CVE-2026-105782
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-105782 is a high-severity Unsafe Reflection (CWE-470) vulnerability. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Reflective Code Loading (T1620); ranked at the 30th 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 AC-3 (Access Enforcement) and AC-6 (Least Privilege) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-92869
Vulnerability Data
Scrapy is a high-level web crawling and scraping framework for Python. From 1.4.0 until 2.14.2, RefererMiddleware in scrapy/spidermiddlewares/referer.py treated a Referrer-Policy response-header value that resembled a Python import path as a referrer policy class, imported the referenced object, and called…
more
it. A malicious website could supply a callable such as sys.exit and terminate a crawler processing the response. This issue is fixed in version 2.14.2.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Enforces authorization checks on the code or classes ultimately invoked, blocking unauthorized selections even if reflection is used.
Limits privileges of any code reached through unsafe reflection, reducing blast radius without stopping the selection itself.
Input validation directly stops externally supplied class or method names from selecting improper code via reflection.
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.
Vulnerability identification processes can discover unsafe reflection during code review or scanning.
Preventing execution of unauthorized code can block exploitation of unsafe reflection at runtime.
Secure SDLC practices directly avoid introducing externally controlled class selection via reflection.
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.
A.8.25 mandates secure SDLC practices including secure coding guidelines, security requirements, checkpoints, testing (scans/penetration), and developer training that can catch/prevent unsafe reflection flaws during development; this stops exploitation for a minority slice (first-party code written under the process) but leaves the bulk of the weakness (e.g. in third-party libraries, legacy code, or incomplete enforcement) untouched.
Application security requirements can explicitly prohibit or constrain reflection based on untrusted input.
A.8.27 mandates security-by-design principles (e.g. distrust external input, least privilege, secure session control, data validation/sanitization, design reviews against attack patterns) that reach a slice of unsafe reflection cases but leave a bounded remainder (e.g. reflection in third-party libraries or dynamic class loading where principles are applied incompletely).
Secure coding standards directly forbid unsafe reflection and require whitelisting or static alternatives.