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You’ve trained the model, packaged it on Red Hat OpenShift AI, and it’s ready to work. The next move is exposing it through an API so people and applications can use it. At that moment, your model stops being an internal experiment and becomes a front-door service. And like any front door, somebody is going to knock … sometimes it’s the right user, sometimes not.Your model is no longer just a project in a lab: it’s a production endpoint. And like any endpoint, it’s a target. How do you ensure that only the right applications and users are interacting with it? How do you protect the

A cybercriminal group that used voice phishing attacks to siphon more than a billion records from Salesforce customers earlier this year has launched a website that threatens to publish data stolen from dozens of Fortune 500 firms if they refuse to pay a ransom. The group also claimed responsibility for a recent breach involving Discord user data, and for stealing terabytes of sensitive files from thousands of customers of the enterprise software maker Red Hat.

### Summary `Deno.FsFile.prototype.utime` and `Deno.FsFile.prototype.utimeSync` are not limited by the permission model check `--deny-write=./`. It's possible to change to change the access (`atime`) and modification (`mtime`) times on the file stream resource even when the file is opened with `read` only permission (and `write`: `false`) and file write operations are not allowed (the script is executed with `--deny-write=./`). Similar APIs like `Deno.utime` and `Deno.utimeSync` require `allow-write` permission, however, when a file is opened, even with read only flags and deny-write permission, it's still possible to change the access (`atime`) and modification (`mtime`) times, and thus bypass the permission model. ### PoC Setup: ``` deno --version deno 2.4.2 (stable, release, x86_64-unknown-linux-gnu) v8 13.7.152.14-rusty typescript 5.8.3 touch test.txt ``` ```js // touch test.txt // https://docs.deno.com/api/deno/~/Deno.FsFile.prototype.utime // deno run --allow-read=./ --den...

### Summary A Server-Side Request Forgery (SSRF) vulnerability exists in the `MediaConnector` class within the vLLM project's multimodal feature set. The `load_from_url` and `load_from_url_async` methods fetch and process media from user-provided URLs without adequate restrictions on the target hosts. This allows an attacker to coerce the vLLM server into making arbitrary requests to internal network resources. This vulnerability is particularly critical in containerized environments like `llm-d`, where a compromised vLLM pod could be used to scan the internal network, interact with other pods, and potentially cause denial of service or access sensitive data. For example, an attacker could make the vLLM pod send malicious requests to an internal `llm-d` management endpoint, leading to system instability by falsely reporting metrics like the KV cache state. ### Vulnerability Details The core of the vulnerability lies in the `MediaConnector.load_from_url` method and its asynchronous ...

## Summary ## A Server-Side Request Forgery (SSRF) vulnerability in the chat API allows any authenticated user to force the server to make arbitrary HTTP requests to internal and external networks. This can lead to the exposure of sensitive internal services, reconnaissance of the internal network, or interaction with third-party services. The same mechanism also allows for a Local File Inclusion (LFI) vulnerability, enabling users to read arbitrary files from the server's filesystem. ## Details ## The vulnerability exists in the _process_request function within src/llamafactory/api/chat.py. This function is responsible for processing incoming multimodal content, including images, videos, and audio provided via URLs. The function checks if the provided URL is a base64 data URI or a local file path (os.path.isfile). If neither is true, it falls back to treating the URL as a web URI and makes a direct HTTP GET request using requests.get(url, stream=True).raw without any validation or...

### Summary A resource-exhaustion (denial-of-service) vulnerability exists in multiple endpoints of the OpenAI-Compatible Server due to the ability to specify Jinja templates via the `chat_template` and `chat_template_kwargs` parameters. If an attacker can supply these parameters to the API, they can cause a service outage by exhausting CPU and/or memory resources. ### Details When using an LLM as a chat model, the conversation history must be rendered into a text input for the model. In `hf/transformer`, this rendering is performed using a Jinja template. The OpenAI-Compatible Server launched by vllm serve exposes a `chat_template` parameter that lets users specify that template. In addition, the server accepts a `chat_template_kwargs` parameter to pass extra keyword arguments to the rendering function. Because Jinja templates support programming-language-like constructs (loops, nested iterations, etc.), a crafted template can consume extremely large amounts of CPU and memory and ...

Researchers report an increase in the use of hidden content in spam and malicious email to confuse filters and other security mechanisms.

### Impact This is a critical network security vulnerability for Akka.Remote **users who have SSL / TLS enabled** on their Akka.Remote connections and were expecting certificate-based authentication to be enforced on all peers attempting to join the network. In all versions of Akka.Remote from v1.2.0 to v1.5.51, TLS could be enabled via our `akka.remote.dot-netty.tcp` transport and this would correctly enforce private key validation on the server-side of inbound connections. Akka.Remote, however, never asked the outbound-connecting client to present ITS certificate - therefore it's possible for untrusted parties to connect to a private key'd Akka.NET cluster and begin communicating with it **without any certificate**. The issue here is that for certificate-based authentication to work properly, ensuring that all members of the Akka.Remote network are secured with the same private key, Akka.Remote needed to implement mutual TLS. This was not the case before Akka.NET v1.5.52. If you...

In a recent poll, readers shared how they're using vibe coding in AppDev (if they are at all). While some found success, others found the risks too great.

Critical Redis flaw RediShell (CVE-2025-49844) exposes 60,000 servers to remote code execution. Patch immediately to prevent full system compromise.