Digital Marketing Pro

NLTK: Quadratic CPU Exhaustion in `XMLCorpusView._read_xml_fragment()`

## Summary `XMLCorpusView._read_xml_fragment()` reads a corpus file in 1 KiB blocks, appending each block to a growing `fragment` string, then calls `_VALID_XML_RE.match(fragment)` on the full accumulated buffer every iteration. Because each iteration rescans the entire accumulated fragment, the total amount of work grows quadratically with input size. Commit `c9c332284` (CWE-1333) made each `match()` call linear. The quadratic behavior is separate: the loop calls `match()` once per 1 KiB bloc

NLTK: Uncontrolled resource consumption in RecursiveDescentParser via ambiguous or left-recursive grammars

`nltk.parse.RecursiveDescentParser` (and `SteppingRecursiveDescentParser`) enumerate parses top-down with no bound on the number of recursive steps. A small, crafted context-free grammar makes a short input consume unbounded CPU (and/or exhaust the Python recursion stack), pinning a process indefinitely — a denial of service. ## Proof of concept Both of the following hang on a 24-token input (killed after 8s; growth is super-linear in input length), on NLTK develop: ```python from nltk import

NLTK: Uncontrolled search path when invoking the Graphviz 'dot' binary

Two NLTK sites executed the Graphviz `dot` program by bare name, so process creation resolved it via the search path — and on Windows via the current working directory — rather than a validated absolute location. An attacker who can place a file named `dot` where resolution looks (the CWD on Windows, or a writable/relative entry such as `.` on `PATH`) has their binary executed in place of Graphviz (arbitrary code execution). Affected (<= 3.10.2): - `nltk.parse.dependencygraph.dot2img` — called

NLTK AllowlistUnpickler dotted-name validation bypass allows remote code execution

NLTK before 3.10.3 contains a remote code execution vulnerability in AllowlistUnpickler that validates only the pickle module string and not the global name, allowing attackers to resolve dotted names by attribute traversal to callables outside the allowlisted namespace. Attackers can craft untrusted transition-parser models that execute arbitrary commands when TransitionParser.parse loads the model through allowlisted_pickle_load.

NLTK TweetTokenizer vulnerable to denial of service through catastrophic regex backtracking

The URLS regular expression in nltk/tokenize/casual.py, compiled into TweetTokenizer.WORD_RE and applied by TweetTokenizer.tokenize, contains a naked-domain branch whose domain-label prefix [a-z0-9]+(?:[.\-][a-z0-9]+)* is unbounded. Input consisting of many alternating label separators can be partitioned in exponentially many ways, and because the branch also requires a trailing top-level domain that such input never supplies, the engine explores those partitions before failing at each offset. A