CVE-2025-66471
Python Urllib3 1.0 – 2.6.0
Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-66471 is a high-severity Data Amplification (CWE-409) vulnerability in Python Urllib3. Its CVSS base score is 8.9 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 50th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SC-5 (Denial-of-service Protection) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-201419
Vulnerability Data
urllib3 is a user-friendly HTTP client library for Python. Starting in version 1.0 and prior to 2.6.0, the Streaming API improperly handles highly compressed data. urllib3's streaming API is designed for the efficient handling of large HTTP responses by reading…
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the content in chunks, rather than loading the entire response body into memory at once. When streaming a compressed response, urllib3 can perform decoding or decompression based on the HTTP Content-Encoding header (e.g., gzip, deflate, br, or zstd). The library must read compressed data from the network and decompress it until the requested chunk size is met. Any resulting decompressed data that exceeds the requested amount is held in an internal buffer for the next read operation. The decompression logic could cause urllib3 to fully decode a small amount of highly compressed data in a single operation. This can result in excessive resource consumption (high CPU usage and massive memory allocation for the decompressed data.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Input validation can reject or limit decompression of data whose expansion ratio exceeds safe thresholds.
DoS protection limits the resource-exhaustion impact when a decompression bomb is processed.
Resource allocation controls bound memory/CPU consumption that a data-amplification attack would otherwise exhaust.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure-development practices include input-validation and resource-limit checks that prevent improper handling of compressed data.
Runtime monitoring of compute resources can detect exhaustion caused by decompression bombs.
Capacity planning and monitoring directly limits the availability impact of data-amplification attacks.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can uncover decompression-bomb vulnerabilities before release.
Redundancy helps availability but does not address the root cause of the weakness.
Monitoring can detect anomalous resource usage but does not prevent the weakness.
Secure development lifecycle includes input validation and resource-limit checks that mitigate data-amplification attacks.
Application security requirements can mandate limits on decompression size and ratio.
Secure architecture principles encourage defensive design against resource-exhaustion threats.