Remote code execution via pickled data packages
Published Jun 27, 2024 · Updated Sep 15, 2024
Unsafe deserialization in NLTK 3.8.1 and earlier allows remote attackers to execute code through downloaded data packages. The data package loader unpickles models such as averaged_perceptron_tagger and punkt without validating that their serialized Python objects are safe. Exploitation requires the integrated downloader to retrieve an attacker-controlled package and application code to invoke functionality that unpickles it.
Summary
What happened
Unsafe deserialization in NLTK 3.8.1 and earlier allows remote attackers to execute code through downloaded data packages. The data package loader unpickles models such as averaged_perceptron_tagger and punkt without validating that their serialized Python objects are safe. Exploitation requires the integrated downloader to retrieve an attacker-controlled package and application code to invoke functionality that unpickles it.
The record
- CVE
- CVE-2024-39705
- Published
- Jun 27, 2024
- Updated
- Sep 15, 2024
- Vendor
- NLTK Project
- Product
- NLTK
- Classifications
- CWE-502, T1195.002
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Jun 27, 2024CVE publishedPublication date reported by the CVE source.
- Sep 15, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
Compare your product and version with the public record. A matching version still requires validation against your environment.
Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=0 <=3.8.1
What conditions does exploitation require?
What is affected?
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
No public exploit references are available in this record.
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
See the directory against your own environment.
Your stack
Check the software in your environment
Book a demo to see how Hinoki identifies affected software and validates exploitability in your environment.
Book a demo