CVE-2026-80206 in NLTK
Summary
by MITRE • 08/26/2026
NLTK before 3.10.3 contains a regular expression denial of service (ReDoS) vulnerability in the tgrep module. The _tgrep_node_action function compiles user-supplied regular expressions embedded in /regex/ pattern nodes and executes them via re.search against tree node labels without any validation or timeout. An attacker who controls the tgrep pattern (e.g., via tgrep_positions() or tgrep_compile() exposed to external input) can supply a pattern that triggers catastrophic backtracking, causing indefinite CPU saturation that blocks the Python process.
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Analysis
by VulDB Data Team • 08/26/2026
The vulnerability identified in Natural Language Toolkit versions prior to 3.10.3 represents a significant regular expression denial of service risk within its tgrep module. This security flaw stems from the improper handling of user-supplied input during pattern matching operations, specifically affecting how regex patterns are processed against tree node labels. The core technical issue resides in the _tgrep_node_action function, which is responsible for compiling and executing regular expressions derived from /regex/ pattern nodes. When this function receives a pattern string that contains specific structural characteristics known to cause catastrophic backtracking, it initiates an exponential time complexity execution path during the search operation. Because there are no input validation mechanisms or timeout controls in place, the Python interpreter becomes trapped in an infinite loop of state transitions within the regex engine, leading to complete CPU saturation and effectively blocking the application process indefinitely.
From a technical perspective, this vulnerability is classified under CWE-400, which covers uncontrolled resource consumption, specifically manifesting as a regular expression denial of service or ReDoS attack. The mechanism relies on poorly constructed regular expressions that exploit ambiguities in backtracking algorithms used by standard regex engines like Python's re module. An attacker who has the ability to inject or control the tgrep pattern can craft input strings designed to trigger these worst-case scenarios for the matching algorithm. This typically involves patterns with nested quantifiers or ambiguous alternations that force the engine to explore an exponential number of possible matches before determining failure. The lack of a timeout mechanism means there is no automated safeguard to abort the operation after a reasonable duration, allowing the attack to persist until manual intervention or system resource exhaustion occurs.
The operational impact of this vulnerability is severe for any application relying on NLTK's tgrep functionality with untrusted input. Since the Python process becomes blocked by CPU saturation, it cannot serve legitimate requests, leading to a denial of service condition. In web applications or API services that expose functions like tgrep_positions() or tgrep_compile() directly to external users without sanitization, this vulnerability can be exploited remotely. The attacker does not need elevated privileges; they only need the ability to submit malicious pattern strings. This results in resource exhaustion for the hosting environment, potentially affecting other processes sharing the same system resources and degrading overall service availability.
Mitigation strategies must focus on both immediate patching and long-term defensive coding practices. The primary remediation is to upgrade NLTK to version 3.10.3 or later, where this vulnerability has been addressed by implementing safeguards against catastrophic backtracking. For environments unable to update immediately, developers should implement strict input validation for any tgrep patterns received from external sources. This includes restricting the allowed characters and structure of regex strings to exclude known problematic constructs such as nested quantifiers. Additionally, integrating a timeout mechanism around regex execution can prevent indefinite blocking by terminating operations that exceed a predefined time threshold. Adhering to secure coding guidelines outlined in OWASP resources for input validation is also recommended to reduce exposure to similar ReDoS vulnerabilities across the application stack.