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The vulnerability in Feast version 0.53.0 involves insecure YAML deserialization in the Kubernetes materializer job. In the file feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py, the code uses `yaml.load(…, Loader=yaml.Loader)` to parse configuration files `/var/feast/feature_store.yaml` and /var/feast/materialization_config.yaml. This loader allows arbitrary Python object instantiation during deserialization, as it does not restrict dangerous constructs. An attacker with write access to these YAML files can inject malicious payloads containing Python tags like !!python/object/apply:os.system. When deserialized, these payloads execute OS commands with the privileges of the worker pod. The deserialization occurs before any configuration validation, so the malicious code runs immediately. This enables remote code execution (RCE) on the pod, potentially compromising the entire Kubernetes cluster. Attackers can leverage this to escalate privileges, access sensitive data, poison feature stores, or sabotage supply chains. The vulnerability is exploitable remotely if YAML files are exposed via network services or through pod compromise. The use of `yaml.Loader` instead of `yaml.SafeLoader` is the root cause, making the system susceptible to deserialization attacks common in Python applications. This flaw highlights the importance of secure coding practices in cloud-native infrastructures.
Platform: Feast
Version: 0.53.0
Vulnerability: Deserialization Untrusted Data
Severity: High
date: 2026-01-01
Prediction: Patch 2026-01-09
What Undercode Say:
Analytics:
Malicious YAML payload example
!!python/object/apply:os.system [“id”]
Check vulnerable code
grep -r “yaml.Loader” feast/
Simulate exploit
python3 -c “import yaml; yaml.load(‘!!python/object/apply:os.system [\”touch /tmp/pwned\”]’, Loader=yaml.Loader)”
How Exploit:
Modify YAML files
Inject Python objects
Execute OS commands
Protection from this CVE:
Use yaml.SafeLoader
Validate configurations pre-deserialization
Restrict file permissions
Impact:
Cluster takeover
Data poisoning
Supply-chain sabotage
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Sources:
Reported By: github.com
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