Python Package Enumeration - Detection Updates
Summary Tenable has updated the Python package enumeration plugins to reduce false positives and to better identify vulnerabilities when multiple packages are present on the scan target. Change Before this update, the Python package enumeration plugins did not attempt to associate detected packages with an RPM or DEB package managed by the Linux distribution. This would cause some packages to report vulnerabilities both based on a Linux distribution vendor’s advisory and a CVE advisory from the Python package maintainer. In addition, some Python packages present through symbolic links (“symlinks”) on a scan target’s filesystem would report as separate files, instead of a single actual file. Finally, some vulnerability plugins did not correctly report when multiple vulnerable Python packages were present on a scan target. After this update, these issues have been addressed. Vulnerable Python packages on Linux assets will be assessed to determine if they are managed by a Linux distribution’s package manager, and if so, will be marked as “Managed” and will not report a vulnerability, unless the Show potential false alarms setting is enabled for the scan. Vulnerable Python packages detected will be assessed to determine if they are files or symlinks, and only the actual file will be reported. However, if multiple actual files are present, vulnerability detection plugins will correctly report all instances. Impact Most customers will notice a reduction in the volume of Python package vulnerabilities reported. Some scan results may show an increase in detected vulnerabilities if multiple independent installs of a Python package are present on a scan target, but this is much less likely. Detection plugins 181215 Python Installed Packages (Windows) 164122 Python Installed Packages (Linux/UNIX) 186173 Apache Superset Installed (Linux / Unix) 196906 AI/LLM Software Report 171433 Apache Airflow Installed (Linux / Unix) 201192 Horovod Detection 198067 Intel Neural Compressor Library Detection 201189 Keras Detection 201190 NumPy Detection 205587 H2O Detection 205584 LangChain Detection 205585 LLama.cpp Python Bindings Detection 206880 MLflow Detection 205586 OpenAi Detection 214312 AWS RedShift Python Connector Detection 205590 Seaborn Detection 205589 Tensorboard Detection 205588 Theano Detection 237200 Tornado Detection 206027 ZenML Detection 200977 PyTorch Detection 201193 Ray Dashboard Detection 201191 Scikit-learn Detection 195192 TensorFlow Detection 195203 Microsoft Azure Command-Line Interface (CLI) Installed (Linux) 208299 DeepSpeed Detection 208127 AIM Detection 208134 BentoML Detection 208126 Google AI Platform (VertexAI SDK) Detection 213710 Gradio Detection 208129 H2O-3 Detection 208135 H2OGPT Detection 208137 Kedro Detection 241433 Model Context Protocol (MCP) Detection 208131 MLRun Detection 208132 Neptune AI SDK Detection 208140 Ollama Detection 208136 Prefect Detection 208139 PySpark Detection 208138 Microsoft RD-Agent Detection 208141 Tensorflow-hub Detection 208130 NVIDIA TensorRT Detection 208133 Weights & Biases Detection 208128 Weights & Biases Weave Detection Vulnerability plugins 210056 NumPy 1.9.x < 1.21.0 Buffer Overflow 210055 NumPy < 1.22.0 Vulnerability - CVE-2021-34141 210057 NumPy < 1.22.2 Null Pointer Dereference 210054 NumPy < 1.19 DoS 213084 Pandas DataFrame.query Code Injection (Unpatched) 211464 torchgeo Python Library < 0.6.1 RCE 192941 Dnspython < 2.6.0rc1 DoS 193912 aioHTTP < 3.9.4 XSS 211644 aioHTTP 3.10.6 < 3.10.11 Memory Leak 211645 aioHTTP < 3.10.11 Request Smuggling 206721 Jupyterlab Python Library < 3.6.8 / 4.0 < 4.2.5 (CVE-2024-43805) 206977 LangChain Experimental Python Library <= 0.0.14 (CVE-2023-44467) 206722 Jupyter Notebook Python Library 7.0.0 < 7.2.2 (CVE-2024-43805) 212710 Pdoc Python Library <= 14.5.1 (CVE-2024-38526) 187972 PyCryptodome < 3.19.1 Side Channel Leak 193202 PyMongo < 4.6.3 Out-of-bounds Read 213287 python-libarchive Python Library <= 4.2.1 Directory Traversal (CVE-2024-55587) 204790 Python Library Certifi < 2024.07.04 Untrusted Root Certificate 206676 Python Library Django 4.2.x < 4.2.16 / 5.0.x < 5.0.9 / 5.1.x < 5.1.1 Multiple Vulnerabilities 214945 Python Library Django 4.2.x < 4.2.18 / 5.0.x < 5.0.11 / 5.1.x < 5.1.5 DoS 237889 Python Library Django 4.2.x < 4.2.22 / 5.1.x < 5.1.10 / 5.2.x < 5.2.2 Log Injection 194476 SAP BTP Python Library sap-xssec < 4.1.0 Privilege Escalation 200807 urllib3 Python Library < 1.26.19, < 2.2.2 (CVE-2024-37891) 242322 aioHTTP < 3.12.14 Request Smuggling (CVE-2025-53643) 234572 Microsoft Azure Promptflow Python Library promptflow-core < 1.17.2 RCE 234573 Microsoft Azure Promptflow Python Library promptflow-tools < 1.6.0 RCE 241329 Python Library Pillow 11.2.x < 11.3.0 Write Buffer Overflow Target Release Date November 10, 2025Machine Learning SinFP Model Updates for OS Fingerprinting
Summary Updates have been released for the Tenable MLSinFP model, which predicts a host's OS based on SinFP fingerprints, by rebuilding it on a newer tech stack, incorporating new features, and using a larger dataset, resulting in improved accuracy of 67%. Change Before this update, plugin 132935 “OS Identification: SinFP with Machine Learning” was targeting operating systems commonly seen up to January 2021; consequently any newer OSs were not available as predictions. Additionally, the plugin solely relied on TCP header information for model features. After this update, the plugin targets operating systems commonly seen up to May 2025. Additionally the training dataset is larger (was 700K records, now 1.8M) and more varied (was 6K distinct SinFP fingerprints, now 100K), the predicted OSs names are cleaner and more consistent, and model features other than TCP header information are relied on. Ultimately these changes resulted in the plugin's balanced accuracy increasing to 67% (was 54%). Impact Remote detection of operating systems based on the MLSinFP method will have a slightly higher confidence score. Assets whose operating system was determined based on this method might have a different detected operating system. Plugins 132935 - OS Identification: SinFP with Machine Learning Target Release Date October 27, 2025Include/Exclude Path and Tenable Utils Unzip added to Log4j Detection
Summary Tenable has updated the Apache Log4j detection plugins. The Windows plugin will now honor the Include/Exclude Filepath configuration option. The Linux/UNIX plugin will now use the version of ‘unzip’ supplied with the Nessus Agent, when enabled in the Agent’s configuration, and correctly inspect the MANIFEST.MF and pom.properties files. Change Before this update, plugin 156000, Apache Log4j Installed (Linux / Unix), would fail to detect Log4j in specific scan scenarios. The plugin uses several inspection methods to determine if a JAR file is a copy of Log4j. During Nessus Agent scans, as well as scans with ‘localhost’ as a target, the plugin was not properly executing the unzip command to inspect META-INF/MANIFEST.MF and pom.properties files in the JAR archive. If this method was the only option that would result in a successful detection, the copy of Log4j would not be detected properly. In addition, the plugin had failed to launch the unzip binary supplied with the Agent when inspecting files in JAR archives. Note: The Nessus Agent can be configured to use find and unzip binaries that it provides, instead of those supplied by the asset’s operating system. See https://docs.tenable.com/vulnerability-management/Content/Scans/AdvancedSettings.htm#Agent_Performance_Options for more information. Also before this update, plugin 156001, Apache Log4j JAR Detection (Windows), would fail to honor the directories included or excluded for full-disk searches configured in the Windows Include Filepath and Windows Exclude Filepath directives in the Advanced Settings of a scan config. Note: Configuration of these options is described in https://docs.tenable.com/vulnerability-management/Content/Scans/AdvancedSettings.htm#Windows_filesearchOptions. After this update, plugin 156000 will use the Agent-supplied copy of unzip when configured to do so. If this option is not enabled in the scan config, the plugin will use the existing method to find and execute an archive utility supplied by the asset’s operating system. In either case, the plugin will properly inspect Log4j’s MANIFEST.MF and pom.properties files as a version source. Plugin 156001 already properly inspects these files. Also after this update, plugin 156001’s Powershell code will now honor directories included or excluded by the Filepath directives. Plugin 156000 already supported this feature. Impact When scanning Linux / UNIX assets via 'localhost' (i.e. scanning the scanner itself) or with the Nessus Agent, additional Log4j instances from MANIFEST.MF or pom.properties sources may be reported. For Linux Nessus Agents with "Use Tenable supplied binaries for find and unzip" enabled and "Agent CPU Resource Control - Scan Performance Mode" set to Low, plugin 156000 will now properly limit CPU usage during scans. As noted in the product documentation, “Note: Setting your process_priority preference value to low could cause longer running scans. You may need to increase your scan-window timeframe to account for this value.” Customers should be aware of this configuration setting and potential changes to the results provided in the Log4J detection results. When scanning Windows targets, Log4j JAR files stored in paths specified in the Windows Exclude Filepath configuration will no longer be detected. Log4j JAR files stored in paths or drives specified in the Windows Include Filepath configuration that had not been previously scanned will now be detected, assuming they can be assessed before the plugin’s configured timeout has been reached. Plugins 156000 - Apache Log4j Installed (Linux / Unix) 156001 - Apache Log4j JAR Detection (Windows) Target Release Date September 1, 2025Updates to Detection of Java on Unix/Linux Summary The Java...
Updates to Detection of Java on Unix/Linux Summary The Java Detection and Identification (Linux/Unix) plugin has been updated to provide detections while avoiding a reported vulnerability and potential privilege escalation. Change As a part of Tenable’s response to TNS-2023-21, a vulnerability reported by CrowdStrike researcher Patrick Romero, Nessus plugin 147817 has been updated. The plugin identifies the distribution and version of Java on Linux and Unix systems. The plugin uses a variety of methods to perform this detection. Previously, one of the methods used in some cases was to execute the java runtime binary with a -version argument and read the output. This method has been removed from the plugin, and replaced with different methods that provide equivalent detection. Impact Customers should notice no material difference in the operation or findings from this plugin. In weeks of testing, Tenable researchers have seen parity in detection between the previous and current methods. If customers feel detection has been affected by this change, please contact Tenable Customer Support. Plugin 147817 - Java Detection and Identification (Linux/Unix) Target Release Date June 26, 2023