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Local arbitrary code execution in Glances versions prior to 4.5.5 occurs when the daemon deserializes its version-check cache file via pickle.load() without integrity validation. An attacker with write access to the Glances user's XDG cache directory (~/.cache/glances/glances-version.db) can plant a malicious pickle that executes as the Glances process user - frequently root - on next startup. Publicly available exploit code exists in the GHSA advisory, but no public exploit identified at time of analysis as actively weaponized.
Unauthenticated remote code execution in OpenDJ Community Edition through 5.1.0 occurs when the JMX RMI connector deserializes attacker-controlled Java objects before authentication is performed. Any deployment with the JMX Connection Handler enabled (commonly turned on for monitoring integrations) is exposed to pre-auth RCE over TCP, as demonstrated against OpenDJ 4.4.15 on JDK 11 with Jackson 2.12.6.1. No public exploit identified at time of analysis, and the issue is not currently listed in CISA KEV.
Detection bypass in picklescan before 0.0.29 allows attackers to smuggle arbitrary code execution payloads through pickle files by abusing the idlelib.autocomplete.AutoComplete.get_entity function inside __reduce__ methods. Because picklescan does not flag this function as dangerous, malicious ML model files (e.g., PyTorch checkpoints) appear safe to scan but execute attacker commands the moment a victim calls pickle.load(). Publicly available exploit code exists in the GHSA advisory, but no public exploit identified at time of analysis in CISA KEV.
Detection bypass in picklescan versions 0.0.26 and earlier (fixed in 0.0.30) allows attackers to smuggle arbitrary code through malicious pickle files by abusing Python's built-in ensurepip._run_pip function, which the scanner failed to flag as dangerous. Organizations relying on picklescan to vet PyTorch models or other serialized Python objects will load the file as safe and trigger remote code execution upon pickle.load(). Publicly available exploit code exists via the GHSA advisory PoC, though no public exploit identified in active campaigns at time of analysis.
Arbitrary code execution in Picklescan before 0.0.33 occurs because the scanner fails to flag the numpy.f2py.crackfortran._eval_length gadget when used inside a pickle __reduce__ method, allowing crafted pickle files to be marked safe while still executing attacker-supplied Python on load. Workflows that rely on Picklescan to vet untrusted pickle or PyTorch model artifacts are exposed to supply-chain poisoning, and publicly available exploit code exists in the GHSA advisory.
Detection bypass in picklescan versions before 0.0.30 allows malicious pickle files to evade security scanning by using cProfile.runctx in __reduce__ methods, leading to arbitrary code execution when the file is loaded via pickle.load(). The flaw undermines the core purpose of picklescan as a defensive tool for ML model security and was reported by VulnCheck with a published proof-of-concept in the GitHub Security Advisory. No public exploit identified at time of analysis as a weaponized in-the-wild attack, but PoC code is published in the GHSA.
Detection bypass in picklescan before 0.0.30 allows attackers to smuggle arbitrary code execution payloads through pickle files by abusing idlelib.pyshell.ModifiedInterpreter.runcommand inside a __reduce__ method, which the scanner fails to flag as dangerous. Any victim who relies on picklescan to vet PyTorch models or other pickle artifacts and then calls pickle.load() will execute attacker-supplied commands. Publicly available exploit code exists (PoC published in the GHSA advisory), no CISA KEV listing, and the issue is fixed in version 0.0.30.
Detection bypass in picklescan before 0.0.28 allows attackers to smuggle arbitrary code through pickle files by abusing torch.utils._config_module.load_config inside __reduce__ methods, defeating the library's malicious-pickle scanning and enabling remote code execution when the file is later loaded. Publicly available exploit code exists (GHSA-vv6j-3g6g-2pvj includes a working PoC), and the flaw is significant for any ML pipeline that trusts picklescan to vet third-party PyTorch model files. No CISA KEV listing at time of analysis, so exploitation status is limited to public POC rather than confirmed in-the-wild use.
Unsafe deserialization in zhilink ADP Application Developer Platform 1.0.0 exposes the testConnection endpoint to remote exploitation by low-privilege authenticated users via manipulation of the jdbcUrl parameter. A public exploit has been published (linked via Feishu document) despite vendor non-response to coordinated disclosure. No public exploit identified at time of analysis meets the KEV threshold, but the combination of public PoC, network-accessible endpoint, and no patch raises operational risk - particularly for organizations running this Chinese low-code/RAD platform internally.
Unsafe pickle deserialization in picklescan before 1.0.1 allows unauthenticated remote attackers to create arbitrary zero-byte files on the server by crafting malicious pickle payloads that instantiate Python's standard-library logging.FileHandler class. This technique bypasses RCE-focused blocklists because it abuses legitimate standard library functionality rather than commonly blocked modules, making it a notable blocklist-evasion primitive. A publicly available proof-of-concept exploit exists; no public exploit identified at time of analysis for active KEV-confirmed exploitation, but the PoC demonstrates concrete filesystem impact including lock-file-based denial of service.
Local arbitrary code execution in Glances versions prior to 4.5.5 occurs when the daemon deserializes its version-check cache file via pickle.load() without integrity validation. An attacker with write access to the Glances user's XDG cache directory (~/.cache/glances/glances-version.db) can plant a malicious pickle that executes as the Glances process user - frequently root - on next startup. Publicly available exploit code exists in the GHSA advisory, but no public exploit identified at time of analysis as actively weaponized.
Unauthenticated remote code execution in OpenDJ Community Edition through 5.1.0 occurs when the JMX RMI connector deserializes attacker-controlled Java objects before authentication is performed. Any deployment with the JMX Connection Handler enabled (commonly turned on for monitoring integrations) is exposed to pre-auth RCE over TCP, as demonstrated against OpenDJ 4.4.15 on JDK 11 with Jackson 2.12.6.1. No public exploit identified at time of analysis, and the issue is not currently listed in CISA KEV.
Detection bypass in picklescan before 0.0.29 allows attackers to smuggle arbitrary code execution payloads through pickle files by abusing the idlelib.autocomplete.AutoComplete.get_entity function inside __reduce__ methods. Because picklescan does not flag this function as dangerous, malicious ML model files (e.g., PyTorch checkpoints) appear safe to scan but execute attacker commands the moment a victim calls pickle.load(). Publicly available exploit code exists in the GHSA advisory, but no public exploit identified at time of analysis in CISA KEV.
Detection bypass in picklescan versions 0.0.26 and earlier (fixed in 0.0.30) allows attackers to smuggle arbitrary code through malicious pickle files by abusing Python's built-in ensurepip._run_pip function, which the scanner failed to flag as dangerous. Organizations relying on picklescan to vet PyTorch models or other serialized Python objects will load the file as safe and trigger remote code execution upon pickle.load(). Publicly available exploit code exists via the GHSA advisory PoC, though no public exploit identified in active campaigns at time of analysis.
Arbitrary code execution in Picklescan before 0.0.33 occurs because the scanner fails to flag the numpy.f2py.crackfortran._eval_length gadget when used inside a pickle __reduce__ method, allowing crafted pickle files to be marked safe while still executing attacker-supplied Python on load. Workflows that rely on Picklescan to vet untrusted pickle or PyTorch model artifacts are exposed to supply-chain poisoning, and publicly available exploit code exists in the GHSA advisory.
Detection bypass in picklescan versions before 0.0.30 allows malicious pickle files to evade security scanning by using cProfile.runctx in __reduce__ methods, leading to arbitrary code execution when the file is loaded via pickle.load(). The flaw undermines the core purpose of picklescan as a defensive tool for ML model security and was reported by VulnCheck with a published proof-of-concept in the GitHub Security Advisory. No public exploit identified at time of analysis as a weaponized in-the-wild attack, but PoC code is published in the GHSA.
Detection bypass in picklescan before 0.0.30 allows attackers to smuggle arbitrary code execution payloads through pickle files by abusing idlelib.pyshell.ModifiedInterpreter.runcommand inside a __reduce__ method, which the scanner fails to flag as dangerous. Any victim who relies on picklescan to vet PyTorch models or other pickle artifacts and then calls pickle.load() will execute attacker-supplied commands. Publicly available exploit code exists (PoC published in the GHSA advisory), no CISA KEV listing, and the issue is fixed in version 0.0.30.
Detection bypass in picklescan before 0.0.28 allows attackers to smuggle arbitrary code through pickle files by abusing torch.utils._config_module.load_config inside __reduce__ methods, defeating the library's malicious-pickle scanning and enabling remote code execution when the file is later loaded. Publicly available exploit code exists (GHSA-vv6j-3g6g-2pvj includes a working PoC), and the flaw is significant for any ML pipeline that trusts picklescan to vet third-party PyTorch model files. No CISA KEV listing at time of analysis, so exploitation status is limited to public POC rather than confirmed in-the-wild use.
Unsafe deserialization in zhilink ADP Application Developer Platform 1.0.0 exposes the testConnection endpoint to remote exploitation by low-privilege authenticated users via manipulation of the jdbcUrl parameter. A public exploit has been published (linked via Feishu document) despite vendor non-response to coordinated disclosure. No public exploit identified at time of analysis meets the KEV threshold, but the combination of public PoC, network-accessible endpoint, and no patch raises operational risk - particularly for organizations running this Chinese low-code/RAD platform internally.
Unsafe pickle deserialization in picklescan before 1.0.1 allows unauthenticated remote attackers to create arbitrary zero-byte files on the server by crafting malicious pickle payloads that instantiate Python's standard-library logging.FileHandler class. This technique bypasses RCE-focused blocklists because it abuses legitimate standard library functionality rather than commonly blocked modules, making it a notable blocklist-evasion primitive. A publicly available proof-of-concept exploit exists; no public exploit identified at time of analysis for active KEV-confirmed exploitation, but the PoC demonstrates concrete filesystem impact including lock-file-based denial of service.