CVE-2026-36590
An issue in EMQ NanoMQ v.0.24.9 allows a remote attacker to cause a denial of service via the nni_qos_db_set function in broker_tcp.c compon
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Exploit Today
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Publicado: 15 jul 2026 · Última mod.: 16 jul 2026 · CWE-400 · CWE-772
0.3%EPSS · 30 días0.4%
2026-07-162026-07-21
An issue in EMQ NanoMQ v.0.24.9 allows a remote attacker to cause a denial of service via the nni_qos_db_set function in broker_tcp.c component
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CVE-2026-564445.9 MED—
———In NLnet Labs Unbound 1.20.0 up to and including 1.25.1, when Unbound is configured with 'serve-expired: yes' and 'serve-expired-client-timeout > discard-timeout > 0' (contrary to the suggested values), the discard-timeout branch during the serve expired logic drops an aged client reply without performing the correct accounting for the number of reply addresses for the query. Other identical branches outside of serve expired perform the correct decrement. Since the counter is never decremented in such scenario, it can reach the maximum limit and new clients for duplicate in-flight queries are silently dropped resulting in degradation of resolution service. A malicious actor can exploit the vulnerability by querying the resolver for a client-controlled slow-on-demand authoritative zone that can drive the counter past the threshold. Shipped defaults for 'serve-expired-client-timeout: 1800' and 'discard-timeout: 1900' make the branch unreachable.9hCVE-2026-416373.7 BAJ—
———In NLnet Labs Unbound 1.22.0 up to and including 1.25.1, client terminated DNS-over-QUIC (DoQ) queries are not accounted properly by Unbound resulting in low-cost inflation of the waiting number of replies for already in-flight resolution queries. This results in degradation of resolution service for new clients for already in-flight queries. A malicious actor can exploit the vulnerability by issuing DoQ queries for query names that need resolution and proceeding on immediately terminating the query by one of STOP_SENDING/RESET_STREAM/CONNECTION_CLOSE QUIC frames. Those terminated DoQ queries are not properly counted for and keep inflating the number of waiting replies for in-flight queries. When the maximum is reached, it results in silent query drops for new clients needing resolution for already in-flight queries. This vulnerability needs Unbound to be compiled with DoQ support ('--with-libngtcp2') and the 'quic-port' to be configured for the listening interfaces. Additionally, a malicious actor needs access to multiple source IPs to bypass the by-default configured 'wait-limit' option.8hCVE-2026-45820——
———fflate through 0.8.2 is vulnerable to denial of service via an infinite loop in unzipSync(). A crafted ZIP archive with a central directory entry declaring compressed_size=0xFFFFFFFF (ZIP64 sentinel) but missing the required ZIP64 extra field tag 0x0001 causes z64e() to loop indefinitely due to out-of-bounds reads returning undefined, which coerces to 0, keeping the loop condition permanently true.9hCVE-2026-632636.5 MED—
——0Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Exponential Data Expansion (CAPEC-197). An authenticated user may submit a specially crafted query to the ES|QL engine that causes exponential CPU consumption during query evaluation. Because the resource exhaustion persists beyond query completion, repeated requests can fully exhaust the available query worker resources, rendering ES|QL queries unavailable until the node is restarted.9hCVE-2026-632616.5 MED—
——0Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailable to all users.8hCVE-2026-632606.5 MED—
——0Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated attacker with low-privilege access can trigger a denial of service condition in Kibana by sending a specially crafted, oversized request payload. Processing this user-supplied input requires resource-intensive memory allocation that can exhaust the available heap memory in the Kibana process, causing it to crash and become unavailable to all users.9h