NLTK before 3.10.0 Insecure Default Configuration in pathsec.py
NLTK versions before 3.10.0 default to ENFORCE=False in pathsec.py, causing all security validation functions to emit warnings instead of raising exceptions. Attackers can bypass path traversal and pickle deserialization protections by exploiting the disabled security controls that are only active when manually enabled.
NLTK 3.9.4 Path Traversal via FrameNet and NKJP Readers
NLTK versions before 3.10.0 contain a path traversal vulnerability in FramenetCorpusReader and NKJPCorpusReader that allows attackers to parse XML files outside the corpus root by supplying unsafe selectors or poisoned index state. Attackers can exploit frame_by_name, doc, lu, and header methods with crafted parameters to read arbitrary XML files accessible to the application.
NLTK 3.9.4 through 3.10.2 Path Traversal via CrubadanCorpusReader pathsec Bypass
NLTK 3.9.4 through 3.10.2 contains a path traversal vulnerability in CrubadanCorpusReader. _load_lang_ngrams joins the corpus root with crubadan_code, the column-0 value read from the corpus table.txt mapping file, and opens the result with the builtin open() rather than the pathsec-validated opener, so os.path.join discards the root when that value is absolute and the read escapes the corpus directory without the containment check nltk.pathsec applies when ENFORCE is set. An attacker who controls a corpus package can disclose file contents outside the corpus root through lang_freq, limited to paths ending in -3grams.txt whose contents parse
NLTK TweetTokenizer URL Pattern Backtracks Catastrophically on Naked-Domain-Like Input
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 few kilobytes of input therefore consumes seconds to minutes of single-threaded CPU, and the HANG_RE substitution performed before matching does not
A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send
A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines
Natural Language Toolkit (NLTK): DNS-rebinding SSRF filter bypass in nltk.pathsec.urlopen (nltk.download / nltk.data.load) defeats ENFORCE mode
### Summary
`nltk.pathsec` provides an SSRF filter that NLTK documents as a security control, blocking loopback, private, link-local, and multicast ranges (including obfuscated forms) and recommending strict `ENFORCE` mode for security-sensitive environments. The filter is bypassable by DNS rebinding: `validate_network_url()` resolves the hostname and checks the resulting IP, but the actual HTTP connection re-resolves the hostname independently at connect time and connects to that second result. The validated IP is never the one connected to. An attacker controlling DNS for a hostname (a TTL-0 rebinding record) returns a public IP for the val
Средний · CVSS 5.3EPSS 0,1%Нет опубликованного исправления
Improper Input Validation in nltk/nltk
In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications.
NLTK: URL-Encoded Path Traversal in nltk.data.load() Allows Arbitrary Local File Read
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Prior to 3.10.0-rc1, nltk.data.load() in NLTK is vulnerable to path traversal via URL-encoded path separators and traversal segments when using the nltk: URL scheme. The unsafe-path regex check is performed before url2pathname() decodes the %xx sequences (a classic decode-after-check / TOCTOU-style flaw), allowing an attacker to bypass the protection documented in NLTK's SECURITY.md and read arbitrary files from the filesystem. While literal traversal strings such as ../../../et