pypdf: Crafted PDF with malformed startxref causes a Denial of Service.
pypdf is a free and open-source pure-python PDF library. Prior to version 6.6.0, pypdf has possible long runtimes for malformed startxref. An attacker who uses this vulnerability can craft a PDF which leads to possibly long runtimes for invalid startxref entries. When rebuilding the cross-reference table, PDF files with lots of whitespace characters become problematic. Only the non-strict reading mode is affected. Only the non-strict reading mode is affected. This issue has been patched in version 6.6.0.
virtualenv TOCTOU race condition allows symlink attacks on directory creation.
virtualenv is a tool for creating isolated virtual python environments. Prior to version 20.36.1, TOCTOU (Time-of-Check-Time-of-Use) vulnerabilities in virtualenv allow local attackers to perform symlink-based attacks on directory creation operations. An attacker with local access can exploit a race condition between directory existence checks and creation to redirect virtualenv's app_data and lock file operations to attacker-controlled locations. This issue has been patched in version 20.36.1.
TOCTOU race condition in filelock allows symlink attack, leading to DoS.
filelock is a platform-independent file lock for Python. Prior to version 3.20.3, a TOCTOU race condition vulnerability exists in the SoftFileLock implementation of the filelock package. An attacker with local filesystem access and permission to create symlinks can exploit a race condition between the permission validation and file creation to cause lock operations to fail or behave unexpectedly. The vulnerability occurs in the _acquire() method between raise_on_not_writable_file() (permission check) and os.open() (file creation). During this race window, an attacker can create a symlink at the lock file path, potentially causing the lock to operate on an unintended target file or leading to denial of service. This issue has been patched in version 3.20.3.
Fickling is vulnerable to detection bypass due to "builtins" blindness.
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, Fickling is vulnerable to detection bypass due to "builtins" blindness. This issue has been patched in version 0.1.7.
Fickling fails to detect unsafe imports, allowing arbitrary code execution.
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, the unsafe_imports() method in Fickling's static analyzer fails to flag several high-risk Python modules that can be used for arbitrary code execution. Malicious pickles importing these modules will not be detected as unsafe, allowing attackers to bypass Fickling's primary static safety checks. This issue has been patched in version 0.1.7.
Fickling scanner bypass via pydoc/ctypes allows remote code execution.
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, both ctypes and pydoc modules aren't explicitly blocked. Even other existing pickle scanning tools (like picklescan) do not block pydoc.locate. Chaining these two together can achieve RCE while the scanner still reports the file as LIKELY_SAFE. This issue has been patched in version 0.1.7.
Fickling misclassifies cProfile pickles, allowing remote code execution.
Fickling is a Python pickling decompiler and static analyzer. Fickling versions up to and including 0.1.6 do not treat Python's cProfile module as unsafe. Because of this, a malicious pickle that uses cProfile.run() is classified as SUSPICIOUS instead of OVERTLY_MALICIOUS. If a user relies on Fickling's output to decide whether a pickle is safe to deserialize, this misclassification can lead them to execute attacker-controlled code on their system. This affects any workflow or product that uses Fickling as a security gate for pickle deserialization. This issue has been patched in version 0.1.7.
Fickling misclassifies pickles using `runpy`, leading to code execution.
Fickling is a Python pickling decompiler and static analyzer. Fickling versions up to and including 0.1.6 do not treat Pythonโs runpy module as unsafe. Because of this, a malicious pickle that uses runpy.run_path() or runpy.run_module() is classified as SUSPICIOUS instead of OVERTLY_MALICIOUS. If a user relies on Ficklingโs output to decide whether a pickle is safe to deserialize, this misclassification can lead them to execute attacker-controlled code on their system. This affects any workflow or product that uses Fickling as a security gate for pickle deserialization. This issue has been patched in version 0.1.7.
CSRF in Authlib due to cache state not being tied to the user session.
Authlib is a Python library which builds OAuth and OpenID Connect servers. In version 1.6.5 and prior, cache-backed state/request-token storage is not tied to the initiating user session, so CSRF is possible for any attacker that has a valid state (easily obtainable via an attacker-initiated authentication flow). When a cache is supplied to the OAuth client registry, FrameworkIntegration.set_state_data writes the entire state blob under _state_{app}_{state}, and get_state_data ignores the callerโs session altogether. This issue has been patched in version 1.6.6.
Improper type conversion in Logging Redactor can cause log formatting errors.
Logging Redactor is a Python library designed to redact sensitive data in logs based on regex patterns and / or dictionary keys. Prior to version 0.0.6, non-string types are converted into string types, leading to type errors in %d conversions. The problem has been patched in version 0.0.6. No known workarounds are available.
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.
The supreme art of war is to subdue the enemy without fighting.
Sun Tzu – “The Art of War”
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