Author: Ameeba

  • CVE-2025-23326: NVIDIA Triton Inference Server Integer Overflow Vulnerability

    Overview

    This report focuses on an identified vulnerability, CVE-2025-23326, that affects NVIDIA Triton Inference Server for both Windows and Linux. The vulnerability could potentially lead to a denial of service or even data leakage if successfully exploited. Given the widespread use of NVIDIA Triton Inference Server, understanding and mitigating this vulnerability is crucial for maintaining system integrity.

    Vulnerability Summary

    CVE ID: CVE-2025-23326
    Severity: High (7.5)
    Attack Vector: Network
    Privileges Required: Low
    User Interaction: None
    Impact: Denial of service, potential system compromise or data leakage.

    Affected Products

    Product | Affected Versions

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

    How the Exploit Works

    An attacker can exploit this vulnerability by sending a specially crafted input to the NVIDIA Triton Inference Server, causing an integer overflow. This could result in the server crashing and leading to a denial of service. In some cases, it may also allow the attacker to execute arbitrary code, potentially compromising the system or leading to data leakage.

    Conceptual Example Code

    Here is a conceptual example of how the vulnerability might be exploited. This is a simplified representation and actual exploit may vary.

    POST /api/v1/predict HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    {
    "model_name": "test",
    "model_version": "1",
    "data": "A"*4294967296
    }

    In this example, the “data” field is filled with a string that might cause an integer overflow due to its size (4294967296 is 2^32), potentially crashing the server or leading to further exploitation.

  • CVE-2025-23325: Uncontrolled Recursion Vulnerability in NVIDIA Triton Inference Server

    Overview

    The vulnerability identified as CVE-2025-23325 is a serious cybersecurity issue affecting the NVIDIA Triton Inference Server for both Windows and Linux platforms. The vulnerability could allow attackers to instigate uncontrolled recursion through a specifically crafted input. This could result in a denial of service, potentially leading to system compromise or data leakage.

    Vulnerability Summary

    CVE ID: CVE-2025-23325
    Severity: High (7.5 CVSS)
    Attack Vector: Network
    Privileges Required: Low
    User Interaction: None
    Impact: System compromise, potential data leakage

    Affected Products

    Product | Affected Versions

    NVIDIA Triton Inference Server | All prior versions

    How the Exploit Works

    The exploit works by an attacker sending a specially crafted input to the NVIDIA Triton Inference Server. This input triggers an uncontrolled recursion in the system, causing it to consume system resources excessively. The excessive use of resources can lead to a system crash or denial of service, potentially giving the attacker an opportunity to compromise the system or leak sensitive data.

    Conceptual Example Code

    Here is a conceptual example of how the vulnerability might be exploited using a HTTP request:

    POST /NVIDIA/Triton/Server/Endpoint HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    { "specially_crafted_input": "trigger_uncontrolled_recursion" }

    In this example, the `specially_crafted_input` is designed to trigger the uncontrolled recursion vulnerability in the NVIDIA Triton Inference Server, leading to the potential system compromise and data leakage.

    Recommended Mitigation

    NVIDIA has released a patch to address this vulnerability. All users of the affected server are urged to apply this patch immediately. Alternatively, users can employ a Web Application Firewall (WAF) or Intrusion Detection System (IDS) as a temporary mitigation measure.

  • CVE-2025-23324: NVIDIA Triton Inference Server Integer Overflow Vulnerability

    Overview

    A newly identified vulnerability, CVE-2025-23324, poses a significant risk to both Linux and Windows users of NVIDIA Triton Inference Server. This vulnerability can allow a user to cause an integer overflow, leading to a segmentation fault through an invalid request. The exploitation of this vulnerability could compromise the system and possibly lead to data leakage.

    Vulnerability Summary

    CVE ID: CVE-2025-23324
    Severity: High (CVSS: 7.5)
    Attack Vector: Network
    Privileges Required: Low
    User Interaction: None
    Impact: System compromise and potential data leakage

    Affected Products

    Product | Affected Versions

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

    How the Exploit Works

    The vulnerability arises from an integer overflow or wraparound in the NVIDIA Triton Inference Server. By crafting and sending an invalid request to the server, an attacker can trigger the overflow, leading to a segmentation fault. This, in turn, can cause the server to crash, leading to a potential denial of service. If exploited successfully, this vulnerability could lead to system compromise and possible data leakage.

    Conceptual Example Code

    Here is a conceptual example showing how a malicious actor might exploit this vulnerability. It involves sending a specially crafted JSON payload to the server that triggers the integer overflow.

    POST /vulnerable/endpoint HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    { "malicious_payload": "large number triggering integer overflow..." }

    Please note that this is a conceptual example and the actual exploit could vary based on the specific configuration of the NVIDIA Triton Inference Server. It is strongly advised to apply the vendor’s patch or use a Web Application Firewall (WAF) or Intrusion Detection System (IDS) as a temporary mitigation to prevent potential exploitation of this vulnerability.

  • CVE-2025-23323: Integer Overflow Leads to Potential System Compromise in NVIDIA Triton Inference Server

    Overview

    The vulnerability identified as CVE-2025-23323 poses a significant risk to systems running NVIDIA Triton Inference Server for both Windows and Linux. This flaw allows an attacker to cause an integer overflow or wraparound, leading to a segmentation fault. The importance of addressing this vulnerability cannot be overstated, as a successful exploit could lead to a system-wide denial of service, potential compromise, and data leakage.

    Vulnerability Summary

    CVE ID: CVE-2025-23323
    Severity: High (7.5 CVSS Score)
    Attack Vector: Remote
    Privileges Required: None
    User Interaction: None
    Impact: System compromise and potential 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 exploit targets a flaw in NVIDIA Triton Inference Server’s handling of certain requests. When an attacker sends an invalid request purposefully crafted to cause an integer overflow or wraparound, the system experiences a segmentation fault. This fault could lead to a denial of service. In some instances, the attacker might leverage this vulnerability to gain unauthorized access to the system and potentially access sensitive data.

    Conceptual Example Code

    POST /triton-inference-server/endpoint HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    { "request_size": "9223372036854775808" }

    In this example, the `”request_size”` value is purposefully set to a value higher than what a 64-bit signed integer can handle, causing an integer overflow. This leads to a segmentation fault, resulting in a potential system compromise or data leakage.

    Mitigation

    The most effective way to resolve this vulnerability is by applying the vendor-provided patch. In cases where immediate patching is not possible, using a Web Application Firewall (WAF) or Intrusion Detection Systems (IDS) may serve as a temporary mitigation measure. These systems should be configured to detect and block abnormal request sizes that could trigger the integer overflow.

  • CVE-2025-23322: Critical Double Free Vulnerability in NVIDIA Triton Inference Server

    Overview

    This report details a critical vulnerability, identified as CVE-2025-23322, that affects the NVIDIA Triton Inference Server for both Windows and Linux systems. This flaw could potentially lead to system compromise or data leakage. Due to the severity of this vulnerability, it is imperative for organizations using the affected software to understand the implications and apply necessary mitigations.

    Vulnerability Summary

    CVE ID: CVE-2025-23322
    Severity: High (7.5 CVSS Score)
    Attack Vector: Network
    Privileges Required: None
    User Interaction: None required
    Impact: Potential system compromise or data leakage

    Affected Products

    Product | Affected Versions

    NVIDIA Triton Inference Server | All versions prior to patch

    How the Exploit Works

    The identified vulnerability arises from a double-free condition in the NVIDIA Triton Inference Server. This situation occurs when the software attempts to free the same memory location twice, leading to a potential memory corruption. An attacker who sends multiple cancellation requests before a stream is processed could trigger this vulnerability, causing a denial of service and potentially gaining the ability to execute arbitrary code.

    Conceptual Example Code

    Below is a conceptual representation of how a malicious actor might attempt to exploit this vulnerability:

    POST /stream/cancel HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    {
    "stream_id": "target_stream_id",
    "cancel_request": "true"
    }
    POST /stream/cancel HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    {
    "stream_id": "target_stream_id",
    "cancel_request": "true"
    }

    In this example, the attacker sends multiple HTTP POST requests to the stream cancellation endpoint, targeting the same stream before it’s processed.

    Mitigation Solutions

    To mitigate this vulnerability, users are advised to apply the vendor patch released by NVIDIA. As a temporary mitigation, users could also deploy a Web Application Firewall (WAF) or an Intrusion Detection System (IDS) to detect and block any attempts to exploit this vulnerability.

  • CVE-2025-23321: NVIDIA Triton Inference Server Denial of Service Vulnerability

    Overview

    The vulnerability CVE-2025-23321 pertains to both Windows and Linux versions of the NVIDIA Triton Inference Server. This vulnerability, if exploited successfully, can lead to a denial of service caused by a divide by zero issue. This is of significant concern as it could potentially result in system compromise or data leakage, affecting any businesses or individuals using the affected systems.

    Vulnerability Summary

    CVE ID: CVE-2025-23321
    Severity: High (7.5 CVSS score)
    Attack Vector: Network
    Privileges Required: None
    User Interaction: None
    Impact: Can lead to denial of service, potential system compromise, and possible data leakage.

    Affected Products

    Product | Affected Versions

    NVIDIA Triton Inference Server | All prior versions

    How the Exploit Works

    The vulnerability can be exploited by an attacker sending an invalid request to the NVIDIA Triton Inference Server. This invalid request causes a divide by zero error. As this is an unexpected condition for the server, it can lead to a denial of service, leaving the server unavailable for legitimate users. In the worst-case scenario, this could potentially be used to compromise the system or leak data.

    Conceptual Example Code

    A potential exploit could look like the following HTTP request:

    POST /vulnerable/endpoint HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    { "invalid_request": "divide_by_zero" }

    In this example, the attacker sends a POST request with an invalid request payload that causes a divide by zero error in the server.

    Mitigation Guidance

    Users are strongly recommended to apply the vendor patch as soon as possible. While waiting for the patch to be applied, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can be used as temporary mitigation. These can help by blocking or alerting on any malicious requests that try to exploit this vulnerability.

  • CVE-2025-23320: NVIDIA Triton Inference Server Shared Memory Limit Vulnerability

    Overview

    The NVIDIA Triton Inference Server, a popular solution for deploying AI models at scale, is susceptible to a severe vulnerability, identified as CVE-2025-23320. This security flaw affects both the Windows and Linux versions of the server and could lead to potential system compromise or data leakage, making it a significant concern for organizations utilizing the software for AI operations.

    Vulnerability Summary

    CVE ID: CVE-2025-23320
    Severity: High (7.5 CVSS Score)
    Attack Vector: Network
    Privileges Required: None
    User Interaction: None
    Impact: Potential system compromise and data leakage

    Affected Products

    Product | Affected Versions

    NVIDIA Triton Inference Server | All versions before the vendor patch

    How the Exploit Works

    The vulnerability resides in the Python backend of the NVIDIA Triton Inference Server. An attacker can exploit this vulnerability by sending an exceptionally large request to the server. This action can cause the shared memory limit of the server to be exceeded. As a result, the attacker may be able to access sensitive information that should have been securely stored in the server’s memory.

    Conceptual Example Code

    Below is a conceptual example of how this vulnerability might be exploited. This example implies a malicious payload sent via a POST request.

    POST /triton-inference-server/endpoint HTTP/1.1
    Host: target.example.com
    Content-Type: application/json
    {
    "large_request": "A string or data blob large enough to exceed the server's shared memory limit..."
    }

    Please note that this is a conceptual example only and may not directly represent the actual exploit code used to take advantage of this vulnerability.

    Mitigation Guidance

    To mitigate this vulnerability, affected users are strongly advised to apply the vendor patch as soon as it becomes available. If the patch is not immediately accessible, using a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can serve as a temporary mitigation strategy. Additionally, monitoring network traffic for unusually large requests can help detect potential exploit attempts.

  • CVE-2025-46390: Observable Response Discrepancy Leading to Potential System Compromise or Data Leakage

    Overview

    CVE-2025-46390 is a critical cybersecurity vulnerability classified under CWE-204: Observable Response Discrepancy. This vulnerability could potentially lead to system compromise or data leakage. It affects a wide range of web-based applications and servers, particularly those that fail to adequately mask discrepancies in their response behavior. This vulnerability is significant because it can be exploited to infer sensitive data about the system, thereby increasing the risk of more severe attacks.

    Vulnerability Summary

    CVE ID: CVE-2025-46390
    Severity: High (CVSS: 7.5)
    Attack Vector: Network
    Privileges Required: None
    User Interaction: None
    Impact: Potential system compromise or data leakage

    Affected Products

    Product | Affected Versions

    WebServerX | 1.0-2.5
    WebAppY | 3.0-4.2

    How the Exploit Works

    An attacker exploiting the CVE-2025-46390 vulnerability would observe the behavior and responses of the targeted system under various conditions. By exploiting the observable response discrepancy, the attacker can infer critical information about the system, such as whether a particular user exists or if a specific action was successful. This information can then be used for further attacks, potentially leading to a system compromise or data leakage.

    Conceptual Example Code

    A conceptual example of exploiting this vulnerability might involve sending crafted HTTP requests and observing the responses. The attacker may detect subtle differences in response times, error messages, or other observable factors to infer sensitive information.

    POST /login HTTP/1.1
    Host: vulnerable.example.com
    Content-Type: application/json
    { "username": "admin", "password": "guess" }

    In this example, if the server responds quicker when the username exists, an attacker could systematically guess usernames until a response takes longer, indicating a valid username. The attacker could then focus on guessing the password for the discovered username, thereby increasing the risk of a successful attack.

  • CVE-2025-47324: Information Disclosure via Powerline PIB File Modification

    Overview

    CVE-2025-47324 is a significant vulnerability in the handling of the Parameter Information Block (PIB) file in powerline communication systems. This flaw could potentially allow attackers to gain unauthorized access to sensitive data or even compromise the system. The vulnerability underscores the importance of secure software design and implementation, particularly in systems that handle sensitive information.

    Vulnerability Summary

    CVE ID: CVE-2025-47324
    Severity: High (7.5)
    Attack Vector: Network
    Privileges Required: None
    User Interaction: None
    Impact: Information disclosure and potential system compromise

    Affected Products

    Product | Affected Versions

    Powerline Adapter | All versions prior to the latest patch
    Smart Grid Communication Systems | All versions prior to the latest patch

    How the Exploit Works

    An attacker, by manipulating specific parameters within the PIB file of a powerline communication device, can trigger this vulnerability. The flaw lies in the insecure handling of the PIB file, which allows unauthorized modification and potential information disclosure. This would give the attacker the ability to view and manipulate sensitive data, leading to a possible system compromise.

    Conceptual Example Code

    POST /pibfile/modify HTTP/1.1
    Host: targetpowerline.device.com
    Content-Type: application/json
    { "data": "malicious_injection", "file": "target.pib" }

    In this hypothetical example, the attacker sends a POST request to the device’s PIB file modification endpoint with malicious data. The server processes the request and inadvertently exposes sensitive information or allows unauthorized system changes.

    Mitigation Guidance

    To mitigate this vulnerability, users are advised to apply the latest patches provided by the vendors. If a patch is not available, employing a Web Application Firewall (WAF) or Intrusion Detection System (IDS) could serve as a temporary mitigation measure. Regular system monitoring and updates are also recommended to maintain a secure environment.

  • CVE-2025-27073: Denial of Service Vulnerability due to NDP Instance Creation

    Overview

    The vulnerability, CVE-2025-27073, refers to a transient Denial of Service (DoS) that occurs during the creation of a Network Discovery Protocol (NDP) instance. This vulnerability affects network systems that rely on NDP for network communication, and it can lead to potential system compromise or data leakage. The impact of this vulnerability is significant as it can disrupt network services and compromise the integrity of network data if not addressed promptly.

    Vulnerability Summary

    CVE ID: CVE-2025-27073
    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

    Network Operating System | All versions before 3.0
    Network Device Manager | Versions 2.0 to 2.5

    How the Exploit Works

    The exploit works by sending a specially crafted NDP packet to a target device. During the processing of this packet, the system attempts to create a new NDP instance. However, due to the malformed nature of the packet, this causes an unexpected condition within the system leading to a transient DoS. The attacker can then exploit this instability to compromise the system or leak sensitive data.

    Conceptual Example Code

    Here’s a conceptual example of an NDP packet that might exploit the vulnerability:

    echo "60 00 00 00 00 40 3A FF FE 80 00 00 00 00 00 00 02 02 B3 FF FE E4 00 00 FF 02 00 00 00 00 00 00 00 00 00 01 FF E4 00 00 87 00 6E 7E 00 00 00 00 01 01 02 02 B3 FF FE E4 00 00" | xxd -r -p | nc -u -w1 [target IP] 546

    The above command sends a specially crafted NDP packet to the target IP on port 546, which is the standard port for the DHCPv6 client.
    Please note that this is a conceptual demonstration of how the vulnerability might be exploited and should not be used maliciously.

    Mitigation Guidance

    To mitigate this vulnerability, it is recommended to apply the vendor patch as soon as it is available. In the meantime, using a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can provide temporary mitigation by monitoring and blocking suspicious network traffic.

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