CVE-2026-3644
Python ≤ 3.13.13
Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:H/VA:N/SC:N/SI:N/SA:N/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-2026-3644 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Python Python. Its CVSS base score is 6.0 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 34th 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 SI-15 (Information Output Filtering) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-12484
Vulnerability Data
The fix for CVE-2026-0672, which rejected control characters in http.cookies.Morsel, was incomplete. The Morsel.update(), |= operator, and unpickling paths were not patched, allowing control characters to bypass input validation. Additionally, BaseCookie.js_output() lacked the output validation applied to BaseCookie.output().
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Incomplete input validation bypass for control characters in http.cookies enables exploitation of public-facing Python web apps via malicious cookie values (CWE-20/116).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
- 6 hardening rules · 3 OS baselines
V1.1.2V1.2.1V1.2.3
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces validation of all input to Morsel (including update(), |=, and unpickling paths) to reject control characters as required by the incomplete fix for CVE-2026-0672.
Requires output filtering on BaseCookie.js_output() equivalent to that already present on BaseCookie.output(), blocking control-character injection in generated JavaScript.
Enables integrity verification of the http.cookies module and its cookie objects to detect tampering or bypasses that allow unvalidated control characters to persist.
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 SDLC practices directly require and enforce input validation during development.
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.
Secure coding standards explicitly require correct output encoding and escaping to preserve message structure.
Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.
Secure-coding guidelines and mandatory security testing (including code scans) compel developers to validate and sanitize inputs at design and implementation time, lowering the incidence of malformed or malicious data reaching downstream components.
Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.
Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.
Regular automated validation of system software and data content, combined with scanning of all inbound files, enforces input validation at the boundary before untrusted content is processed.