CVE-2026-81722
nltk PorterStemmer in versions <= 3.10.2 (fixed in 3.10.3) contains an inefficient-algorithmic-complexity denial of service in PorterStemmer
CVSS
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0-100
Publicado: 27 ago 2026 · Última mod.: 27 ago 2026 · CWE-407
Sin historial EPSS suficiente todavía.
nltk PorterStemmer in versions <= 3.10.2 (fixed in 3.10.3) contains an inefficient-algorithmic-complexity denial of service in PorterStemmer.stem(). The _is_consonant() helper walks backward over the entire run of trailing 'y' characters on every call, and _measure() invokes it for each stem position, causing O(n^2) behavior. A single ~20-50 KB untrusted token consisting of a long run of the letter 'y' followed by a matching suffix (e.g., 'ness') can pin a CPU core for seconds to minutes, causing availability impact.
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CVE-2026-75005——
———Inefficient Algorithmic Complexity vulnerability in Apache APISIX.
A single small request can pin a gateway worker at 100% CPU for an extended period in graphql-limit-count routes.
This issue affects Apache APISIX: 3.17.0.
Users are recommended to upgrade to version 3.18.0, which fixes the issue.13hCVE-2026-764015.9 MED20.5%
——6In Splunk Connect for Kafka versions below 2.2.7, an unauthenticated user who can reach the Kafka Connect Representational State Transfer (REST) API could configure timestamp extraction with a crafted regular expression and matching event data to block a Kafka Connect worker thread, stopping event delivery for the affected connector. The vulnerability is possible because timestamp extraction evaluates customer-supplied regular expressions without a time limit. For more information see Install Splunk Connect for Kafka (https://help.splunk.com/en/data-management/integrate-data-with-add-ons/splunk-connect-for-kafka/2.2/install/install-splunk-connect-for-kafka) and Data ingestion parameters for Splunk Connect for Kafka (https://help.splunk.com/en/data-management/integrate-data-with-add-ons/splunk-connect-for-kafka/2.2/overview/data-ingestion-parameters-for-splunk-connect-for-kafka) in the Splunk documentation.3dCVE-2026-75596—27.8%
——8Netty is an asynchronous, event-driven network application framework. Prior to 4.1.137.Final and 4.2.17.Final, the default io.netty.handler.ssl.SniHandler constructors use the pre-handshake ClientHello aggregation path in handler/src/main/java/io/netty/handler/ssl/SslClientHelloHandler.java at io.netty.handler.ssl.SslClientHelloHandler#decode, where handshakeBuffer.clear() and writeBytes() recopy all previously received body bytes for every additional TLS record. An unauthenticated remote peer can advertise a large ClientHello and deliver its body in thousands of tiny records, causing quadratic CPU work on the event loop before the TLS handshake completes and degrading TLS handling for other clients. This issue is fixed in versions 4.1.137.Final and 4.2.17.Final.7dCVE-2026-660467.5 ALT32.0%
——10Expat through 2.8.3 contains a denial of service vulnerability caused by quadratic algorithmic complexity in the storeAtts() function in xmlparse.c, where processing N specified attributes with non-normalized values triggers an O(N^2) linear scan of elementType->defaultAtts to determine CDATA status. A remote unauthenticated attacker can supply a single well-formed XML document of a few megabytes to an application parsing untrusted XML to cause excessive CPU consumption, resulting in denial of service without requiring authentication, external entity resolution, or non-default parser options.7dCVE-2026-71491—17.8%
——5sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, group_comments in sqlparse/engine/grouping.py repeatedly rescans comment-only statements before the MAX_GROUPING_TOKENS guard, causing quadratic CPU consumption through sqlparse.parse() and sqlparse.format(sql, strip_comments=True). This issue is fixed in version 0.6.0.10dCVE-2026-54284—17.8%
——5sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.10d