Author: Ameeba

Overview

This report details a significant vulnerability, identified as CVE-2025-26515, that affects previous versions of StorageGRID prior to 11.8.0.15 and 11.9.0.8 without Single Sign-On enabled. This vulnerability poses a serious threat as it can potentially allow an unauthenticated attacker to alter the password of any non-federated Grid Manager or Tenant Manager user. The severity of this vulnerability is underscored by its potential to compromise systems and lead to data leakage.

Vulnerability Summary

CVE ID: CVE-2025-26515
Severity: High, CVSS score: 7.5
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: System compromise and potential data leakage

Affected Products

Product | Affected Versions

StorageGRID | versions prior to 11.8.0.15
StorageGRID Webscale | versions prior to 11.9.0.8

How the Exploit Works

This exploit takes advantage of a Server-Side Request Forgery (SSRF) vulnerability in StorageGRID. By sending a maliciously crafted request, an unauthenticated attacker can trick the server into changing the password of any non-federated Grid Manager or Tenant Manager user. This could potentially allow the attacker to gain unauthorized access to the system and possibly leak sensitive data.

Conceptual Example Code

Below is a conceptual example of how the vulnerability might be exploited. The attacker sends a malicious HTTP POST request, targeting the password change function of the server.

POST /api/change_password HTTP/1.1
Host: target.example.com
Content-Type: application/json
{
"username": "victim_user",
"new_password": "attacker_password"
}

In this example, `victim_user` would be the username of the targeted Grid Manager or Tenant Manager user and `attacker_password` would be the new password set by the attacker.

Overview

This report details the cybersecurity vulnerability known as CVE-2025-10468, which is an improper limitation of a pathname to a restricted directory, or ‘Path Traversal’, vulnerability that affects the software product CityPlus by Beyaz Computer. This vulnerability is of significant concern as it could lead to potential system compromise or data leakage, thereby posing a risk to the confidentiality, integrity, and availability of the affected systems.

Vulnerability Summary

CVE ID: CVE-2025-10468
Severity: High (CVSS: 7.5)
Attack Vector: Network
Privileges Required: None
User Interaction: Required
Impact: Potential system compromise or data leakage

Affected Products

Product | Affected Versions

CityPlus | Before 24.29375

How the Exploit Works

The CVE-2025-10468 vulnerability allows a malicious actor to traverse the file directory stored within CityPlus software due to insufficient security restrictions. This vulnerability can be exploited when the software fails to sufficiently sanitize user-supplied input before using it in file system operations. An attacker could manipulate file and directory paths to navigate out of the intended directory structure to access files or directories that are outside of the restricted directory.

Conceptual Example Code

Here is a conceptual example demonstrating how an HTTP request might be crafted to exploit this vulnerability:

GET /file?filename=../../../etc/passwd HTTP/1.1
Host: vulnerable.cityplus.com
Content-Type: application/json

In this example, the attacker is attempting to traverse the directory to access a sensitive file (`/etc/passwd`) that resides outside of the intended directory structure.

Mitigation

To mitigate this vulnerability, it is advised to apply the vendor’s patch for CityPlus versions before 24.29375. In situations where applying the patch is not immediately possible, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can serve as a temporary mitigation measure, providing some level of protection by detecting and blocking path traversal attempts.

Overview

The vulnerability CVE-2025-23329 is a critical issue affecting the NVIDIA Triton Inference Server for both Windows and Linux systems. This vulnerability allows an attacker to cause memory corruption by identifying and accessing the shared memory region used by the Python backend, which can potentially lead to a system compromise or data leakage. It is a significant concern for organizations utilizing the NVIDIA Triton Inference Server due to its high CVSS severity score and potential impact.

Vulnerability Summary

CVE ID: CVE-2025-23329
Severity: High – CVSS Score 7.5
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: Potential system compromise or data leakage

Affected Products

Product | Affected Versions

NVIDIA Triton Inference Server for Windows | All versions prior to the patched version
NVIDIA Triton Inference Server for Linux | All versions prior to the patched version

How the Exploit Works

The exploit takes advantage of a flaw in the NVIDIA Triton Inference Server’s handling of shared memory regions utilized by the Python backend. An attacker can identify and access this shared memory region, causing memory corruption. If executed successfully, this could lead to a denial of service, system compromise, or data leakage.

Conceptual Example Code

Here’s a conceptual example of how the vulnerability might be exploited:

# Python pseudocode for a potential exploit
import os
# Identify shared memory region
shmem_id = os.shmget(key, size, flags)
# Access and corrupt the shared memory region
shmem_address = os.shmat(shmem_id, None, flags)
os.write(shmem_address, malicious_data)

The above example is very simplified and does not represent a real-world exploit. It is only intended to illustrate the nature of the vulnerability. In real-world conditions, exploiting this vulnerability would likely involve complex and sophisticated code.

Recommendations

Users are strongly advised to apply the vendor-provided patch to mitigate this vulnerability. Until the patch can be applied, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can be used as a temporary mitigation. Regularly updating and patching software is crucial in maintaining a secure environment.

Overview

The NVIDIA Triton Inference Server, a popular choice for both Windows and Linux environments, has been identified as having a security vulnerability, CVE-2025-23328. This vulnerability could allow an attacker to cause an out-of-bounds write through specially crafted input, leading to a potential denial of service. This vulnerability is critical as it affects a widely used server, and if exploited, could result in system compromise or data leakage.

Vulnerability Summary

CVE ID: CVE-2025-23328
Severity: High (7.5 CVSS)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: Denial of service, potential system compromise, and data leakage

Affected Products

Product | Affected Versions

NVIDIA Triton Inference Server for Windows | All versions prior to patch
NVIDIA Triton Inference Server for Linux | All versions prior to patch

How the Exploit Works

The vulnerability is exploited when an attacker sends specially crafted input to the NVIDIA Triton Inference Server. The server fails to properly handle this input, leading to an out-of-bounds write. This could cause the server to crash, leading to a denial of service. Moreover, it may also allow an attacker to execute arbitrary code or access sensitive information, leading to potential system compromise or data leakage.

Conceptual Example Code

Below is a conceptual example of how this vulnerability might be exploited, using a hypothetical malicious payload in a network request:

POST /api/v1/inference HTTP/1.1
Host: target.example.com
Content-Type: application/json
{ "data": "AAA...[long string]...AAA" } // Overly long string causing out-of-bounds write

Here, the attacker sends a POST request with a long string in the ‘data’ field. The NVIDIA Triton Inference Server fails to handle this input properly, leading to out-of-bounds write and triggering the vulnerability.

Overview

This report focuses on the CVE-2025-59353 vulnerability that affects the Dragonfly P2P file distribution and image acceleration system. This vulnerability is particularly concerning as it could allow a peer to obtain a valid TLS certificate for arbitrary IP addresses, potentially compromising the system or leading to data leakage. Understanding and addressing this issue is essential for any organization utilizing the Dragonfly system.

Vulnerability Summary

CVE ID: CVE-2025-59353
Severity: High (7.5)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: Potential system compromise leading to data leakage

Affected Products

Product | Affected Versions

Dragonfly | Prior to 2.1.0

How the Exploit Works

The vulnerability stems from the Dragonfly Manager’s Certificate gRPC service’s failure to validate whether the requested IP addresses are owned by the peer requesting the certificate. This means a peer connecting from one IP address can request a certificate for a different IP address. The result is that the peer can obtain a valid TLS certificate for arbitrary IP addresses, which essentially nullifies the mTLS authentication.

Conceptual Example Code

This vulnerability does not require a specific code to exploit but is more related to the misuse of the certificate request system. A malicious user might perform something like this:

$ grpcurl -d '{"addresses":["malicious.ip.address"]}’ dragonfly-manager.example.com:443 API.GenerateCertificate

In this example, “malicious.ip.address” is an IP address that the attacker does not own but can now use to connect to the network as a legitimate peer, bypassing mTLS authentication.

Mitigation Guidance

It is strongly recommended to upgrade to Dragonfly version 2.1.0 or later, where this vulnerability has been fixed. If an immediate upgrade is not possible, implementing a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can serve as a temporary mitigation strategy. However, these should not be considered long-term solutions, as they cannot fully prevent exploitation of this vulnerability.

Overview

The vulnerability identified as CVE-2025-59348 is a critical flaw in Dragonfly, an open-source peer-to-peer file distribution and image acceleration system. This vulnerability affects versions prior to 2.1.0 and may result in a denial-of-service condition for the peer, ultimately leading to potential system compromise or data leakage. Its importance lies in its potential to disrupt services and compromise sensitive information, affecting both individual users and organizations.

Vulnerability Summary

CVE ID: CVE-2025-59348
Severity: High (7.5 CVSS)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: Denial-of-Service, potential system compromise or data leakage

Affected Products

Product | Affected Versions

Dragonfly P2P System | < 2.1.0 How the Exploit Works

The exploit capitalizes on the fact that the processPieceFromSource method does not update the structure’s usedTraffic field. This is due to the use of an uninitialized variable ‘n’ as a guard to the AddTraffic method call, instead of the ‘result.Size’ variable. Consequently, a task processed by a peer does not update the usedTraffic metadata during the processing, leading to incorrect application of rate limiting. This results in a denial-of-service condition for the peer.

Conceptual Example Code

A conceptual example might involve a peer sending a large number of requests to the vulnerable system, exhausting resources due to the incorrect application of rate limiting:

POST /dragonfly/processPieceFromSource HTTP/1.1
Host: target.example.com
Content-Type: application/json
{ "taskID": "12345", "peerID": "67890", "requestCount": "1000000" }

In the above example, ‘requestCount’ is arbitrarily large, intending to trigger the rate limit handling flaw. Please note that this is a conceptual example and may not directly apply to the actual software.

Mitigation Guidance

Users are advised to apply the vendor-provided patch and upgrade to version 2.1.0 which has addressed this vulnerability. If an immediate update is not feasible, employing a Web Application Firewall (WAF) or Intrusion Detection System (IDS) could serve as a temporary mitigation. However, these solutions are not permanent fixes and only provide limited protection against potential exploitation.

Overview

This report discusses a significant vulnerability, CVE-2025-58767, found in the REXML Ruby XML toolkit. This vulnerability affects versions 3.3.3 to 3.4.1 of the REXML gems and is of particular concern for those parsing untrusted XMLs. The vulnerability could lead to potential system compromise or data leakage, highlighting the critical nature of this issue.

Vulnerability Summary

CVE ID: CVE-2025-58767
Severity: High (7.5 CVSS)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: System compromise and potential data leakage

Affected Products

Product | Affected Versions

REXML Ruby XML Toolkit | 3.3.3 to 3.4.1

How the Exploit Works

The exploit takes advantage of a flaw in REXML’s parsing mechanism. Specifically, when the toolkit encounters XML containing multiple XML declarations, a denial of service (DoS) vulnerability is triggered. This vulnerability allows an attacker to overwhelm the system, potentially leading to system compromise and data leakage.

Conceptual Example Code

An attacker could exploit the vulnerability by sending a specially crafted XML file with multiple XML declarations. The conceptual example of a malicious payload might look like this:

<?xml version="1.0"?>
<?xml version="1.0"?>
<root>
<element>Malicious Content</element>
</root>

By sending this XML to an application that uses affected versions of REXML for parsing, an attacker could trigger the DoS condition and potentially compromise the system.

Mitigation Guidance

To mitigate this vulnerability, users are advised to apply the vendor supplied patch by upgrading to REXML gem version 3.4.2 or later, which includes fixes for these vulnerabilities. As a temporary mitigation, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) could be used to block or identify malicious XML traffic.

Overview

This report covers a critical vulnerability in the Apache::AuthAny::Cookie module for Perl. The flaw lies in the insecure generation of session ids, which could be leveraged by an attacker to gain unauthorized access to systems. Anyone using version 0.201 or earlier of this module is vulnerable, and due to the potential for system compromise or data leakage, it is crucial that this issue is addressed promptly.

Vulnerability Summary

CVE ID: CVE-2025-40933
Severity: High (7.5)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: System compromise or data leakage

Affected Products

Product | Affected Versions

Apache::AuthAny::Cookie for Perl | 0.201 or earlier

How the Exploit Works

An attacker can exploit this vulnerability by predicting the session ids generated by the module. The module generates these ids using an MD5 hash of the epoch time and a call to the built-in rand function. The epoch time may be guessed, especially if leaked from the HTTP Date header. The built-in rand function is not cryptographically secure, making this process even more vulnerable. Predictable session ids could allow an attacker to hijack sessions and gain unauthorized access to the system.

Conceptual Example Code

The following pseudocode illustrates how an attacker might predict a session id:

import time
import hashlib
# Guess the epoch time
epoch_time = int(time.time())
# Guess the value from the rand function
rand_val = 12345  # This value is usually not secure
# Generate the session id
session_id = hashlib.md5(str(epoch_time) + str(rand_val)).hexdigest()
print("Predicted session id: " + session_id)

In the actual attack, the attacker would use this predicted session id to impersonate a valid user in the system.

Mitigation

To mitigate this vulnerability, it is recommended to apply the patch provided by the vendor. In the absence of a patch, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can be used as a temporary mitigation measure. However, these options do not address the root cause of the vulnerability and should be considered short-term solutions.

Overview

This report details a significant vulnerability identified in the Catch Dark Mode plugin for WordPress. This vulnerability, labelled as CVE-2025-10143, potentially allows authenticated attackers, with Contributor-level access and above, to include and execute arbitrary .php files on the server, leading to potential system compromise or data leakage. This is a serious security risk for any organizations or individuals using affected versions of the plugin on their WordPress sites.

Vulnerability Summary

CVE ID: CVE-2025-10143
Severity: High (CVSS 7.5)
Attack Vector: Local File Inclusion
Privileges Required: Contributor-level access
User Interaction: Required
Impact: Potential system compromise or data leakage

Affected Products

Product | Affected Versions

Catch Dark Mode WordPress Plugin | All versions up to and including 2.0

How the Exploit Works

The vulnerability lies in the ‘catch_dark_mode’ shortcode of the Catch Dark Mode plugin. Attackers with at least Contributor-level access can exploit this vulnerability by including arbitrary .php files via the shortcode. Since the shortcode does not properly sanitize or validate the included files, this allows the execution of any PHP code in those files. Consequently, attackers can bypass access controls, obtain sensitive data, or achieve code execution in cases where .php file types can be uploaded and included.

Conceptual Example Code

The following pseudocode exemplifies how an attacker might exploit this vulnerability:

catch_dark_mode('[include] /path/to/malicious.php [/include]');

In this example, ‘malicious.php’ is an arbitrary PHP file that the attacker has uploaded to the server. When the Catch Dark Mode plugin processes the shortcode, it includes and executes the code in ‘malicious.php’, leading to potential system compromise or data leakage.

Overview

A major broken access control vulnerability has been identified in HPE Aruba Networking EdgeConnect OS (ECOS). This vulnerability has the potential to impact numerous businesses and network users who use this OS. If exploited successfully, it could allow unauthorized traffic to bypass firewall protections, leading to possible system compromises or data leaks.

Vulnerability Summary

CVE ID: CVE-2025-37125
Severity: High (7.5 CVSS Score)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: System compromise or data leakage

Affected Products

Product | Affected Versions

HPE Aruba Networking EdgeConnect OS | All versions prior to patch

How the Exploit Works

The attacker, by exploiting this broken access control vulnerability, can manipulate the process of how the firewall rules are applied in the EdgeConnect OS. This can potentially allow the attacker to route malicious traffic through the network, bypassing firewall protections and normal security checks. This could lead to unauthorized access to sensitive data or even full system compromise.

Conceptual Example Code

The following conceptual example showcases how an attacker might send malicious requests to a vulnerable endpoint:

POST /firewall/rule/bypass HTTP/1.1
Host: target.example.com
Content-Type: application/json
{
"new_rule": {
"rule_id": "1",
"action": "bypass",
"traffic_type": "all"
}
}

In this example, the attacker is attempting to create a new firewall rule that bypasses all traffic, effectively negating the firewall’s protection.

Mitigation Guidance

Users of HPE Aruba Networking EdgeConnect OS are advised to apply the latest vendor patches as soon as possible. If unable to patch immediately, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can be employed as a temporary mitigation measure to detect and block potential exploit attempts.