| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Microsoft Word Remote Code Execution Vulnerability |
| Microsoft Word Remote Code Execution Vulnerability |
| Access of resource using incompatible type ('type confusion') in Microsoft Office Word allows an unauthorized attacker to execute code locally. |
| Mattermost versions 11.5.x <= 11.5.1, 10.11.x <= 10.11.13 fail to validate the Host header when constructing response URLs for custom slash commands which allows an authenticated attacker to redirect slash command responses to an attacker-controlled server via a spoofed Host header.. Mattermost Advisory ID: MMSA-2026-00582 |
| AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions 0.1.0 through 0.6.51, SendEmailBlock in autogpt_platform/backend/backend/blocks/email_block.py accepts a user-supplied smtp_server (string) and smtp_port (integer) as per-execution block inputs, then passes them directly to Python's smtplib.SMTP() to open a raw TCP connection with no IP address validation. This completely bypasses the platform's hardened SSRF protections in backend/util/request.py — the validate_url_host() function and BLOCKED_IP_NETWORKS blocklist that every other block uses to block connections to private, loopback, link-local, and cloud metadata addresses. An authenticated user on a shared AutoGPT deployment can use this to perform non-blind internal network port scanning and service fingerprinting: smtplib reads the target's TCP banner on connect and embeds it in the exception message, which is persisted as user-visible block output via the execution framework. This issue has been fixed in version 0.6.52. |
| Script injection in SanitizerAPI in Google Chrome on Android prior to 148.0.7778.168 allowed a remote attacker to inject arbitrary scripts or HTML (UXSS) via a crafted HTML page. (Chromium security severity: High) |
| AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions 0.6.34 through 0.6.51, the backend deserializes Redis cache bytes using pickle.loads without integrity/authenticity checks. The write path serializes values with pickle.dumps(...) into Redis and the read path blindly invokes pickle.loads(...) on bytes with no HMAC/signature or strict schema validation gating deserialization. If an attacker can poison a shared-cache key in Redis, arbitrary command execution is possible in the backend container context, affecting confidentiality, integrity, and availability. This issue has been fixed in version 0.6.52. |
| ws is an open source WebSocket client and server for Node.js. Prior to 8.20.1, the websocket.close() implementation is vulnerable to uninitialized memory disclosure when a TypedArray is passed as the reason argument. This vulnerability is fixed in 8.20.1. |
| Unsafe use of Python's eval() on server-received data in the vector_in() function in amazon-redshift-python-driver before 2.1.14 allows a rogue server or man-in-the-middle actor to execute arbitrary code on the client.
To remediate this issue, users should upgrade to version 2.1.14. |
| A pre-authentication, code injection vulnerability in version 1.0.0 or later of the ChromaDB Python project allows an unauthenticated attacker to run arbitrary code on the server by sending a malicious model repository and trust_remote_code set to true in the /api/v2/tenants/{tenant}/databases/{db}/collections endpoint. |
| Net::Statsd::Lite versions before 0.9.0 for Perl allowed metric injections.
The metric names were not checked for newlines, colons or pipes. Metrics generated from untrusted sources could inject additional statsd metrics. |
| Net::Statsd::Lite versions through 0.10.0 for Perl allowed metric injections.
The values from the set_add method were not checked for newlines, colons or pipes. Metrics generated from untrusted sources could inject additional statsd metrics.
Note that version 0.9.0 fixed a similar issue CVE-2026-46719 for metric names. |
| Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.9.5, the POST /api/v1/evaluations/feedback endpoint in Open WebUI v0.9.2 is vulnerable to mass assignment via FeedbackForm, which uses model_config = ConfigDict(extra='allow'). Due to an insecure dictionary merge order in insert_new_feedback(), an authenticated attacker can inject a user_id field in the request body that overwrites the server-derived value, creating feedback records attributed to any arbitrary user. This corrupts the model evaluation leaderboard (Elo ratings) and enables identity spoofing. This vulnerability is fixed in 0.9.5. |
| Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.9.5, a parsing difference between the urlparse and requests libraries led to an SSRF bypass vulnerability. This vulnerability is fixed in 0.9.5. |
| Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.9.5, the validate_url() function in backend/open_webui/retrieval/web/utils.py only validates the initial URL submitted by the caller. The HTTP clients used downstream (sync requests, async aiohttp, langchain's WebBaseLoader) follow HTTP 3xx redirects by default and do not re-validate the redirect target against the private-IP / metadata-IP block list. Any authenticated user can therefore submit a public URL that 302-redirects to an internal address (e.g. 127.0.0.1, 169.254.169.254, RFC1918) and read the internal response body via the /api/v1/retrieval/process/web endpoint, the /api/v1/images/... endpoints, the /api/chat/completions endpoint with an image_url content part, and any other route that calls these helpers. This vulnerability is fixed in 0.9.5. |
| Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, diffusers 0.37.0 allows remote code execution without the trust_remote_code=True safeguard when loading pipelines from Hugging Face Hub repositories. The _resolve_custom_pipeline_and_cls function in pipeline_loading_utils.py performs string interpolation on the custom_pipeline parameter using f"{custom_pipeline}.py". When custom_pipeline is not supplied by the user, it defaults to None, which Python interpolates as the literal string "None.py". If an attacker publishes a Hub repository containing a file named None.py with a class that subclasses DiffusionPipeline, the file is automatically downloaded and executed during a standard DiffusionPipeline.from_pretrained() call with no additional keyword arguments. The trust_remote_code check in DiffusionPipeline.download() is bypassed because it evaluates custom_pipeline is not None as False (since the kwarg was never supplied), while the downstream code path that actually loads the module resolves the None value into a valid filename. An attacker can achieve silent arbitrary code execution by publishing a malicious model repository with a None.py file and a standard-looking model_index.json that references a legitimate pipeline class name, requiring only that a victim calls from_pretrained on the repository. This vulnerability is fixed in 0.38.0. |
| Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trust_remote_code bypass in DiffusionPipeline.from_pretrained allows arbitrary remote code execution despite the user passing trust_remote_code=False (or omitting it, which is the default). The vulnerability has three variants, all sharing the same root cause — the trust_remote_code gate was implemented inside DiffusionPipeline.download() rather than at the actual dynamic-module load site, so any code path that bypassed or short-circuited download() also bypassed the security check. DiffusionPipeline.from_pretrained('repoA', custom_pipeline='attacker/repoB', trust_remote_code=False) — the gate evaluated against repoA's file list rather than repoB's, so repoB's pipeline.py was loaded and executed. DiffusionPipeline.from_pretrained('/local/snapshot', custom_pipeline='attacker/repoB', trust_remote_code=False) — the local-path branch never invoked download(), so the gate was never reached and remote code from repoB executed. DiffusionPipeline.from_pretrained('/local/snapshot', trust_remote_code=False) where the snapshot contains custom component files (e.g. unet/my_unet_model.py) referenced from model_index.json — same root cause; the local path skipped download() and custom component code executed. This vulnerability is fixed in 0.38.0. |
| Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.9.0, validate_url() in backend/open_webui/retrieval/web/utils.py calls validators.ipv6(ip, private=True), but the validators library does NOT implement the private keyword for IPv6 — the call raises a ValidationError (which is falsy in a boolean context), so every IPv6 address passes the filter. In addition, IPv4-mapped IPv6 (::ffff:10.0.0.1) bypasses the IPv4 check entirely, and several reserved IPv4 ranges (0.0.0.0/8, 100.64.0.0/10, 192.0.0.0/24, etc.) are not blocked. This vulnerability is fixed in 0.9.0. |
| Summarize prior to 0.15.1 contains a vulnerability in the hover summary feature that allows malicious pages to dispatch synthetic mouseover events over attacker-controlled links, causing the extension to make authenticated daemon requests using stored tokens without verifying event trustworthiness. Attackers can place local or private-network URLs behind hoverable links to route authenticated requests through the daemon, potentially accessing sensitive internal endpoints when users interact with attacker-controlled content. |
| Insufficient policy enforcement in ViewTransitions in Google Chrome prior to 148.0.7778.168 allowed a remote attacker to leak cross-origin data via a crafted HTML page. (Chromium security severity: High) |
