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NLTK: Quadratic-time CPU denial of service in Tree.chomsky_normal_form right-factor binarization via list.pop(0)

Tree.chomsky_normal_form() binarizes a parse tree and defaults to right factoring. For a node with N children the right-factor branch repeatedly removes the first element of a working list with list.pop(0), which shifts all remaining elements each time, so binarizing one wide node costs O(N^2). An application that converts an attacker-supplied treebank tree to Chomsky Normal Form can be forced into tens of seconds of single-threaded CPU by one wide flat …

NLTK: Quadratic-time CPU denial of service in ConllCorpusReader SRL instance builder via nested span rescan

ConllCorpusReader.srl_instances() builds semantic-role-labeling instances from a CoNLL corpus block. For a sentence block with P predicates and P span columns, the instance builder rescans every span column (and every span within it) once per predicate while searching for each predicate's head, giving O(P^2 * R) work. A single well-formed block that places the head span in the last column forces the full scan on every predicate, so an application that …

NLTK: Quadratic-time CPU denial of service in CCG lexicon parser (fromstring) on wide bracket bodies and operator chains

The public CCG lexicon parser nltk.ccg.lexicon.fromstring parses caller-influenced lexicon text with two pure-Python loops whose cost is quadratic in the input width. A service that parses an untrusted CCG lexicon string can be driven into tens of seconds of single-threaded CPU by a few-megabyte input, starving the request worker. No authentication or user interaction is required.

Tornado: Open redirect via triple-slash redirect paths

Due to differences in the way browsers and Python's urllib parse urls, browsers treat a string starting with three or more slashes as a protocol-level redirect, while urllib does not. This means that the 6.6.0 fix for the RedirectHandler open redirect (CVE-2026-116578, commit cc75ab0e) is incomplete. Tornado 6.6.1 improves the open-redirect detection to handle this case correctly, as well as fixing a regression in the 6.6.0 implementation.

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Two LiteLLM versions published containing credential harvesting malware

After an API Token exposure from an exploited trivy dependency, two new releases of litellm were uploaded to PyPI containing automatically activated malware, harvesting sensitive credentials and files, and exfiltrating to a remote API. Anyone who has installed and run the project should assume any credentials available to litellm environment may have been exposed, and revoke/rotate thema ccordingly.