🚨 CVE-2026-18445
There is an integer overflow vulnerability resulting in an out-of-bounds write recently discovered in NI LabVIEW. This may result in information disclosure or arbitrary code execution. Successful exploitation requires an attacker to get a user to open a specially crafted VI file. This vulnerability affects NI LabVIEW 2026 Q3 and prior versions.
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There is an integer overflow vulnerability resulting in an out-of-bounds write recently discovered in NI LabVIEW. This may result in information disclosure or arbitrary code execution. Successful exploitation requires an attacker to get a user to open a specially crafted VI file. This vulnerability affects NI LabVIEW 2026 Q3 and prior versions.
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Ni
Integer Overflow Vulnerability Resulting in an Out of Bounds Write in NI LabVIEW
There is an integer overflow vulnerability resulting in an out-of-bounds write recently discovered in NI LabVIEW. This may result in information disclosure or arbitrary code execution. Successful exploitation requires an attacker to get a user to open a…
🚨 CVE-2026-24166
NVIDIA UFM Enterprise contains a vulnerability in the session management component, where an attacker could use a hard-coded cryptographic key to extract information. A successful exploit of this vulnerability might lead to information disclosure and escalation of privileges.
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NVIDIA UFM Enterprise contains a vulnerability in the session management component, where an attacker could use a hard-coded cryptographic key to extract information. A successful exploit of this vulnerability might lead to information disclosure and escalation of privileges.
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GitHub
product-security/2026/5809 at main · NVIDIA/product-security
Starting October 1, 2025, NVIDIA PSIRT will publish an initial set of security bulletins on GitHub in Markdown, CSAF, and CVE formats. Coverage will expand over time, while all bulletins remain ava...
🚨 CVE-2026-24167
NVIDIA UFM Enterprise contains a vulnerability in the user management component, where an authenticated administrator could inject commands by sending a crafted API request. A successful exploit of this vulnerability might lead to code execution, escalation of privileges and information disclosure.
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NVIDIA UFM Enterprise contains a vulnerability in the user management component, where an authenticated administrator could inject commands by sending a crafted API request. A successful exploit of this vulnerability might lead to code execution, escalation of privileges and information disclosure.
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GitHub
product-security/2026/5809 at main · NVIDIA/product-security
Starting October 1, 2025, NVIDIA PSIRT will publish an initial set of security bulletins on GitHub in Markdown, CSAF, and CVE formats. Coverage will expand over time, while all bulletins remain ava...
🚨 CVE-2026-24168
NVIDIA UFM Enterprise contains a vulnerability in the IBDiagnet API where an authenticated attacker with administrative privileges may cause command injection by sending crafted API requests. A successful exploit of this vulnerability may lead to code execution, escalation of privileges and information disclosure.
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NVIDIA UFM Enterprise contains a vulnerability in the IBDiagnet API where an authenticated attacker with administrative privileges may cause command injection by sending crafted API requests. A successful exploit of this vulnerability may lead to code execution, escalation of privileges and information disclosure.
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GitHub
product-security/2026/5809 at main · NVIDIA/product-security
Starting October 1, 2025, NVIDIA PSIRT will publish an initial set of security bulletins on GitHub in Markdown, CSAF, and CVE formats. Coverage will expand over time, while all bulletins remain ava...
🚨 CVE-2026-24169
NVIDIA UFM Enterprise contains a vulnerability in the plugin management API, where an authenticated user with low privileges could inject code by sending a specially crafted API request. A successful exploit of this vulnerability might lead to code execution, escalation of privileges and information disclosure.
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NVIDIA UFM Enterprise contains a vulnerability in the plugin management API, where an authenticated user with low privileges could inject code by sending a specially crafted API request. A successful exploit of this vulnerability might lead to code execution, escalation of privileges and information disclosure.
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GitHub
product-security/2026/5809 at main · NVIDIA/product-security
Starting October 1, 2025, NVIDIA PSIRT will publish an initial set of security bulletins on GitHub in Markdown, CSAF, and CVE formats. Coverage will expand over time, while all bulletins remain ava...
🚨 CVE-2026-24170
NVIDIA UFM Enterprise contains a vulnerability in the web interface authorization component, where an authenticated user could cause improper authentication by sending specially crafted HTTP requests. A successful exploit of this vulnerability might lead to code execution and escalation of privileges.
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NVIDIA UFM Enterprise contains a vulnerability in the web interface authorization component, where an authenticated user could cause improper authentication by sending specially crafted HTTP requests. A successful exploit of this vulnerability might lead to code execution and escalation of privileges.
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GitHub
product-security/2026/5809 at main · NVIDIA/product-security
Starting October 1, 2025, NVIDIA PSIRT will publish an initial set of security bulletins on GitHub in Markdown, CSAF, and CVE formats. Coverage will expand over time, while all bulletins remain ava...
🚨 CVE-2026-24225
NVIDIA DGX Spark contains a vulnerability in the standalone MM firmware where an attacker could be able to cause an out-of-bounds read. A successful exploit of this vulnerability might lead to information disclosure.
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NVIDIA DGX Spark contains a vulnerability in the standalone MM firmware where an attacker could be able to cause an out-of-bounds read. A successful exploit of this vulnerability might lead to information disclosure.
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GitHub
product-security/2026/5867 at main · NVIDIA/product-security
Starting October 1, 2026, NVIDIA PSIRT will only publish security bulletins on GitHub in Markdown, CSAF, and CVE formats to meet industry demand for easier integration. - NVIDIA/product-security
🚨 CVE-2026-24262
NVIDIA DGX Spark contains a vulnerability in the system firmware, where a privileged attacker could be able to cause an out-of-bounds write. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, denial of service, information disclosure, and data tampering.
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NVIDIA DGX Spark contains a vulnerability in the system firmware, where a privileged attacker could be able to cause an out-of-bounds write. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, denial of service, information disclosure, and data tampering.
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GitHub
product-security/2026/5867 at main · NVIDIA/product-security
Starting October 1, 2026, NVIDIA PSIRT will only publish security bulletins on GitHub in Markdown, CSAF, and CVE formats to meet industry demand for easier integration. - NVIDIA/product-security
🚨 CVE-2026-24263
NVIDIA DGX Spark contains a vulnerability in the system firmware, where a privileged attacker could be able to cause a NULL pointer dereference. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, denial of service, information disclosure, and data tampering.
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NVIDIA DGX Spark contains a vulnerability in the system firmware, where a privileged attacker could be able to cause a NULL pointer dereference. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, denial of service, information disclosure, and data tampering.
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GitHub
product-security/2026/5867 at main · NVIDIA/product-security
Starting October 1, 2026, NVIDIA PSIRT will only publish security bulletins on GitHub in Markdown, CSAF, and CVE formats to meet industry demand for easier integration. - NVIDIA/product-security
🚨 CVE-2026-47626
NVIDIA DGX Spark contains a vulnerability in the system firmware, where a privileged attacker could be able to cause an out-of-bounds write. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, denial of service, information disclosure, and data tampering.
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NVIDIA DGX Spark contains a vulnerability in the system firmware, where a privileged attacker could be able to cause an out-of-bounds write. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, denial of service, information disclosure, and data tampering.
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GitHub
product-security/2026/5867 at main · NVIDIA/product-security
Starting October 1, 2026, NVIDIA PSIRT will only publish security bulletins on GitHub in Markdown, CSAF, and CVE formats to meet industry demand for easier integration. - NVIDIA/product-security
🚨 CVE-2026-59184
OpenEXR is the reference implementation and specification for the EXR image format, widely used in the motion picture industry. Versions before 3.2.11, 3.3.0 through 3.3.12, and 3.4.0 through 3.4.13 allow a crafted EXR with a nonzero dataWindow.min to make TypedFlatImageChannel::row() return an invalid heap pointer, causing out-of-bounds or use-after-free writes. This occurs when an application writes rows through FlatHalfChannel::row(). Affected consumers are tools, converters, render pipeline components, or image-processing services that accept untrusted EXR files and use FlatHalfChannel::row() on loaded images. This issue is fixed in versions 3.2.11, 3.3.13, and 3.4.14.
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OpenEXR is the reference implementation and specification for the EXR image format, widely used in the motion picture industry. Versions before 3.2.11, 3.3.0 through 3.3.12, and 3.4.0 through 3.4.13 allow a crafted EXR with a nonzero dataWindow.min to make TypedFlatImageChannel::row() return an invalid heap pointer, causing out-of-bounds or use-after-free writes. This occurs when an application writes rows through FlatHalfChannel::row(). Affected consumers are tools, converters, render pipeline components, or image-processing services that accept untrusted EXR files and use FlatHalfChannel::row() on loaded images. This issue is fixed in versions 3.2.11, 3.3.13, and 3.4.14.
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GitHub
Fix OpenEXRUtil row() OOB read with non-zero data window origin (#2488) · AcademySoftwareFoundation/openexr@37f03b6
The row() method in TypedDeepImageChannel, TypedFlatImageChannel, and
SampleCountChannel is documented as 0-based within the data window,
but used the _base offset meant for absolute (x, y) access....
SampleCountChannel is documented as 0-based within the data window,
but used the _base offset meant for absolute (x, y) access....
🚨 CVE-2026-59982
OpenEXR is the reference implementation and specification for the EXR image format, widely used in the motion picture industry. OpenEXR versions before 3.2.11, 3.3.0 through 3.3.12, and 3.4.0 through 3.4.13 can return an out-of-bounds pointer from TypedDeepImageChannel::row() when a crafted deep EXR has a nonzero dataWindow origin. This vulnerability occurs because the API combines zero-based row access with an absolute-coordinate-adjusted base pointer, allowing a crash or limited information disclosure. This issue is fixed in versions 3.2.11, 3.3.13, and 3.4.14.
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OpenEXR is the reference implementation and specification for the EXR image format, widely used in the motion picture industry. OpenEXR versions before 3.2.11, 3.3.0 through 3.3.12, and 3.4.0 through 3.4.13 can return an out-of-bounds pointer from TypedDeepImageChannel::row() when a crafted deep EXR has a nonzero dataWindow origin. This vulnerability occurs because the API combines zero-based row access with an absolute-coordinate-adjusted base pointer, allowing a crash or limited information disclosure. This issue is fixed in versions 3.2.11, 3.3.13, and 3.4.14.
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GitHub
Fix OpenEXRUtil row() OOB read with non-zero data window origin (#2488) · AcademySoftwareFoundation/openexr@37f03b6
The row() method in TypedDeepImageChannel, TypedFlatImageChannel, and
SampleCountChannel is documented as 0-based within the data window,
but used the _base offset meant for absolute (x, y) access....
SampleCountChannel is documented as 0-based within the data window,
but used the _base offset meant for absolute (x, y) access....
🚨 CVE-2026-80051
github.com/graphql-go/graphql (GraphQL for Go) through 0.8.1 does not validate that a scalar variable value matches its declared type. The built-in coerceString and coerceBool functions (scalars.go) accept input whose type does not match the declared String, ID, or Boolean scalar instead of raising the request error that the GraphQL specification mandates. In some cases (but not any typical case of JSON sent to a website), a deeply nested value leads to an unrecoverable "fatal error: stack overflow" condition.
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github.com/graphql-go/graphql (GraphQL for Go) through 0.8.1 does not validate that a scalar variable value matches its declared type. The built-in coerceString and coerceBool functions (scalars.go) accept input whose type does not match the declared String, ID, or Boolean scalar instead of raising the request error that the GraphQL specification mandates. In some cases (but not any typical case of JSON sent to a website), a deeply nested value leads to an unrecoverable "fatal error: stack overflow" condition.
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GitHub
graphql/scalars.go at v0.8.1 · graphql-go/graphql
An implementation of GraphQL for Go / Golang. Contribute to graphql-go/graphql development by creating an account on GitHub.
🚨 CVE-2026-55619
eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information. Prior to 3.0.2, eml_parser.parser.HeaderParser.header_fetch_parse in eml_parser/parser.py uses email.utils.getaddresses() to parse address-bearing e-mail headers. A deeply nested CFWS comment construct exhausts the standard-library recursive descent parser's call stack and raises RecursionError, which is not caught and therefore aborts parsing of the entire message. An attacker can disrupt SOC pipelines that process untrusted EML files, although callers already need to handle exceptions from malformed or pathological messages. This issue is fixed in version 3.0.2.
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eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information. Prior to 3.0.2, eml_parser.parser.HeaderParser.header_fetch_parse in eml_parser/parser.py uses email.utils.getaddresses() to parse address-bearing e-mail headers. A deeply nested CFWS comment construct exhausts the standard-library recursive descent parser's call stack and raises RecursionError, which is not caught and therefore aborts parsing of the entire message. An attacker can disrupt SOC pipelines that process untrusted EML files, although callers already need to handle exceptions from malformed or pathological messages. This issue is fixed in version 3.0.2.
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GitHub
Address security advisories (#90) · GOVCERT-LU/eml_parser@746a69f
* handle exceeded stack limit in header parsing
* fix slow parenthesis removal
* Improve documentation of `noparenthesis`.
* Properly handle HTML entities in URLs
This also runs the domain pars...
* fix slow parenthesis removal
* Improve documentation of `noparenthesis`.
* Properly handle HTML entities in URLs
This also runs the domain pars...
🚨 CVE-2026-62986
OpenEXR is the reference implementation and specification for the EXR image file format, widely used in the motion picture industry. In versions 3.3.0 through 3.3.12 and 3.4.0 through 3.4.13, the PyOpenEXR Python bindings return stale heap data when reading a crafted deep scanline EXR that uses layer-prefixed RGB channels. With the default channel coalescing (separate_channels=False), the wrapper groups channels such as left.R, left.G, and left.B into a single RGB sample array, but the lane-offset calculation in PyPart::setDeepSliceData() only recognizes the exact unprefixed names G, B, and A. As a result, prefixed channels like left.G and left.B are decoded into lane 0 while lanes 1 and 2 are left uninitialized and returned to Python. A Python application that reads untrusted deep EXR files through the default OpenEXR.File API and then logs, serializes, previews, or otherwise processes the resulting NumPy sample arrays may expose uninitialized same-process heap contents, in addition to receiving incorrect green and blue channel data. This issue is fixed in versions 3.3.13 and 3.4.14.
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OpenEXR is the reference implementation and specification for the EXR image file format, widely used in the motion picture industry. In versions 3.3.0 through 3.3.12 and 3.4.0 through 3.4.13, the PyOpenEXR Python bindings return stale heap data when reading a crafted deep scanline EXR that uses layer-prefixed RGB channels. With the default channel coalescing (separate_channels=False), the wrapper groups channels such as left.R, left.G, and left.B into a single RGB sample array, but the lane-offset calculation in PyPart::setDeepSliceData() only recognizes the exact unprefixed names G, B, and A. As a result, prefixed channels like left.G and left.B are decoded into lane 0 while lanes 1 and 2 are left uninitialized and returned to Python. A Python application that reads untrusted deep EXR files through the default OpenEXR.File API and then logs, serializes, previews, or otherwise processes the resulting NumPy sample arrays may expose uninitialized same-process heap contents, in addition to receiving incorrect green and blue channel data. This issue is fixed in versions 3.3.13 and 3.4.14.
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GitHub
Fix name comparison in deep prefixed RGB channel coalescing (#2522) · AcademySoftwareFoundation/openexr@36ff096
setDeepSliceData() used strcmp(c.name(), "G"/"B"/"A") to select the
RGB channel offset, which only matched unprefixed channel names. For
layer-...
RGB channel offset, which only matched unprefixed channel names. For
layer-...
🚨 CVE-2026-65979
OpenEXR is the reference implementation and specification for the EXR image format, widely used in the motion picture industry. From version 3.4.0 through 3.4.12, the HTJ2K decoder parses a header-length field (PLEN) from a chunk's compressed data but never checks that this value fits within the available buffer before using it. When decoding, it advances the codestream pointer by the attacker-supplied header size and passes the resulting offset and remaining length to the OpenJPH memory-input path, so a crafted value pushes the pointer past the end of the buffer and causes an out-of-bounds read. Because this field comes straight from attacker-controlled EXR chunk data, the flaw is reachable during normal decoding of an untrusted file. This issue is fixed in version 3.4.13.
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OpenEXR is the reference implementation and specification for the EXR image format, widely used in the motion picture industry. From version 3.4.0 through 3.4.12, the HTJ2K decoder parses a header-length field (PLEN) from a chunk's compressed data but never checks that this value fits within the available buffer before using it. When decoding, it advances the codestream pointer by the attacker-supplied header size and passes the resulting offset and remaining length to the OpenJPH memory-input path, so a crafted value pushes the pointer past the end of the buffer and causes an out-of-bounds read. Because this field comes straight from attacker-controlled EXR chunk data, the flaw is reachable during normal decoding of an untrusted file. This issue is fixed in version 3.4.13.
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GitHub
Validate HTJ2K chunk header length before decode (#2434) · AcademySoftwareFoundation/openexr@c7af2d2
* Validate HTJ2K chunk header length before decode
Reject oversized or inconsistent header payload lengths so corrupted
chunks cannot advance the codestream pointer past the compressed buffer.
Add...
Reject oversized or inconsistent header payload lengths so corrupted
chunks cannot advance the codestream pointer past the compressed buffer.
Add...
🚨 CVE-2026-78379
Improper neutralization of input used for LLM prompting in the python_repl tool in Amazon Strands Agents Tools before 0.8.5 might allow remote actors to execute arbitrary Python code on the agent's host by bypassing the human consent gate, via a crafted prompt that forwards non_interactive_mode as a keyword argument through the batch tool. To remediate this issue, users should upgrade to version 0.8.5 or later.
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Improper neutralization of input used for LLM prompting in the python_repl tool in Amazon Strands Agents Tools before 0.8.5 might allow remote actors to execute arbitrary Python code on the agent's host by bypassing the human consent gate, via a crafted prompt that forwards non_interactive_mode as a keyword argument through the batch tool. To remediate this issue, users should upgrade to version 0.8.5 or later.
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🚨 CVE-2026-80049
Airbyte Platform resolves the workspace used for its authorization decision from a field the caller supplies. AuthorizationServerHandler copies recognised identifiers out of the raw JSON request body into X-Airbyte-* headers, and AuthenticationHeaderResolver.resolveWorkspace consults X-Airbyte-Workspace-Id ahead of every resource-derived header, including those for connection, source and destination identifiers. Endpoints whose declared request bodies carry only a resource identifier are nonetheless reached with an added workspaceId field, because the extractor reads the body rather than the endpoint's schema, so the permission check is performed against the workspace the caller nominated while the handler acts on the resource identifier the caller supplied. Nothing afterwards compares the resource's owning workspace with the one that was authorized. A member of any workspace can therefore read source and destination configuration, trigger and cancel syncs, and delete connections, sources and destinations that belong to workspaces they have no access to, at whatever privilege level their own workspace membership grants them.
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Airbyte Platform resolves the workspace used for its authorization decision from a field the caller supplies. AuthorizationServerHandler copies recognised identifiers out of the raw JSON request body into X-Airbyte-* headers, and AuthenticationHeaderResolver.resolveWorkspace consults X-Airbyte-Workspace-Id ahead of every resource-derived header, including those for connection, source and destination identifiers. Endpoints whose declared request bodies carry only a resource identifier are nonetheless reached with an added workspaceId field, because the extractor reads the body rather than the endpoint's schema, so the permission check is performed against the workspace the caller nominated while the handler acts on the resource identifier the caller supplied. Nothing afterwards compares the resource's owning workspace with the one that was authorized. A member of any workspace can therefore read source and destination configuration, trigger and cancel syncs, and delete connections, sources and destinations that belong to workspaces they have no access to, at whatever privilege level their own workspace membership grants them.
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GitHub
GitHub - airbytehq/airbyte-platform: The platform that powers Airbyte. Please file issues in https://github.com/airbytehq/airbyte
The platform that powers Airbyte. Please file issues in https://github.com/airbytehq/airbyte - airbytehq/airbyte-platform
🚨 CVE-2026-43657
A permissions issue was addressed with additional restrictions. This issue is fixed in iOS 26.5 and iPadOS 26.5. A malicious app may be able to enumerate installed apps.
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A permissions issue was addressed with additional restrictions. This issue is fixed in iOS 26.5 and iPadOS 26.5. A malicious app may be able to enumerate installed apps.
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Apple Support
About the security content of iOS 26.5 and iPadOS 26.5 - Apple Support
This document describes the security content of iOS 26.5 and iPadOS 26.5.
🚨 CVE-2026-43670
A Content Security Policy bypass was addressed with improved enforcement in AudioWorklet contexts. This issue is fixed in Safari 26.5, iOS 18.7.9 and iPadOS 18.7.9, iOS 26.5 and iPadOS 26.5, macOS Tahoe 26.5. Processing maliciously crafted web content may bypass Content Security Policy.
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A Content Security Policy bypass was addressed with improved enforcement in AudioWorklet contexts. This issue is fixed in Safari 26.5, iOS 18.7.9 and iPadOS 18.7.9, iOS 26.5 and iPadOS 26.5, macOS Tahoe 26.5. Processing maliciously crafted web content may bypass Content Security Policy.
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Apple Support
About the security content of iOS 26.5 and iPadOS 26.5 - Apple Support
This document describes the security content of iOS 26.5 and iPadOS 26.5.
❤1
🚨 CVE-2026-45018
Chainlit is a Python framework for building production-ready conversational AI applications. From 2.4.0rc0 until 2.12.0, Chainlit deployments with features.mcp.enabled set to true in .chainlit/config.toml expose the POST /mcp endpoint without requiring authentication. For stdio transport, the endpoint accepts a user-controlled fullCommand string. The validate_mcp_command() function in backend/chainlit/mcp.py checks only the executable name against config.features.mcp.stdio.allowed_executables and passes unchecked arguments to StdioServerParameters in backend/chainlit/server.py. Because npx supports the -c argument, an attacker can execute arbitrary shell commands with the privileges of the Chainlit process. If allowed_executables is unset, its None default is treated as allowing every executable. This issue is fixed in version 2.12.0.
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Chainlit is a Python framework for building production-ready conversational AI applications. From 2.4.0rc0 until 2.12.0, Chainlit deployments with features.mcp.enabled set to true in .chainlit/config.toml expose the POST /mcp endpoint without requiring authentication. For stdio transport, the endpoint accepts a user-controlled fullCommand string. The validate_mcp_command() function in backend/chainlit/mcp.py checks only the executable name against config.features.mcp.stdio.allowed_executables and passes unchecked arguments to StdioServerParameters in backend/chainlit/server.py. Because npx supports the -c argument, an attacker can execute arbitrary shell commands with the privileges of the Chainlit process. If allowed_executables is unset, its None default is treated as allowing every executable. This issue is fixed in version 2.12.0.
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GitHub
chainlit/docs/security-advisory-2026-mcp.md at 2.12.0 · Chainlit/chainlit
Build Conversational AI in minutes ⚡️. Contribute to Chainlit/chainlit development by creating an account on GitHub.