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.

In Python (CPython) 3.6 through 3.6.10, 3.7 through 3.7.6, and 3.8 through 3.8.1, an insecure dependency load upon launch on Windows 7 may result in an attacker's copy of api-ms-win-core-path-l1-1-0.dll being loaded and used instead of the system's copy. Windows 8 and later are unaffected.

The py-bcrypt module before 0.3 for Python does not properly handle concurrent memory access, which allows attackers to bypass authentication via multiple authentication requests, which trigger the password hash to be overwritten.

python-markdown2 before 1.0.1.14 has multiple cross-site scripting (XSS) issues.

Juniper Junos OS 13.2 before 13.2R5, 13.2X51, 13.2X52, and 13.3 before 13.3R3 allow local users to bypass intended restrictions and execute arbitrary Python code via vectors involving shell access.

When Python was installed on Windows, a python file being served with the MIME type of text/plain could be executed by Python instead of being opened as a text file when the Open option was selected upon download. *Note: this issue only occurs on Windows. Other operating systems are unaffected.*. This vulnerability affects Firefox < 72.

There is a DoS vulnerability in Pillow before 6.2.2 caused by FpxImagePlugin.py calling the range function on an unvalidated 32-bit integer if the number of bands is large. On Windows running 32-bit Python, this results in an OverflowError or MemoryError due to the 2 GB limit. However, on Linux running 64-bit Python this results in the process being terminated by the OOM killer.

A flaw was found in all python-ecdsa versions before 0.13.3, where it did not correctly verify whether signatures used DER encoding. Without this verification, a malformed signature could be accepted, making the signature malleable. Without proper verification, an attacker could use a malleable signature to create false transactions.