CVE-2026-81699 in openssl_encrypt
Summary
by MITRE • 08/27/2026
openssl_encrypt versions before 1.4.9 fail to properly validate key derivation function costs in crafted files, allowing attackers to trigger unbounded memory and CPU exhaustion during pre-authentication processing. Attackers can supply malicious files with excessive KDF parameters to exhaust system resources and crash or wedge the process before password verification occurs.
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Analysis
by VulDB Data Team • 08/27/2026
The vulnerability identified in openssl_encrypt versions prior to 1.4.9 represents a critical resource management failure within the cryptographic key derivation subsystem. This flaw stems from an insufficient validation mechanism for parameters governing Key Derivation Functions, specifically those related to computational cost and memory usage metrics such as iterations or parallelism factors. In secure implementations of password hashing algorithms like Argon2 or scrypt, these parameters are strictly bounded by configuration limits to ensure that the time and resources required to derive a key remain within acceptable thresholds for both legitimate users and system stability. However, in the affected versions, the software fails to enforce these upper bounds when processing user-supplied data structures containing KDF configurations. This oversight allows an attacker to craft malicious input files or network payloads that specify excessively high values for cost parameters, effectively bypassing the intended safeguards designed to prevent computational abuse.
From a technical perspective, this flaw constitutes a classic case of uncontrolled resource consumption during pre-authentication processing phases. When a system attempts to validate credentials using a KDF with artificially inflated costs, it initiates intensive memory allocation and CPU-intensive calculations before any actual password verification logic is executed. Because the validation occurs prior to authentication checks, the application must process these malicious parameters regardless of whether the user possesses valid credentials or not. This pre-authentication nature significantly amplifies the severity of the vulnerability, as it lowers the barrier for exploitation by allowing unauthenticated remote attackers to trigger the resource exhaustion directly through network requests or file uploads without needing any prior access privileges.
The operational impact of this vulnerability is severe, primarily manifesting as a Denial of Service condition against the hosting application and potentially the underlying infrastructure. By supplying crafted files with excessive KDF parameters, an attacker can cause unbounded memory allocation and CPU exhaustion on the server side. This resource depletion can lead to process crashes, system wedging, or complete service unavailability for legitimate users sharing the same resources. In cloud-native environments or shared hosting architectures, this could also result in collateral damage to other tenants or services running on the same host due to hypervisor-level resource contention triggered by the compromised application instance. The ability to wedge a process before password verification means that even high-traffic authentication endpoints are vulnerable to rapid degradation of service quality and availability.
This vulnerability aligns with CWE-787: Out-of-bounds Write in terms of memory exhaustion dynamics, although more accurately it maps to CWE-400: Uncontrolled Resource Consumption. The exploitation technique is consistent with ATT&CK tactic T1499: Endpoint Denial of Service, specifically under the sub-technique of resource exhaustion via application layer attacks. Security architects and developers should treat this as a high-severity issue requiring immediate remediation to maintain service availability integrity.
To mitigate this vulnerability, organizations must upgrade openssl_encrypt to version 1.4.9 or later where these validation checks have been properly implemented. In the interim, if upgrading is not immediately feasible, defensive measures such as implementing strict input validation at the application gateway level can help filter out requests with abnormally large KDF parameters before they reach the vulnerable library functions. Additionally, deploying rate limiting and resource quotas for authentication endpoints can reduce the blast radius of an attack by throttling excessive computational demands from single sources. Monitoring system metrics for sudden spikes in CPU or memory usage during login attempts may also provide early detection capabilities to identify ongoing exploitation attempts.