Remote code execution via Pickle deserialization
Published Aug 29, 2022 · Updated Aug 3, 2024
Unsafe deserialization in NVIDIA FLARE before 2.1.4 allows remote attackers to execute code through a crafted federated-learning message. The server's fed_server.py message path passes attacker-controlled fl_context bytes to pickle.loads, which invokes payload-defined reduction functions during object reconstruction. A malicious connected client can run commands with the server process's privileges, read or alter its data, or crash the service.
Summary
What happened
Unsafe deserialization in NVIDIA FLARE before 2.1.4 allows remote attackers to execute code through a crafted federated-learning message. The server's fed_server.py message path passes attacker-controlled fl_context bytes to pickle.loads, which invokes payload-defined reduction functions during object reconstruction. A malicious connected client can run commands with the server process's privileges, read or alter its data, or crash the service.
The record
- CVE
- CVE-2022-34668
- Published
- Aug 29, 2022
- Updated
- Aug 3, 2024
- Vendor
- DPDK Project
- Product
- NVIDIA FLARE
- Classifications
- CWE-502, T1190
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Aug 29, 2022CVE publishedPublication date reported by the CVE source.
- Aug 3, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=All versions prior to 2.1.4
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
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
- NVFLARE before 2.1.4 unsafe Pickle deserialization exploitfunctional · demonstrated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
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Your stack
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