Apache Fory
Monthly
Memory disclosure and denial-of-service in Apache Fory's Rust deserialization path (versions 0.13.0 through 1.3.0) let remote attackers submit a crafted Fory-serialized payload that triggers a use-after-free, causing undefined behavior, process crashes, or leakage of adjacent process memory. The flaw affects any service that deserializes untrusted Fory data using the Rust implementation, and Apache has published a fixed release (1.4.0). There is no public exploit identified at time of analysis and EPSS exploitation probability is low (0.18%, 7th percentile), but the network-reachable, unauthenticated attack surface makes it a meaningful hardening priority for exposed services.
Remote code execution risk in Apache Fory (the Java serialization framework formerly known as Fury) before 1.4.0 arises because attacker-supplied data can bypass the class-registration allowlist during Java lambda deserialization, with the gap confined to the lambda capture class. Registration checks are Fory's core defense against untrusted-deserialization gadget attacks, so bypassing them for lambda payloads can let an attacker instantiate otherwise-disallowed classes and reach code execution or memory corruption. There is no public exploit identified at time of analysis and this CVE is not listed in CISA KEV; the vendor (Apache) rates it CVSS 9.8 and a fixed release (1.4.0) is available.
Insecure deserialization in Apache Fory's PyFory (Python) library allows remote attackers to bypass DeserializationPolicy validation hooks via the ReduceSerializer, letting untrusted classes, functions, or module attributes be restored despite policy restrictions. All PyFory releases before 1.0.0 are affected when running Python-native mode with strict mode disabled, enabling attacker-controlled data to instantiate unsafe objects and achieve code execution. There is no public exploit identified at time of analysis and EPSS probability is very low (0.04%), but CVSS is 9.8 and SSVC rates technical impact as total with automatable exploitation.
Memory disclosure and denial-of-service in Apache Fory's Rust deserialization path (versions 0.13.0 through 1.3.0) let remote attackers submit a crafted Fory-serialized payload that triggers a use-after-free, causing undefined behavior, process crashes, or leakage of adjacent process memory. The flaw affects any service that deserializes untrusted Fory data using the Rust implementation, and Apache has published a fixed release (1.4.0). There is no public exploit identified at time of analysis and EPSS exploitation probability is low (0.18%, 7th percentile), but the network-reachable, unauthenticated attack surface makes it a meaningful hardening priority for exposed services.
Remote code execution risk in Apache Fory (the Java serialization framework formerly known as Fury) before 1.4.0 arises because attacker-supplied data can bypass the class-registration allowlist during Java lambda deserialization, with the gap confined to the lambda capture class. Registration checks are Fory's core defense against untrusted-deserialization gadget attacks, so bypassing them for lambda payloads can let an attacker instantiate otherwise-disallowed classes and reach code execution or memory corruption. There is no public exploit identified at time of analysis and this CVE is not listed in CISA KEV; the vendor (Apache) rates it CVSS 9.8 and a fixed release (1.4.0) is available.
Insecure deserialization in Apache Fory's PyFory (Python) library allows remote attackers to bypass DeserializationPolicy validation hooks via the ReduceSerializer, letting untrusted classes, functions, or module attributes be restored despite policy restrictions. All PyFory releases before 1.0.0 are affected when running Python-native mode with strict mode disabled, enabling attacker-controlled data to instantiate unsafe objects and achieve code execution. There is no public exploit identified at time of analysis and EPSS probability is very low (0.04%), but CVSS is 9.8 and SSVC rates technical impact as total with automatable exploitation.