In XWiki Platform 7.2 through 11.10.2, registered users without scripting/programming permissions are able to execute python/groovy scripts while editing personal dashboards. This has been fixed 11.3.7 , 11.10.3 and 12.0.

Deserialization of Untrusted Data in Plex Media Server on Windows allows a remote, authenticated attacker to execute arbitrary Python code.

Apport reads and writes information on a crashed process to /proc/pid with elevated privileges. Apport then determines which user the crashed process belongs to by reading /proc/pid through get_pid_info() in data/apport. An unprivileged user could exploit this to read information about a privileged running process by exploiting PID recycling. This information could then be used to obtain ASLR offsets for a process with an existing memory corruption vulnerability. The initial fix introduced regressions in the Python Apport library due to a missing argument in Report.add_proc_environ in apport/report.py. It also caused an autopkgtest failure when reading /proc/pid and with Python 2 compatibility by reading /proc maps. The initial and subsequent regression fixes are in 2.20.11-0ubuntu16, 2.20.11-0ubuntu8.6, 2.20.9-0ubuntu7.12, 2.20.1-0ubuntu2.22 and 2.14.1-0ubuntu3.29+esm3.

Improper Input Validation in Plex Media Server on Windows allows a local, unauthenticated attacker to execute arbitrary Python code with SYSTEM privileges.

python-markdown2 through 2.3.8 allows XSS because element names are mishandled unless a \w+ match succeeds. For example, an attack might use elementname@ or elementname- with an onclick attribute.

Python-apt doesn't check if hashes are signed in `Version.fetch_binary()` and `Version.fetch_source()` of apt/package.py or in `_fetch_archives()` of apt/cache.py in version 1.9.3ubuntu2 and earlier. This allows downloads from unsigned repositories which shouldn't be allowed and has been fixed in verisions 1.9.5, 1.9.0ubuntu1.2, 1.6.5ubuntu0.1, 1.1.0~beta1ubuntu0.16.04.7, 0.9.3.5ubuntu3+esm2, and 0.8.3ubuntu7.5.

python-apt only checks the MD5 sums of downloaded files in `Version.fetch_binary()` and `Version.fetch_source()` of apt/package.py in version 1.9.0ubuntu1 and earlier. This allows a man-in-the-middle attack which could potentially be used to install altered packages and has been fixed in versions 1.9.0ubuntu1.2, 1.6.5ubuntu0.1, 1.1.0~beta1ubuntu0.16.04.7, 0.9.3.5ubuntu3+esm2, and 0.8.3ubuntu7.5.

A vulnerability was discovered in the PyYAML library in versions before 5.3.1, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.

The command-line "safety" package for Python has a potential security issue. There are two Python characteristics that allow malicious code to “poison-pill” command-line Safety package detection routines by disguising, or obfuscating, other malicious or non-secure packages. This vulnerability is considered to be of low severity because the attack makes use of an existing Python condition, not the Safety tool itself. This can happen if: You are running Safety in a Python environment that you don’t trust. You are running Safety from the same Python environment where you have your dependencies installed. Dependency packages are being installed arbitrarily or without proper verification. Users can mitigate this issue by doing any of the following: Perform a static analysis by installing Docker and running the Safety Docker image: $ docker run --rm -it pyupio/safety check -r requirements.txt Run Safety against a static dependencies list, such as the requirements.txt file, in a separate, clean Python environment. Run Safety from a Continuous Integration pipeline. Use PyUp.io, which runs Safety in a controlled environment and checks Python for dependencies without any need to install them. Use PyUp's Online Requirements Checker.

The svglib package through 0.9.3 for Python allows XXE attacks via an svg2rlg call.

The gzip_decode function in the xmlrpc client library in Python 3.4 and earlier allows remote attackers to cause a denial of service (memory consumption) via a crafted HTTP request.

The _encode_invalid_chars function in util/url.py in the urllib3 library 1.25.2 through 1.25.7 for Python allows a denial of service (CPU consumption) because of an inefficient algorithm. The percent_encodings array contains all matches of percent encodings. It is not deduplicated. For a URL of length N, the size of percent_encodings may be up to O(N). The next step (normalize existing percent-encoded bytes) also takes up to O(N) for each step, so the total time is O(N^2). If percent_encodings were deduplicated, the time to compute _encode_invalid_chars would be O(kN), where k is at most 484 ((10+6*2)^2).

Improper neutralization of directives in dynamically evaluated code in Druva inSync Mac OS Client 6.5.0 allows a local, authenticated attacker to execute arbitrary Python expressions with root privileges.

The CGIHTTPServer module in Python 2.7.5 and 3.3.4 does not properly handle URLs in which URL encoding is used for path separators, which allows remote attackers to read script source code or conduct directory traversal attacks and execute unintended code via a crafted character sequence, as demonstrated by a %2f separator.

The Identity Provider (IdP) server in Ipsilon 0.1.0 before 1.0.1 does not properly escape certain characters in a Python exception-message template, which makes it easier for remote attackers to conduct cross-site scripting (XSS) attacks via an HTTP response.

A Code Execution vulnerability exists in select.py when using python-mode 2012-12-19.

Multiple format string vulnerabilities in the python module in RRDtool, as used in Zenoss Core before 4.2.5 and other products, allow remote attackers to execute arbitrary code or cause a denial of service (application crash) via a crafted third argument to the rrdtool.graph function, aka ZEN-15415, a related issue to CVE-2013-2131.

Lib/zipfile.py in Python through 3.7.2 allows remote attackers to cause a denial of service (resource consumption) via a ZIP bomb.

Python 2.7 through 2.7.17, 3.5 through 3.5.9, 3.6 through 3.6.10, 3.7 through 3.7.6, and 3.8 through 3.8.1 allows an HTTP server to conduct Regular Expression Denial of Service (ReDoS) attacks against a client because of urllib.request.AbstractBasicAuthHandler catastrophic backtracking.

In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant("hello", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.