CVE-2026-102739
Description
A flaw was found in ESPectre. The analysis tools insecurely load dataset files with Python object deserialization enabled. An attacker can supply a specially crafted dataset file containing malicious serialized data, leading to arbitrary code execution when a user or developer processes the file.
Statement
This vulnerability is rated as Important severity because insecure object deserialization can lead to arbitrary code execution with the privileges of the local user, though exploitation requires tricking a victim into opening an untrusted file. ESPectre is not packaged or distributed within any Red Hat products, so enterprise deployments are not exposed by default. Any operational risk is restricted to developer environments where third-party analysis scripts are manually invoked against unverified external data files.
Mitigation
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.
--- CME Mitigation Guidance (2026-11-06) ---
Disclaimer: The following mitigation solutions are provided as a courtesy, pending the application of an official patch. This content was generated utilizing AI tools in conjunction with data from https://cmetaxonomy.org. Customers are advised to independently evaluate and test these temporary mitigations within their own infrastructure.
The highest-value action is to disable Python object deserialization and pickle loading across ESPectre dataset loaders and analysis scripts when opening NPZ files: upgrade to ESPectre 3.0.0-rc1+, which enforce allow_pickle=False and reject arrays with object data types by raising a ValueError, closing all 2 injection vectors (crafted NPZ dataset file, malicious pull-request dataset contribution). Until patched, this is a concern on Developer and maintainer environments running ESPectre analysis scripts against untrusted dataset files, so Do not process or inspect unverified external NPZ datasets or untrusted pull-request contributions with ESPectre analysis tools. As a compensating measure, Allow only explicitly safe array dtypes and reject arbitrary object dtypes upon input parsing and Deploy EDR agents to detect and terminate suspicious child processes or malicious payloads executed via pickled object instantiation. These controls limit blast radius and contain exploitation, but they do not fix the underlying insecure deserialization defect — apply the upstream patch to fully remediate.
Highest-impact CME: CME-1302 Deserialization Allowlist (Safe Loading) (high)
Understanding the Weakness (CWE)
Integrity
Technical Impact: Modify Application Data; Unexpected State
Attackers can modify unexpected objects or data that was assumed to be safe from modification. Deserialized data or code could be modified without using the provided accessor functions, or unexpected functions could be invoked.
Availability
Technical Impact: DoS: Resource Consumption (CPU)
If a function is making an assumption on when to terminate, based on a sentry in a string, it could easily never terminate.
Other
Technical Impact: Varies by Context
The consequences can vary widely, because it depends on which objects or methods are being deserialized, and how they are used. Making an assumption that the code in the deserialized object is valid is dangerous and can enable exploitation. One example is attackers using gadget chains to perform unauthorized actions, such as generating a shell.
Frequently Asked Questions
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