Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-26145 is a high-severity OS Command Injection (CWE-78) vulnerability in Derrickgilland Pydash. Its CVSS base score is 7.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Junk Data (T1001.001); ranked in the top 11% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0214
Vulnerability Data
This affects versions of the package pydash before 6.0.0. A number of pydash methods such as pydash.objects.invoke() and pydash.collections.invoke_map() accept dotted paths (Deep Path Strings) to target a nested Python object, relative to the original source object. These paths can…
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be used to target internal class attributes and dict items, to retrieve, modify or invoke nested Python objects. **Note:** The pydash.objects.invoke() method is vulnerable to Command Injection when the following prerequisites are satisfied: 1) The source object (argument 1) is not a built-in object such as list/dict (otherwise, the __init__.__globals__ path is not accessible) 2) The attacker has control over argument 2 (the path string) and argument 3 (the argument to pass to the invoked method) The pydash.collections.invoke_map() method is also vulnerable, but is harder to exploit as the attacker does not have direct control over the argument to be passed to the invoked function.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.5V1.2.8V1.3.1
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.
Validates inputs to block special elements that would alter OS command execution.
Platform-independent apps typically execute inside a managed runtime or sandbox that restricts direct OS command execution, reducing the ability to exploit OS command injection.
Makes persistent code injection into loaded programs impossible when the executable image itself resides on hardware-protected read-only media.
Dynamically generated code can be produced and executed inside the isolated chamber, preventing host compromise from code-injection payloads.
Directly prevents execution of attacker-supplied code written into data memory regions.
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.
PR.PS-06's SDLC practices directly require secure coding and input handling that blocks command-injection defects, yet the single broad outcome leaves many specific neutralization vectors and verification gaps unaddressed.
Routine patching/maintenance can remediate known command-injection CVEs in dependencies (partial forward) but does nothing to stop developers from introducing improper neutralization in custom code (none reverse).
PR.DS-10 protects runtime data confidentiality/integrity but has no bearing on neutralizing externally influenced input during code generation, so neither direction shows any preventive effect.
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.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.
- No fine-grained STIG row for CWE-77, a class-level weakness, and none of its children carries one either.