CVE-2026-106440
Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/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-2026-106440 is a high-severity Unsafe Reflection (CWE-470) vulnerability. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Reflective Code Loading (T1620); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-93661
Vulnerability Data
Hydra is a framework for elegantly configuring complex applications. From 1.2.0 until 1.3.0 and 1.4.0.dev10, the hydra-optuna-sweeper package accepts a configuration-controlled dotted path in hydra.sweeper.custom_search_space, resolves it with hydra.utils.get_method(), and later invokes the returned callable in the Hydra controller process.…
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Because get_method() is a trusted-input lookup helper and does not apply the execution policy used by instantiate(), an attacker who controls Optuna sweep configuration or command-line overrides can select importable Python code for execution with the application's privileges, including bypassing a trusted execution whitelist on affected Hydra 1.4 development releases. This issue is fixed in versions 1.3.0 and 1.4.0.dev10.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Externally controlled class or code selection can be resolved and invoked inside the chamber, surfacing unsafe reflection without system impact.
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.