Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/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-2023-44392 is a high-severity Code Injection (CWE-94) vulnerability in Garden Garden. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Junk Data (T1001.001); ranked in the top 46% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
Garden is an automation tool for Kubernetes development and testing that depends on the cryo library for object serialization. Prior to versions 0.13.17 and 0.12.65, Garden cached test and run results by storing cryo-serialized objects inside Kubernetes ConfigMaps whose names are prefixed with test-result or run-result; these resources reside in either the garden-system namespace or a user-specified namespace. The vulnerability stems from cryo’s insecure deserialization implementation, which permits code injection and is tracked under CWE-94 and CWE-502.
An attacker who already possesses access to the target Kubernetes cluster can place malicious serialized objects into the relevant ConfigMaps. When a legitimate user later executes the garden test or garden run command against a previously cached result, Garden retrieves and deserializes the object, triggering remote code execution on the user’s workstation. Exploitation therefore requires both cluster-level write access to the ConfigMaps and an active user invocation of one of the two affected commands.
The GitHub Security Advisory GHSA-hm75-6vc9-8rpr and the associated commits confirm that the flaw is resolved in Garden 0.13.17 (Bonsai) and 0.12.65 (Acorn); no workarounds are documented. The EPSS score remains flat at 0.0733 with no material increase after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-48738
Vulnerability Data
Garden provides automation for Kubernetes development and testing. Prior tov ersions 0.13.17 and 0.12.65, Garden has a dependency on the cryo library, which is vulnerable to code injection due to an insecure implementation of deserialization. Garden stores serialized objects using…
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cryo in the Kubernetes `ConfigMap` resources prefixed with `test-result` and `run-result` to cache Garden test and run results. These `ConfigMaps` are stored either in the `garden-system` namespace or the configured user namespace. When a user invokes the command `garden test` or `garden run` objects stored in the `ConfigMap` are retrieved and deserialized. This can be used by an attacker with access to the Kubernetes cluster to store malicious objects in the `ConfigMap`, which can trigger a remote code execution on the users machine when cryo deserializes the object. In order to exploit this vulnerability, an attacker must have access to the Kubernetes cluster used to deploy garden remote environments. Further, a user must actively invoke either a `garden test` or `garden run` which has previously cached results. The issue has been patched in Garden versions `0.13.17` (Bonsai) and `0.12.65` (Acorn). Only Garden versions prior to these are vulnerable. No known workarounds are available.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.1
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.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates inputs used in dynamic code generation to block injected directives.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Makes persistent code injection into loaded programs impossible when the executable image itself resides on hardware-protected read-only media.
Directly prevents execution of attacker-supplied code written into data memory regions.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
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 target injection flaws via secure coding and testing (mostly), yet as a single broad outcome it leaves many code-generation specifics unaddressed (partial).
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.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
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.