ghsa

Due to an error in sed command parsing, it was possible to bypass the Claude Code read-only validation and write to arbitrary files on the host system. Users on standard Claude Code auto-update will have received this fix automatically. Users performing manual updates are advised to update to the latest version. Thank you to Adam Chester - SpecterOps for reporting this issue!

### Summary The /v1/chat/completions and /tokenize endpoints allow a `chat_template_kwargs` request parameter that is used in the code before it is properly validated against the chat template. With the right `chat_template_kwargs` parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests ### Details In serving_engine.py, the chat_template_kwargs are unpacked into kwargs passed to chat_utils.py `apply_hf_chat_template` with no validation on the keys or values in that chat_template_kwargs dict. This means they can be used to override optional parameters in the `apply_hf_chat_template` method, such as `tokenize`, changing its default from False to True. https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814 https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610 Both serving_...

### Summary Users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct `ndim` but incorrect `shape` (e.g. hidden dimension is wrong), regardless of whether the model is intended to support such inputs (as defined in the Supported Models page). The issue has existed ever since we added support for image embedding inputs, i.e. #6613 (released in v0.5.5) ### Details Using image embeddings as an example: - For models that support image embedding inputs, the engine crashes when scattering the embeddings to `inputs_embeds` (mismatched shape) - For models that don't support image embedding inputs, the engine crashes when validating the inputs inside `get_input_embeddings` (validation fails). This happens because we only validate `ndim` of the tensor, but not the full shape, in input processor (via `MultiModalDataParser`). ### Impact - Denial of service by crashing the engine ### Mitigation - Use API key to limit access to trusted us...

### Summary A memory corruption vulnerability that leading to a crash (denial-of-service) and potentially remote code execution (RCE) exists in vLLM versions 0.10.2 and later, in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using torch.load() without sufficient validation. Due to a change introduced in PyTorch 2.8.0, sparse tensor integrity checks are disabled by default. As a result, maliciously crafted tensors can bypass internal bounds checks and trigger an out-of-bounds memory write during the call to to_dense(). This memory corruption can crash vLLM and potentially lead to code execution on the server hosting vLLM. ### Details A vulnerability that can lead to RCE from the completions API endpoint exists in vllm, where due to missing checks when loading user-provided tensors, an out-of-bounds write can be triggered. This happens because the default behavior of `torch.load(tensor, weights_only=True)` since py...

Snipe-IT v8.3.4 (build 20218) contains a reflected cross-site scripting (XSS) vulnerability in the CSV Import workflow. When an invalid CSV file is uploaded, the application returns a progress_message value that is rendered as raw HTML in the admin interface. An attacker can intercept and modify the POST /livewire/update request to inject arbitrary HTML or JavaScript into the progress_message. Because the server accepts the modified input without sanitization and reflects it back to the user, arbitrary JavaScript executes in the browser of any authenticated admin who views the import page.

When zx is invoked with --prefer-local=<path>, the CLI creates a symlink named ./node_modules pointing to <path>/node_modules. Due to a logic error in src/cli.ts (linkNodeModules / cleanup), the function returns the target path instead of the alias (symlink path). The later cleanup routine removes what it received, which deletes the target directory itself. Result: zx can delete an external <path>/node_modules outside the current working directory.

A bug in the filesystem traversal fallback path causes fs/diriterate/diriterate.go:Next() to overindex an empty slice when ReadDir returns nil for an empty directory, resulting in a panic (index out of range) and an application crash (denial of service) in OSV-SCALIBR.

### Summary A Markdown front-matter block that contains JavaScript delimiter causes the JS engine in gray-matter library to execute arbitrary code in the Markdown to PDF converter process of **md-to-pdf** library, resulting in remote code execution. ### Details **md-to-pdf** uses the gray-matter library to parse front-matter. Gray-matter exposes a JavaScript engine that, when enabled or triggered by certain front-matter delimiters (e.g. ---js or ---javascript), will evaluate the front-matter contents as JavaScript. If user-supplied Markdown is fed to md-to-pdf and the front-matter contains malicious JS, the converter process will execute that code. ### PoC ``` const { mdToPdf } = require('md-to-pdf'); var payload = '---javascript\n((require("child_process")).execSync("calc.exe"))\n---RCE'; (async () => { await mdToPdf({ content: payload }, { dest: './output.pdf'}); })(); ``` Running the PoC on Windows launches the calculator application, demonstrating arbitrary code execution. #...

## Context A template injection vulnerability exists in LangChain's prompt template system that allows attackers to access Python object internals through template syntax. This vulnerability affects applications that accept **untrusted template strings** (not just template variables) in `ChatPromptTemplate` and related prompt template classes. Templates allow attribute access (`.`) and indexing (`[]`) but not method invocation (`()`). The combination of attribute access and indexing may enable exploitation depending on which objects are passed to templates. When template variables are simple strings (the common case), the impact is limited. However, when using `MessagesPlaceholder` with chat message objects, attackers can traverse through object attributes and dictionary lookups (e.g., `__globals__`) to reach sensitive data such as environment variables. The vulnerability specifically requires that applications accept **template strings** (the structure) from untrusted sources, not...

### Summary The public SenderContext Seal() API has a race condition which allows for the same AEAD nonce to be re-used for multiple Seal() calls. This can lead to complete loss of Confidentiality and Integrity of the produced messages. ### Details The SenderContext Seal() [implementation](https://github.com/dajiaji/hpke-js/blob/b7fd3592c7c08660c98289d67c6bb7f891af75c4/packages/core/src/senderContext.ts#L22-L34) allows for concurrent executions to trigger `computeNonce()` with the same sequence number. This results in the same nonce being used in the suite's AEAD. ### PoC This code reproduces the issue (and also checks for more things that could be wrong with the implementation). ```js import { CipherSuite, KdfId, AeadId, KemId } from "hpke-js"; const suite = new CipherSuite({ kem: KemId.DhkemP256HkdfSha256, kdf: KdfId.HkdfSha256, aead: AeadId.Aes128Gcm, }); const keypair = await suite.kem.generateKeyPair(); const skR = keypair.privateKey; const pkR = keypair.publicKey; ...