Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the Pillow package are vulnerable to an Out-of-bounds Write issue due to insufficient validation of tile extents when decoding PSD image data. When Image.open() loads a PSD and the decoder paths in src/decode.c and src/encode.c process tile offsets and sizes, negative xoff/yoff values (and related invalid extents) can bypass expected bounds checks and lead to writes outside the intended image buffer.

Affected versions of this package are vulnerable to a Buffer Overflow when saving sufficiently large compressed DDS images (>64KB with default settings). The DDS encoding functionality fails to perform bounds checking when writing to the destination buffer, leading to a heap buffer overflow condition. This vulnerability was introduced in Pillow 11.2.0 when BCn compression support for DDS format was added.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the Django package are vulnerable to SQL Injection due to improper handling of control characters in column aliases within FilteredRelation. The FilteredRelation class fails to properly sanitize column aliases containing control characters when used with QuerySet methods annotate(), aggregate(), extra(), values(), values_list(), and alias() via dictionary expansion (**kwargs).

Affected versions of the Django package are vulnerable to Denial of Service (DoS) due to inefficient string concatenation when processing duplicate HTTP headers in ASGI mode. The ASGIRequest class combines repeated headers using repeated string concatenation, resulting in super-linear (quadratic) time complexity when processing requests with many duplicate headers.

Affected versions of the Django package are vulnerable to SQL Injection due to improper sanitization of band index parameters in PostGIS raster lookups. The raster lookup functionality in Django's GIS module fails to properly validate or escape untrusted data used as a band index when performing spatial queries against PostGIS databases.

Affected versions of the Django package are vulnerable to SQL Injection due to improper handling of column aliases containing periods in QuerySet.order_by() when combined with FilteredRelation. The QuerySet.order_by() method fails to properly sanitize column aliases that contain periods when the same alias is used in FilteredRelation via dictionary expansion. 
https://github.com/django/django/commit/90f5b10784ba5bf369caed87640e2b4394ea3314

An issue was discovered in Django 4.2 before 4.2.21, 5.1 before 5.1.9, and 5.2 before 5.2.1. The django.utils.html.strip_tags() function is vulnerable to a potential denial-of-service (slow performance) when processing inputs containing large sequences of incomplete HTML tags. The template filter striptags is also vulnerable, because it is built on top of strip_tags().

Affected versions of the Django package are vulnerable to Denial of Service (DoS) due to quadratic time complexity during HTML parsing in text truncation methods. The django.utils.text.Truncator.chars() and Truncator.words() methods (with html=True), as well as the truncatechars_html and truncatewords_html template filters, exhibit quadratic time complexity when processing inputs containing a large number of unmatched HTML end tags.

Affected versions of the Django package are vulnerable to Information Disclosure (Timing Attack) due to non-constant-time comparison in the mod_wsgi authentication handler. The django.contrib.auth.handlers.modwsgi.check_password() function does not perform user existence checks in constant time, allowing response timing differences to reveal whether usernames exist.

Django fixes a potential denial-of-service vulnerability in XML ``Deserializer``.

Affected versions of the Django package are vulnerable to SQL Injection due to insufficient neutralization of user-controlled column alias names provided via dictionary expansion. The QuerySet.annotate(), QuerySet.alias(), QuerySet.aggregate(), and QuerySet.extra() methods accept **kwargs whose keys are used as column aliases, and on MySQL and MariaDB, those identifiers are not safely quoted, permitting crafted input to be incorporated into the generated SQL.

An issue was discovered in Django 5.2 before 5.2.3, 5.1 before 5.1.11, and 4.2 before 4.2.23. Internal HTTP response logging does not escape request.path, which allows remote attackers to potentially manipulate log output via crafted URLs. This may lead to log injection or forgery when logs are viewed in terminals or processed by external systems.

CVE-2025-64459: Affected versions of the Django package are vulnerable to SQL Injection due to improper input validation, allowing the internal _connector keyword argument to be accepted from untrusted dictionaries via expansion. The .filter(), .exclude(), and .get() methods on QuerySet, as well as the Q class, resolve **kwargs and will treat a supplied _connector value as the logical connector without constraining it to the expected set (AND/OR), permitting attacker-controlled tokens to influence SQL predicate construction.

CVE-2025-64458: Affected versions of the Django package are vulnerable to Denial of Service (DoS) due to slow Unicode NFKC normalization on Windows being applied to untrusted inputs. The django.contrib.auth.views.LoginView and django.contrib.auth.views.LogoutView, and django.views.i18n.set_language normalize user-controlled strings using Python’s NFKC algorithm, which is unusually slow on Windows for huge Unicode sequences and can be triggered to consume excessive CPU.

Affected versions of the Django package are vulnerable to Path Traversal due to improper validation of archive member paths during extraction. The django.utils.archive.extract() function—used by the startapp --template and startproject --template commands—checked path prefixes instead of using canonicalised paths, allowing archive entries whose names share a prefix with the destination to resolve outside the intended directory.

Affected versions of the Django package are vulnerable to SQL Injection due to insufficient input sanitization in FilteredRelation column aliases. The FilteredRelation class fails to properly validate or escape column alias names when they are provided through dictionary expansion as keyword arguments to QuerySet.annotate() or QuerySet.alias() methods, allowing malicious SQL code to be injected directly into the generated database queries.

Django fixes potential SQL injection in ``FilteredRelation`` column aliases on PostgreSQL.

Affected versions of the Pillow package are vulnerable to an Out-of-bounds Write issue due to insufficient validation of tile extents when decoding PSD image data. When Image.open() loads a PSD and the decoder paths in src/decode.c and src/encode.c process tile offsets and sizes, negative xoff/yoff values (and related invalid extents) can bypass expected bounds checks and lead to writes outside the intended image buffer.

Affected versions of this package are vulnerable to a Buffer Overflow when saving sufficiently large compressed DDS images (>64KB with default settings). The DDS encoding functionality fails to perform bounds checking when writing to the destination buffer, leading to a heap buffer overflow condition. This vulnerability was introduced in Pillow 11.2.0 when BCn compression support for DDS format was added.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the Pillow package are vulnerable to an Out-of-bounds Write issue due to insufficient validation of tile extents when decoding PSD image data. When Image.open() loads a PSD and the decoder paths in src/decode.c and src/encode.c process tile offsets and sizes, negative xoff/yoff values (and related invalid extents) can bypass expected bounds checks and lead to writes outside the intended image buffer.

Affected versions of this package are vulnerable to a Buffer Overflow when saving sufficiently large compressed DDS images (>64KB with default settings). The DDS encoding functionality fails to perform bounds checking when writing to the destination buffer, leading to a heap buffer overflow condition. This vulnerability was introduced in Pillow 11.2.0 when BCn compression support for DDS format was added.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the Pillow package are vulnerable to an Out-of-bounds Write issue due to insufficient validation of tile extents when decoding PSD image data. When Image.open() loads a PSD and the decoder paths in src/decode.c and src/encode.c process tile offsets and sizes, negative xoff/yoff values (and related invalid extents) can bypass expected bounds checks and lead to writes outside the intended image buffer.

Affected versions of this package are vulnerable to a Buffer Overflow when saving sufficiently large compressed DDS images (>64KB with default settings). The DDS encoding functionality fails to perform bounds checking when writing to the destination buffer, leading to a heap buffer overflow condition. This vulnerability was introduced in Pillow 11.2.0 when BCn compression support for DDS format was added.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the Django package are vulnerable to SQL Injection due to improper handling of control characters in column aliases within FilteredRelation. The FilteredRelation class fails to properly sanitize column aliases containing control characters when used with QuerySet methods annotate(), aggregate(), extra(), values(), values_list(), and alias() via dictionary expansion (**kwargs).

Affected versions of the Django package are vulnerable to Denial of Service (DoS) due to inefficient string concatenation when processing duplicate HTTP headers in ASGI mode. The ASGIRequest class combines repeated headers using repeated string concatenation, resulting in super-linear (quadratic) time complexity when processing requests with many duplicate headers.

Affected versions of the Django package are vulnerable to SQL Injection due to improper sanitization of band index parameters in PostGIS raster lookups. The raster lookup functionality in Django's GIS module fails to properly validate or escape untrusted data used as a band index when performing spatial queries against PostGIS databases.

Affected versions of the Django package are vulnerable to SQL Injection due to improper handling of column aliases containing periods in QuerySet.order_by() when combined with FilteredRelation. The QuerySet.order_by() method fails to properly sanitize column aliases that contain periods when the same alias is used in FilteredRelation via dictionary expansion. 
https://github.com/django/django/commit/90f5b10784ba5bf369caed87640e2b4394ea3314

An issue was discovered in Django 4.2 before 4.2.21, 5.1 before 5.1.9, and 5.2 before 5.2.1. The django.utils.html.strip_tags() function is vulnerable to a potential denial-of-service (slow performance) when processing inputs containing large sequences of incomplete HTML tags. The template filter striptags is also vulnerable, because it is built on top of strip_tags().

Affected versions of the Django package are vulnerable to Denial of Service (DoS) due to quadratic time complexity during HTML parsing in text truncation methods. The django.utils.text.Truncator.chars() and Truncator.words() methods (with html=True), as well as the truncatechars_html and truncatewords_html template filters, exhibit quadratic time complexity when processing inputs containing a large number of unmatched HTML end tags.

Affected versions of the Django package are vulnerable to Information Disclosure (Timing Attack) due to non-constant-time comparison in the mod_wsgi authentication handler. The django.contrib.auth.handlers.modwsgi.check_password() function does not perform user existence checks in constant time, allowing response timing differences to reveal whether usernames exist.

Django fixes a potential denial-of-service vulnerability in XML ``Deserializer``.

Affected versions of the Django package are vulnerable to SQL Injection due to insufficient neutralization of user-controlled column alias names provided via dictionary expansion. The QuerySet.annotate(), QuerySet.alias(), QuerySet.aggregate(), and QuerySet.extra() methods accept **kwargs whose keys are used as column aliases, and on MySQL and MariaDB, those identifiers are not safely quoted, permitting crafted input to be incorporated into the generated SQL.

An issue was discovered in Django 5.2 before 5.2.3, 5.1 before 5.1.11, and 4.2 before 4.2.23. Internal HTTP response logging does not escape request.path, which allows remote attackers to potentially manipulate log output via crafted URLs. This may lead to log injection or forgery when logs are viewed in terminals or processed by external systems.

CVE-2025-64459: Affected versions of the Django package are vulnerable to SQL Injection due to improper input validation, allowing the internal _connector keyword argument to be accepted from untrusted dictionaries via expansion. The .filter(), .exclude(), and .get() methods on QuerySet, as well as the Q class, resolve **kwargs and will treat a supplied _connector value as the logical connector without constraining it to the expected set (AND/OR), permitting attacker-controlled tokens to influence SQL predicate construction.

CVE-2025-64458: Affected versions of the Django package are vulnerable to Denial of Service (DoS) due to slow Unicode NFKC normalization on Windows being applied to untrusted inputs. The django.contrib.auth.views.LoginView and django.contrib.auth.views.LogoutView, and django.views.i18n.set_language normalize user-controlled strings using Python’s NFKC algorithm, which is unusually slow on Windows for huge Unicode sequences and can be triggered to consume excessive CPU.

Affected versions of the Django package are vulnerable to Path Traversal due to improper validation of archive member paths during extraction. The django.utils.archive.extract() function—used by the startapp --template and startproject --template commands—checked path prefixes instead of using canonicalised paths, allowing archive entries whose names share a prefix with the destination to resolve outside the intended directory.

Affected versions of the Django package are vulnerable to SQL Injection due to insufficient input sanitization in FilteredRelation column aliases. The FilteredRelation class fails to properly validate or escape column alias names when they are provided through dictionary expansion as keyword arguments to QuerySet.annotate() or QuerySet.alias() methods, allowing malicious SQL code to be injected directly into the generated database queries.

Django fixes potential SQL injection in ``FilteredRelation`` column aliases on PostgreSQL.

Affected versions of the Pillow package are vulnerable to an Out-of-bounds Write issue due to insufficient validation of tile extents when decoding PSD image data. When Image.open() loads a PSD and the decoder paths in src/decode.c and src/encode.c process tile offsets and sizes, negative xoff/yoff values (and related invalid extents) can bypass expected bounds checks and lead to writes outside the intended image buffer.

Affected versions of this package are vulnerable to a Buffer Overflow when saving sufficiently large compressed DDS images (>64KB with default settings). The DDS encoding functionality fails to perform bounds checking when writing to the destination buffer, leading to a heap buffer overflow condition. This vulnerability was introduced in Pillow 11.2.0 when BCn compression support for DDS format was added.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.

Affected versions of the sqlparse package are vulnerable to Denial of Service (DoS) due to missing hard limits on token grouping recursion depth and token processing when formatting very large SQL tuple lists. During sqlparse.format() processing, the sqlparse.engine.grouping._group_matching() and sqlparse.engine.grouping._group() functions can recurse and iterate over excessively large tlist.tokens without enforcing MAX_GROUPING_DEPTH or MAX_GROUPING_TOKENS, allowing grouping work to grow until it effectively hangs.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks due to Algorithmic Complexity. The SQL parser fails to enforce limits when processing deeply nested tuples and large token sequences, leading to excessive resource consumption through crafted SQL statements with extreme nesting depth or token counts.

**Note:** This issue is due to an incomplete fix for CVE-2024-4340.