Inefficient Algorithmic Complexity

js-yaml is a JavaScript YAML parser and dumper. From 3.0.0 until 3.15.2, 4.3.2, and 5.4.1, maxTotalMergeKeys in lib/js-yaml/loader.js and lib/loader.js does not count empty mapping sources while processing the merge key <<. An attacker can alias a large sequence of empty mappings into many merge targets, causing O(N * K) processing while totalMergeKeys remains unchanged and the configured resource limit is never reached. A relatively small YAML document can therefore cause prolonged CPU consumption in applications that parse untrusted YAML, and merge processing is enabled by default on these release lines. In v3 & v4, merge is enabled by default so the severity score is higher. This issue is fixed in versions 3.15.2, 4.3.2, and 5.4.1.Show less

sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, sqlparse.format(sql, reindent=True) and sqlformat --reindent route attacker-controlled parenthesized tuple lists through ReindentFilter._get_offset() in sqlparse/filters/reindent.py, where _flatten_up_to_token() repeatedly rebuilds and joins the statement prefix. Thousands of offset calculations walk an expanding token tree, producing quadratic CPU consumption for inputs that remain below MAX_GROUPING_TOKENS and causing request delays, reduced throughput, or worker starvation. This issue is fixed in version 0.6.0.Show less

A flaw was found in openshift/oauth-server. The OAuth login and error page endpoints pass the unauthenticated Accept-Language header to golang.org/x/text/language.ParseAcceptLanguage() without input validation. A bypass of the CVE-2022-32149 mitigation exists: the upstream guard counts only '-' characters but the internal BCP 47 scanner aliases '_' to '-' after the guard check. An unauthenticated attacker can send a crafted Accept-Language header using '_' separators to trigger quadratic-time parsing, consuming excessive CPU and denying authentication to all cluster users.Show less

xmldom is a pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module. Prior to @xmldom/xmldom versions 0.8.15 and 0.9.12, and in xmldom versions 0.3.0 through 0.6.0, two independent quadratic paths can cause denial of service. In lib/sax.js, parseElementStartPart repeatedly rescans a malformed tag name to the next > during single-character recovery; in lib/dom.js, normalize() repeatedly removes and appends adjacent text nodes, causing quadratic reindexing and string rebuilding. The first path is reachable through default DOMParser.parseFromString() processing, while the second is also reachable through a direct normalize() call on a programmatically constructed DOM, and endDocument invokes that normalization after parsing. This issue is fixed in @xmldom/xmldom versions 0.8.15 and 0.9.12; no fixed version is available for xmldom.Show less

xmldom is a pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module. Prior to @xmldom/xmldom versions 0.8.15 and 0.9.12, and in xmldom version 0.6.0 and earlier, DOMHandler.startElement in lib/dom-parser.js inserts every parsed attribute through setAttributeNode, while NamedNodeMap.setNamedItem in lib/dom.js calls the linear getNamedItem or getNamedItemNS lookup for each insertion. A well-formed element with many distinct attributes therefore requires quadratic comparisons during DOMParser.parseFromString() and can stall a Node.js event loop before application validation. This issue is fixed in @xmldom/xmldom versions 0.8.15 and 0.9.12; no fixed version is available for xmldom.Show less

pypdf is a free and open-source pure-python PDF library. Prior to 6.15.0, an attacker can craft a PDF that causes long runtimes when the pypdf/_utils.py function read_until_whitespace reads a stream containing a long run of bytes without whitespace. The function repeatedly performs immutable bytes concatenation in a one-byte loop, causing quadratic processing cost for the long non-whitespace input. This issue is fixed in version 6.15.0.Show less

Inefficient Algorithmic Complexity vulnerability in ash-project ash_paper_trail allows a user who can submit a large array attribute to a paper-trailed create or update action to cause a denial of service through excessive CPU and memory use. With full-diff change tracking, AshPaperTrail.ChangeBuilders.FullDiff.ListChange pairs each prior array element against the new list by rebuilding the remaining-elements accumulator with acc ++ [tuple] on every step, copying the growing list each time, so the pairing scales cubically in the array length. Nothing bounds the length and the value comes straight from action input, so one request carrying a large accepted {:array, _} attribute forces tens of seconds of CPU and multi-gigabyte allocations. This issue affects ash_paper_trail: from 0.1.1 before 0.7.0.Show less

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.Show less

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.Show less

An algorithmic complexity flaw exists in libsoup's HTTP Range header processing that persists after the CVE-2025-32907 fix. CVE-2025-32907 addressed memory amplification when a client repeated the same range many times in a single Range header. Commit 9bb92f7a corrected merge correctness in soup_message_headers_get_ranges_internal() in libsoup/soup-message-headers.c, but the coalescing loop still removes merged ranges using g_array_remove_index() for each coalesced element. Because GArray is contiguous, each mid-array removal performs an O(N) memmove. When many identical satisfiable ranges are supplied (for example bytes=0-0 repeated thousands of times), the loop performs O(N²) work coalescing them into a single range. The vulnerable path is reachable server-side from handle_partial_get() in libsoup/server/http1/soup-server-message-io-http1.c when a SoupServer handler returns HTTP 200 with a non-empty body. No authentication is required. The number of ranges is bounded only by the maximum request header size (~100 KiB), allowing roughly 25,000 ranges per request. Reporter measurements on libsoup HEAD containing the CVE-2025-32907 fix show ~90 ms single-core CPU per such request at the wire maximum, blocking the server's event loop for that duration. This is a CPU exhaustion / availability issue only. No memory corruption or information disclosure occurs. Affected: libsoup versions containing the CVE-2025-32907 fix but not merge request !550. Fixed upstream: MR !550 merged 2026-08-20, replacing per-element removal with O(N) in-place compaction and rejecting Range headers requesting more than 200 ranges. Upstream report: https://gitlab.gnome.org/GNOME/libsoup/-/issues/538 Related: CVE-2025-32907Show less

icalendar is an RFC 5545 compatible parser and generator of iCalendar files for Python. From 7.1.0 until 7.1.3, the Component equality method in src/icalendar/cal/component.py compares nested subcomponents with two membership loops, and each membership test invokes the same method on child components, causing O(2^n) work relative to nesting depth. Component.from_ical accepts arbitrarily nested BEGIN:VEVENT blocks without a depth limit, so an attacker can submit a sub-kilobyte .ics file containing equal nested subtrees and trigger the cost when an application performs equality, inequality, membership, deduplication, test-assertion, round-trip, or normalization comparisons. Parsing alone does not trigger the issue, and comparisons that differ early short-circuit, but a few hundred bytes can pin a CPU core for minutes or indefinitely, causing denial of service in calendar sync or import endpoints, invite processing, and other comparison paths. This issue is fixed in version 7.1.3.Show less

In 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.Show less

Netty 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.Show less

Expat 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.Show less

sqlparse 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.Show less

sqlparse 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.Show less

Previously, resolving relative paths containing parent directory ('..') segments performed string conversions and buffer rewrites on each step, resulting in quadratic time complexity and high memory allocation overhead. Now, path resolution operates on a byte buffer using index-based backtracking for '..' segments, eliminating the quadratic time complexity and significantly reducing memory allocations.Show less

A flaw in Elasticsearch allows a low-privileged authenticated user who can index documents to submit a single small document containing a crafted user-supplied input. Processing one such document occupies a worker thread from a bounded pool for a disproportionate amount of time, degrading the availability of indexing operations on the affected node.Show less

Inefficient Algorithmic Complexity (CWE-407) in Kibana can lead to denial of service via Input Data Manipulation (CAPEC-153). A specially crafted, deeply nested expression submitted to a Kibana TSVB visualization is evaluated with a worst-case cost that grows disproportionately with the size of the input. Because the evaluation runs synchronously, a single request consumes the Kibana request-processing thread indefinitely, and Kibana stops responding to all further requests until the service is restarted.Show less

js-yaml is a JavaScript YAML parser and dumper. From 5.0.0 until 5.2.2, parsing a small YAML document can take exponential time when an application calls load() or loadAll() on untrusted input. In src/parser/parser.ts, readFlowCollection uses restoreState and calls parseNode a second time when a flow-sequence entry is recognized as a key: value pair. If the key is a nested flow sequence of the same shape, every level is parsed twice, causing O(2^n) work and allowing an input under 200 bytes to keep one CPU busy for minutes, block the Node.js event loop, and stall the process. No anchors, aliases, merges, tags, or nondefault options are required. This issue is fixed in version 5.2.2.Show less