🚨 CVE-2026-40610
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. In versions 1.4.38 and prior, the build packaging workflow follows attacker-controlled symlinks inside the build context and copies the referenced file contents into the generated Bento artifact. If a victim builds an untrusted repository or other attacker-supplied build context, the attacker can place a symlink such as loot.txt -> /tmp/outside-marker.txt or a link to a more sensitive local file. When bentoml build runs, BentoML dereferences the symlink and packages the target file contents into the Bento. The leaked file can then propagate further through export, push, or containerization workflows. An attacker can exfiltrate local files from the build host into the Bento artifact, exposing secrets such as cloud credentials, SSH keys, API tokens, environment files, or other sensitive local configurations. Because Bento artifacts are commonly exported, uploaded, stored, or containerized after build, the leaked file contents can spread beyond the original build machine. This issue has been fixed in version 1.4.39.

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🚨 CVE-2026-5817
The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered.

Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.

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🚨 CVE-2026-5843
The MLX inference backend in Docker Model Runner on macOS uses the MLX-LM library, which unconditionally imports and executes arbitrary Python files from model directories via the model_file configuration field in config.json. When a model's config.json specifies a model_file pointing to a Python file, MLX-LM uses importlib to load and execute it with no trust_remote_code gate or equivalent safety check. The MLX backend runs without sandboxing, resulting in arbitrary code execution on the Docker host as the Docker Desktop user.

Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model from an attacker-controlled OCI registry and request inference.

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🚨 CVE-2026-3294
An authentication logic vulnerability in multiple TP-Link range extenders allows an unauthenticated attacker on an adjacent network to manipulate a login parameter and reset the administrator password due to insufficient validation.

Successful exploitation allows an attacker to obtain full administrative control of the affected device, potentially impacting on confidentiality, integrity, and availability.

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🚨 CVE-2026-40864
JupyterHub is software that allows users to create a multi-user server for Jupyter notebooks. In versions 4.1.0 through 5.4.4, XSRF protection (updated in 4.1.0) inappropriately treated requests with Sec-Fetch-Mode: no-cors as same-origin requests, bypassing XSRF checks. The JSON API is not affected, only HTTP form endpoints, such as /hub/spawn and /hub/accept-share, meaning attackers could trigger server spawn (but not access the server) and if the attacker is a JupyterHub user permitted to share access to their server, cause a user to accept a share and have access to the attacker's server. This issue has been fixed in version 5.4.5. If developers are unable to immediately upgrade, they can temporarily mitigate this issue by dropping requests to JupyterHub with Sec-Fetch-Mode: no-cors if they are using a reverse proxy.

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🚨 CVE-2026-41069
libheif is a HEIF and AVIF file format decoder and encoder. In versions 1.21.2 and prior, a malformed HEIF sequence file can trigger an out-of-bounds read in core sequence parsing logic, causing DoS. A malformed file can have stco.entry_count == 0 (creating no chunks) while still passing validation because saio.entry_count == 0 matches, but with saiz.sample_count > 0 the SampleAuxInfoReader constructor still enters its loop. This leads to an out-of-bounds dereference on the empty chunks[0] in chunked mode.

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🚨 CVE-2026-41071
libheif is a HEIF and AVIF file format decoder and encoder. In versions 1.21.2 and prior, a crafted HEIF sequence file where the saiz box declares more samples than actually exist in the track's chunk table causes a heap-buffer-overflow (out-of-bounds read) in the SampleAuxInfoReader constructor. The SampleAuxInfoReader constructor iterates over saiz->get_num_samples() samples but doesn't validate that this count is consistent with the number of chunks in the chunks vector. When saiz declares more samples than the chunks cover, the loop increments current_chunk past chunks.size(), causing an out-of-bounds read on the chunks vector. The vulnerability is triggered during file parsing (heif_context_read_from_file) without any additional user interaction. Any application using libheif to open untrusted HEIF files is affected. This issue has been fixed in version 1.22.0.

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🚨 CVE-2026-41073
RT is an open source, enterprise-grade issue and ticket tracking system. Versions prior to 5.0.10 and 6.0.0 through 6.0.2 contain a spreadsheet (CSV/formula) injection vulnerability. User-controlled data in spreadsheet exports is not sanitized before being written to the output file, which can cause spreadsheet applications to interpret crafted values as formulas or macros when the file is opened. This issue has been fixed in versions 5.0.10 and 6.0.3. If developers are unable to upgrade immediately, they can temporarily work around this issue by avoiding opening exported RT spreadsheet files directly in spreadsheet applications when the data may contain untrusted user input.

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🚨 CVE-2026-41074
RT is an open source, enterprise-grade issue and ticket tracking system. Versions 6.0.0 through 6.0.2 contain a Cross-Site Request Forgery (CSRF) vulnerability. An attacker who can induce a logged-in RT user to visit a malicious web page can trigger arbitrary state-changing actions in RT on that user's behalf. This issue has been fixed in version 6.0.3.

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🚨 CVE-2026-41075
RT is an open source, enterprise-grade issue and ticket tracking system. Versions 5.0.0 through 5.0.9 and 6.0.0 through 6.0.2 contain an SQL injection vulnerability. An authenticated user can craft input that is incorporated into database queries without proper validation, potentially allowing them to read or modify data in the RT database. This issue has been fixed in versions 5.0.10 and 6.0.3. If developers are unable to upgrade immediately, they can temporarily work around this issue by restricting RT account access to trusted users.

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🚨 CVE-2026-41076
RT is an open source, enterprise-grade issue and ticket tracking system. Versions 5.0.9 and prior in addition to 6.0.0 through 6.0.2 contain an authentication bypass vulnerability in RT installations that use LDAP/AD for user authentication. Under certain LDAP server configurations, an attacker may be able to authenticate as any LDAP-backed RT user without supplying valid credentials. This issue has been fixed in versions 5.0.10 and 6.0.3. If developers are unable to upgrade immediately, they can temporarily work around this issue by reviewing their LDAP server's authentication policy to ensure it rejects unauthenticated bind attempts. Upgrading RT remains the recommended fix.

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🚨 CVE-2026-23652
Improper neutralization of special elements used in a command ('command injection') in Microsoft Power Pages allows an unauthorized attacker to execute code over a network.

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🚨 CVE-2026-23663
Improper privilege management in Azure Entra ID allows an unauthorized attacker to elevate privileges over a network.

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🚨 CVE-2026-26147
Improper input validation in Azure Compute Gallery allows an authorized attacker to disclose information over a network.

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🚨 CVE-2026-33843
Authentication bypass using an alternate path or channel in Microsoft Azure Active Directory B2C allows an unauthorized attacker to elevate privileges over a network.

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🚨 CVE-2026-35430
Authorization bypass through user-controlled key in Azure Privileged Identity Management (PIM) allows an authorized attacker to elevate privileges over a network.

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🚨 CVE-2026-40411
Improper input validation in Azure Virtual Network Gateway allows an authorized attacker to execute code over a network.

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🚨 CVE-2026-40412
Unrestricted upload of file with dangerous type in Azure Orbital Spatio allows an unauthorized attacker to execute code over a network.

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🚨 CVE-2026-41090
Improper neutralization of special elements used in a command ('command injection') in Microsoft Copilot allows an unauthorized attacker to perform tampering over a network.

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🚨 CVE-2026-41104
Deserialization of untrusted data in Microsoft Planetary Computer Pro allows an unauthorized attacker to disclose information over a network.

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🚨 CVE-2026-41148
Mermaid is a JavaScript tool that uses Markdown-inspired text to create and modify diagrams and charts. Versions 10.9.5 and prior, in addition to 11.0.0-alpha.1 through 11.12.0 are vulnerable to CSS injection through improper sanitization. The state diagram (and any other diagram type that routes user-controlled style strings through the createCssStyles parser) captures classDef values using an unrestricted regex that matches everything up to a newline. That value then flows unsanitized through addStyleClass() into createCssStyles() and is assigned to style.innerHTML, so a closing brace (}) in the value terminates the generated CSS selector and turns everything after it into a new CSS rule on the page. This enables page defacement, user tracking via url() callbacks, and DOM attribute exfiltration. This issue has been fixed in versions 10.9.6 and 11.15.0. If developers are unable to immediately upgrade, they can work around this issue by setting "securityLevel": "sandbox", which prevents the issue by rendering the mermaid diagram in a sandboxed <iframe>.

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