such as sets or maps which allow constant-time lookups and insertions on average. By replacing the nested loop with a linear scan utilizing these optimized constructs, developers can reduce validation cost from O(n^2) to approximately O(n), thereby mitigating potential abuse scenarios effectively without compromising security guarantees.
This type of vulnerability aligns closely with CWE-400: Uncontrolled Resource Consumption and also relates indirectly to CWE-756: Missing or Incorrectly Implemented Canonicalization Rule if improper handling leads to bypassing intended validation logic through resource exhaustion tactics. Additionally, from an ATT&CK framework standpoint, this behavior could be classified under T1499: Endpoint Denial of Service since it involves leveraging software weaknesses to degrade service availability for legitimate users by consuming excessive computational resources during routine processing tasks involving cryptographic material parsing and verification processes commonly found in modern web services APIs backend systems dealing with identity providers or federated identities ecosystems.
To mitigate this risk, developers should refactor the duplicate checking mechanism into one that utilizes hash sets instead of nested loops ensuring consistent performance regardless input size variations while maintaining strict adherence to specification requirements regarding uniqueness constraints enforced upon key operation fields within JSON Web Key structures defined by RFC 7517 standards governing interoperability between different implementations dealing with public/private keys used across various cryptographic protocols including TLS JWT OAuth2 OIDC etcetera further strengthening overall resilience against adversarial attempts aimed at disrupting service continuity through targeted exploitation of known inefficiencies embedded deep inside core libraries handling sensitive security-related data transformations conversions validations checks before being utilized downstream throughout entire application stack layers spanning frontend clients middlewares gateways proxies load 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