Executive Summary:
A high-severity vulnerability has been discovered in the NVIDIA Triton Inference Server, a key component in many AI and machine learning infrastructures. An attacker with local access to an affected system could exploit this flaw to corrupt the server's memory, potentially causing a denial of service by crashing the application or, in a worst-case scenario, allowing the attacker to execute arbitrary code. This could lead to significant service disruption and potential system compromise.

Vulnerability Details

CVE-ID: CVE-2025-23329

Affected Software: NVIDIA Triton Inference Server

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists in the way the NVIDIA Triton Inference Server's Python backend utilizes shared memory. An attacker with local access to the host system can identify the specific shared memory region used by the backend. By writing crafted data to this improperly protected memory region, the attacker can trigger memory corruption within the Triton server process, leading to a crash (Denial of Service) or potentially hijacking the program's execution flow to achieve arbitrary code execution.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. Successful exploitation could have a significant business impact by causing a Denial of Service (DoS) condition, rendering critical AI/ML-powered applications and services unavailable. This disruption could lead to operational downtime, revenue loss, and reputational damage. In the event that an attacker achieves code execution, they could gain control of the server, leading to data theft, intellectual property loss, or lateral movement into the broader corporate network.

Remediation Plan

Immediate Action: The primary and most effective remediation is to apply the security updates provided by NVIDIA to all vulnerable instances of the Triton Inference Server immediately. After patching, organizations should monitor for any signs of post-remediation exploitation attempts and review system and application access logs for any suspicious activity that occurred prior to the patch.

Proactive Monitoring: Security teams should monitor for anomalous process behavior on hosts running Triton, specifically looking for unexpected processes attempting to access memory segments owned by the Triton server. Monitor application logs for unexpected crashes or errors related to the Python backend. Enhanced logging and alerting on local user account activity on these servers can also help detect precursor attack behavior.

Compensating Controls: If patching cannot be performed immediately, organizations should implement compensating controls. Restrict local and shell access to servers running Triton Inference Server to only essential, authorized personnel. Employ host-based security solutions or mandatory access control systems (like SELinux or AppArmor) to enforce stricter process isolation and limit access to shared memory segments.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of the publication date, September 17, 2025, there are no known public proof-of-concept exploits or active exploitation of this vulnerability in the wild. However, given the high-severity rating, it is anticipated that threat actors will analyze the patch to develop exploits. Organizations should treat this as a critical vulnerability requiring prompt attention.

Analyst Recommendation

Due to the high CVSS score and the critical role of the Triton Inference Server in AI/ML pipelines, this vulnerability poses a significant risk to the organization. Although it is not currently listed on the CISA KEV (Known Exploited Vulnerabilities) catalog, the potential for Denial of Service and arbitrary code execution warrants immediate action. We strongly recommend that all system owners prioritize the deployment of the vendor-supplied security patches to all affected systems to mitigate this risk before exploits become publicly available.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, affecting both Windows and Linux versions. An attacker can send a specially crafted input to the server, causing it to write data outside of its intended memory buffer, which could lead to a system crash or allow the attacker to execute arbitrary code and take control of the affected system.

Vulnerability Details

CVE-ID: CVE-2025-23328

Affected Software: NVIDIA Triton Inference Server for Windows and Linux

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is an out-of-bounds write. This occurs when the software attempts to write data to a memory location that is outside the boundaries of the allocated buffer. An unauthenticated remote attacker can trigger this flaw by sending a specially crafted input request to the Triton Inference Server, which fails to properly validate the input size, leading to memory corruption. Successful exploitation could result in a denial-of-service (DoS) condition by crashing the server process or could be leveraged to achieve arbitrary code execution with the permissions of the server process.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. Successful exploitation could have a significant business impact by compromising the integrity, availability, and confidentiality of AI/ML services. If an attacker achieves arbitrary code execution, they could gain control of the inference server, potentially stealing sensitive proprietary models, accessing the data being processed, or using the compromised server as a pivot point to attack other systems on the network. A denial-of-service attack would disrupt critical business applications that rely on the inference server, leading to service outages, reputational damage, and financial loss.

Remediation Plan

Immediate Action: Apply the security updates released by NVIDIA immediately to all affected Triton Inference Servers. After patching, it is crucial to monitor systems for any signs of attempted exploitation and review server access and application logs for anomalous activity that may have occurred prior to patch deployment.

Proactive Monitoring: Implement enhanced monitoring on affected servers. Look for server process crashes, unexpected resource consumption (CPU/memory spikes), or error logs indicating memory corruption. Network monitoring should be configured to detect and alert on unusually large or malformed requests sent to the inference server's API endpoints.

Compensating Controls: If immediate patching is not feasible, implement the following controls to reduce risk:

• Place the Triton Inference Server behind a Web Application Firewall (WAF) or an Intrusion Prevention System (IPS) with rules to inspect and block malformed or malicious inputs.
• Restrict network access to the server, ensuring it is only accessible from trusted, authorized application front-ends and not directly exposed to the internet.
• Run the server process with the lowest possible user privileges to limit the impact of a potential code execution exploit.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of September 17, 2025, there are no known public proof-of-concept exploits or reports of active exploitation in the wild for this vulnerability. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, given the nature of the vulnerability and the widespread use of NVIDIA Triton, threat actors may actively work to develop exploits.

Analyst Recommendation

Due to the high severity rating (CVSS 7.5) and the potential for remote code execution, this vulnerability poses a significant risk to the organization. We strongly recommend that all system owners identify affected NVIDIA Triton Inference Servers and apply the vendor-supplied security updates on an emergency basis. While there is no current evidence of active exploitation, the risk of compromise is substantial. Organizations should prioritize patching and implement the suggested monitoring and compensating controls to protect critical AI/ML infrastructure.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, affecting both Windows and Linux versions. An unauthenticated attacker can send a specially crafted request over the network, causing the server to crash and become unavailable. This presents a significant risk of Denial of Service (DoS), which could disrupt critical AI and machine learning operations that rely on this platform.

Vulnerability Details

CVE-ID: CVE-2025-23325

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists within the input processing module of the NVIDIA Triton Inference Server. An attacker can send a malformed request to the server's API endpoint. This specially crafted input triggers a function that calls itself recursively without a proper termination condition, leading to a condition known as uncontrolled recursion. This rapidly consumes all available stack memory, causing a stack overflow and resulting in the immediate termination of the server process, leading to a Denial of Service.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. Successful exploitation results in a complete Denial of Service (DoS) of the Triton Inference Server. For any organization leveraging this server for real-time AI/ML model inference, the impact is direct and severe. This can lead to significant operational disruption, outage of customer-facing applications, failure of internal automated processes, and potential financial loss associated with service downtime. The primary risk is to service availability and business continuity.

Remediation Plan

Immediate Action: Apply the security updates released by NVIDIA immediately to patch the vulnerability across all affected systems. Concurrently, security teams should begin to monitor for any signs of exploitation attempts by closely reviewing server access logs for anomalous or malformed requests targeting the inference server.

Proactive Monitoring:

• Log Analysis: Monitor Triton server logs and system-level event logs (Windows Event Viewer, Linux syslog) for crash reports, stack overflow errors, or unexpected process terminations.
• Network Traffic Analysis: Inspect network traffic for unusual patterns or malformed API requests directed at the Triton server. A sudden increase in failed requests from a specific source IP could indicate an attack attempt.
• System Performance: Utilize system monitoring tools to alert on sudden restarts of the Triton server process or spikes in CPU and memory usage that precede a crash, as these can be indicators of an ongoing attack.

Compensating Controls:

• Access Control Lists (ACLs): If patching is delayed, restrict network access to the Triton Inference Server to only trusted, authorized IP addresses and subnets.
• Web Application Firewall (WAF): Deploy a WAF in front of the server to inspect and filter malicious requests. Custom rules may be required to block the specific attack pattern once it is better understood.
• Rate Limiting: Implement rate limiting on the server's API endpoints to slow down and mitigate automated attack attempts from a single source.

Exploitation Status

Public Exploit Available: False

Analyst Notes: As of August 6, 2025, there are no known public proof-of-concept exploits or observed in-the-wild attacks targeting this vulnerability. However, the description of the vulnerability is specific enough that skilled threat actors could develop an exploit. The likelihood of exploitation will increase as more technical details become public.

Analyst Recommendation

This High severity vulnerability poses a direct threat to the availability of critical AI/ML services. Given the potential for significant operational disruption, organizations must treat this as a high-priority issue. We strongly recommend that all system owners identify affected Triton Inference Servers and apply the vendor-supplied patches immediately. Although not currently on the CISA KEV list, the risk of service interruption is substantial. Until patches can be fully deployed, organizations should implement compensating controls such as network segmentation and enhanced monitoring to mitigate risk.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, a key component for deploying artificial intelligence models. An unauthenticated attacker can send a specially crafted request to the server, causing it to crash and become unavailable. This presents a significant denial-of-service risk, which could disrupt critical business applications and services that rely on AI-driven functionalities.

Vulnerability Details

CVE-ID: CVE-2025-23324

Affected Software: NVIDIA Triton Inference Server for Windows and Linux

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is an integer overflow within the NVIDIA Triton Inference Server. An attacker can exploit this by sending a network request containing specific, malformed data with invalid numerical values. When the server processes this invalid request, the flawed code attempts a calculation that results in a number exceeding the capacity of the intended variable (integer overflow), leading to a memory access error known as a segmentation fault, which immediately terminates the server process and causes a denial of service.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. Exploitation of this flaw can lead to a complete denial of service for the Triton Inference Server. For organizations that rely on this platform for production AI/ML workloads—such as real-time analytics, recommendation engines, or natural language processing services—an outage can result in direct financial loss, operational disruption, and reputational damage. The primary risk is the abrupt and repeated termination of critical AI-powered services, rendering them unavailable to users and internal systems.

Remediation Plan

Immediate Action: Organizations must prioritize the deployment of security updates provided by NVIDIA across all affected Triton Inference Server instances. After patching, administrators should confirm that the service is running the updated version and functioning correctly.

Proactive Monitoring: Security teams should actively monitor for potential exploitation attempts. This includes reviewing Triton server logs for an increase in segmentation faults or unexpected crashes. Network and application access logs should be inspected for unusual or malformed requests, particularly those containing abnormally large or negative values in their parameters, which are indicative of attempts to trigger an integer overflow.

Compensating Controls: If immediate patching is not feasible, implement the following controls to reduce risk:

• Place the Triton Inference Server behind a Web Application Firewall (WAF) or API gateway with strict input validation rules to block requests with out-of-bounds or malformed numerical data.
• Enforce network segmentation to restrict access to the Triton server, ensuring that only trusted and authorized clients can communicate with it.
• Configure automated service restart mechanisms to minimize downtime in the event of a successful denial-of-service attack, though this does not prevent the exploit itself.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of the publication date of August 6, 2025, there are no known public proof-of-concept exploits or observed in-the-wild attacks targeting this vulnerability. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, threat actors frequently reverse-engineer patches to develop exploits for high-severity vulnerabilities, so the likelihood of exploitation will increase over time.

Analyst Recommendation

Given the High severity rating (CVSS 7.5) and the critical role of AI inference servers in business operations, this vulnerability poses a significant risk. The primary impact is a denial of service, which can halt revenue-generating or mission-critical applications. We strongly recommend that organizations apply the vendor-supplied security patches to all affected systems as a top priority. While there is no current evidence of active exploitation, proactive patching is the most effective defense to prevent future disruption.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, a platform used for deploying AI models. An unauthenticated attacker can send a specially crafted request to the server, causing an integer overflow that leads to a server crash. This results in a denial-of-service condition, making AI-powered applications and services that rely on the server unavailable.

Vulnerability Details

CVE-ID: CVE-2025-23323

Affected Software: NVIDIA Triton Inference Server for Windows and Linux

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is an integer overflow within the NVIDIA Triton Inference Server. An attacker can exploit this by sending a request containing an invalid, maliciously large numerical value for a specific parameter. When the server processes this value, the integer data type cannot accommodate the large number, causing it to "wrap around" to a small or negative number. This incorrect value is then used in subsequent operations, such as memory allocation, leading to a memory access error and a segmentation fault, which terminates the server process and causes a denial of service.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. The primary business impact is a Denial of Service (DoS). Successful exploitation would crash the Triton Inference Server, disrupting all AI/ML models it serves. This can halt critical business functions that rely on real-time inference, such as recommendation engines, fraud detection systems, or automated customer support, leading to potential revenue loss, operational downtime, and damage to the organization's reputation. The risk is significant for any organization leveraging NVIDIA Triton for production AI workloads.

Remediation Plan

Immediate Action: The primary remediation is to apply the security updates provided by NVIDIA to the affected Triton Inference Server instances immediately. After patching, system administrators should monitor server logs and performance to ensure the patch has been applied successfully and has not introduced any instability.

Proactive Monitoring: Organizations should configure monitoring to detect potential exploitation attempts. This includes setting up alerts for unexpected crashes or restarts of the Triton server process. Review server access logs for malformed requests, particularly those containing unusually large numerical values in their parameters. Network traffic should be monitored for patterns indicative of a DoS attack, such as a high volume of invalid requests from a single source.

Compensating Controls: If patching cannot be performed immediately, implement compensating controls to reduce the risk. Place the Triton Inference Server behind a Web Application Firewall (WAF) or an API gateway configured to inspect and block requests with out-of-range or malicious parameter values. Additionally, restrict network access to the server, allowing connections only from trusted and authorized client systems to limit the attack surface.

Exploitation Status

Public Exploit Available: False

Analyst Notes: As of the publication date of August 6, 2025, there are no known public proof-of-concept exploits or reports of this vulnerability being actively exploited in the wild. However, given the straightforward nature of denial-of-service attacks based on integer overflows, threat actors could develop exploit code relatively easily to target unpatched systems.

Analyst Recommendation

Given the high CVSS score of 7.5 and the critical role of the Triton Inference Server in AI/ML operations, we strongly recommend that all organizations using this software treat this vulnerability with high urgency. The primary course of action is to apply the vendor-provided security updates across all affected systems without delay. Although this CVE is not currently on the CISA KEV list, its potential for causing significant service disruption warrants immediate attention. Implementing proactive monitoring and compensating controls like a WAF will provide an essential layer of defense-in-depth against potential exploitation attempts.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, a key component for AI and machine learning operations. An attacker can exploit this flaw by sending and then cancelling multiple requests, which can cause the server to crash or potentially allow the attacker to run unauthorized code. This poses a significant risk of service disruption to critical applications and could lead to a complete system compromise.

Vulnerability Details

CVE-ID: CVE-2025-23322

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is a double-free memory corruption error within the NVIDIA Triton Inference Server. An unauthenticated remote attacker can trigger this condition by sending multiple requests to the server and then cancelling those requests in a specific timing window before the server has fully processed them. This race condition causes the application to attempt to release the same memory block twice, leading to memory corruption, which can be leveraged by an attacker to cause a denial-of-service (DoS) by crashing the server or, in a more advanced attack, achieve arbitrary code execution (ACE) with the privileges of the server process.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. Exploitation could have a significant business impact by disrupting services that rely on AI/ML models served by the Triton Inference Server. A denial-of-service attack would render these applications unavailable, halting business processes and potentially causing financial loss. If an attacker achieves arbitrary code execution, they could gain control of the underlying server, leading to sensitive data exfiltration, lateral movement across the network, or the deployment of ransomware, posing a critical risk to the organization's data integrity and security posture.

Remediation Plan

Immediate Action: Apply the security updates released by NVIDIA across all affected Triton Inference Server instances immediately. Concurrently, security teams should actively monitor for any signs of exploitation attempts and conduct a thorough review of system and application access logs for anomalous activity, particularly focusing on the time before patch deployment.

Proactive Monitoring: Security teams should monitor for an unusual volume of cancelled requests in Triton server logs, unexpected server process crashes or restarts, and abnormal memory consumption spikes on the host system. On the network level, monitor for rapid, repeated connection and cancellation patterns originating from a single source IP address.

Compensating Controls: If patching cannot be performed immediately, implement the following controls:

• Restrict network access to the Triton Inference Server to only trusted, internal application sources.
• Implement strict rate-limiting on incoming requests to prevent an attacker from sending the high volume of requests needed to trigger the race condition.
• Place the server behind a Web Application Firewall (WAF) or reverse proxy capable of inspecting and blocking malformed or suspicious request patterns.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of August 6, 2025, there are no known public proof-of-concept exploits or active exploitation of this vulnerability in the wild. However, memory corruption vulnerabilities, especially in widely-used, high-value software like the Triton Inference Server, are prime targets for exploit development by threat actors.

Analyst Recommendation

Given the high severity score (CVSS 7.5) and the potential for both service disruption and complete system compromise, it is strongly recommended that organizations prioritize the immediate deployment of the vendor-supplied security patches. The affected software is often a core component of critical business infrastructure, increasing the urgency. Although this vulnerability is not currently listed on the CISA KEV list, its potential impact warrants immediate and decisive action to mitigate risk.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, affecting both Windows and Linux versions. An unauthenticated attacker can send a specially crafted request to the server, causing a "divide by zero" error that results in a denial of service, crashing the application and disrupting critical AI/ML operations. Organizations using the affected software should prioritize immediate patching to prevent service outages.

Vulnerability Details

CVE-ID: CVE-2025-23321

Affected Software: NVIDIA Triton Inference Server for Windows and Linux

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: This vulnerability is a flaw in the input validation logic of the NVIDIA Triton Inference Server. An unauthenticated, remote attacker can exploit this by sending a specially crafted request containing values that will be used as a divisor in a mathematical operation within the server's code. Because the server fails to sanitize this input and check for a zero value before the division occurs, it triggers an unhandled exception, causing the server process to terminate abruptly and resulting in a Denial of Service (DoS) condition.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5. The primary business impact is the loss of availability for critical services that rely on the Triton Inference Server for AI and machine learning model inferencing. Successful exploitation would render these services inoperable, potentially halting production workflows, disrupting customer-facing applications, and interrupting data analysis pipelines. This can lead to direct financial loss, reputational damage, and a loss of confidence in the organization's services. The low complexity of the attack means that even a low-skilled attacker could disrupt key business functions.

Remediation Plan

Immediate Action: Organizations must apply the security updates provided by NVIDIA immediately to all affected Triton Inference Server instances. After patching, system administrators should verify that the service is running correctly. It is also critical to monitor for any signs of exploitation attempts by reviewing server and application access logs for anomalous requests or crash events.

Proactive Monitoring: Implement monitoring to detect potential exploitation attempts. This includes configuring alerts for unexpected server crashes or restarts, monitoring application logs for arithmetic exception errors or stack traces, and analyzing network traffic for malformed or unusual requests targeting the Triton Inference Server's API endpoints.

Compensating Controls: If immediate patching is not feasible, implement compensating controls to reduce the risk. Restrict network access to the Triton Inference Server to only trusted, internal systems. If the server must be exposed, place it behind a Web Application Firewall (WAF) or an Intrusion Prevention System (IPS) with rules configured to inspect and block malformed requests that could trigger the vulnerability.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of the publication date of August 6, 2025, there are no known public exploits or reports of this vulnerability being actively exploited in the wild. However, denial-of-service vulnerabilities triggered by malformed requests are often simple to reproduce, and proof-of-concept code could emerge quickly.

Analyst Recommendation

Given the high severity score (CVSS 7.5) and the critical role of the Triton Inference Server in AI/ML infrastructure, this vulnerability poses a significant risk of service disruption. Although it is not currently listed on the CISA KEV list, its potential impact warrants immediate action. We strongly recommend that all organizations prioritize applying the vendor-supplied patches to all vulnerable systems without delay. In parallel, implement the proactive monitoring and compensating controls detailed above to create a defense-in-depth security posture and mitigate risk for systems awaiting a maintenance window.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Triton Inference Server, affecting both Windows and Linux deployments. An unauthenticated attacker can remotely send a specially crafted large request to the server, causing it to crash and resulting in a denial-of-service condition. This can disrupt critical business functions that rely on AI and machine learning models, making the server and its hosted models unavailable.

Vulnerability Details

CVE-ID: CVE-2025-23320

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists within the Python backend of the NVIDIA Triton Inference Server. The server fails to properly validate the size of incoming requests before processing them and allocating resources. An attacker can exploit this by sending a request with an exceptionally large payload, which forces the Python backend to attempt an allocation of shared memory that exceeds the pre-configured system limit (shm-size). This excessive memory allocation request causes the server process to terminate abruptly, leading to a denial-of-service. Exploitation requires network access to the Triton Inference Server endpoint but does not require any authentication.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.5, primarily impacting service availability. Successful exploitation will lead to a denial-of-service, rendering the Triton Inference Server and all hosted AI/ML models inoperative. For organizations that rely on these models for real-time decision-making, analytics, fraud detection, or customer-facing applications, the impact includes operational disruption, potential revenue loss, and reputational damage. The ease of exploitation (a single large request) increases the risk of targeted attacks aimed at disrupting key business processes.

Remediation Plan

Immediate Action:
Organizations must identify all instances of the NVIDIA Triton Inference Server within their environment and apply the security updates provided by the vendor immediately. System administrators should prioritize patching for internet-facing or business-critical servers to mitigate the risk of disruption. After patching, monitor server logs and performance to ensure the update has been applied successfully and the service is stable.

Proactive Monitoring:

• Log Analysis: Review Triton server logs for any error messages related to shared memory allocation failures (e.g., "failed to allocate shared memory segment"), out-of-memory errors, or unexpected process terminations.
• Network Traffic Analysis: Monitor network traffic for unusually large HTTP/gRPC requests directed at Triton server endpoints. Establish a baseline for normal request sizes and alert on significant deviations.
• System Health: Monitor system resource utilization, specifically focusing on shared memory usage (/dev/shm on Linux) and the stability of the Triton server process. Configure alerts for unexpected crashes or service restarts.

Compensating Controls:
If immediate patching is not feasible, implement the following controls to reduce risk:

• Request Filtering: Place a reverse proxy or Web Application Firewall (WAF) in front of the Triton Inference Server. Configure rules to enforce a maximum request body size, dropping any requests that exceed a reasonable threshold before they reach the vulnerable application.
• Access Control: Restrict network access to the Triton server to only trusted and authorized clients. Avoid exposing the server directly to the internet if possible.
• Resource Isolation: If running in a containerized environment, ensure resource limits (CPU, memory) are properly configured to limit the impact of a crash and enable automated restarts.

Exploitation Status

Public Exploit Available: False

Analyst Notes:
As of August 6, 2025, there are no known public proof-of-concept exploits or observed in-the-wild attacks targeting this vulnerability. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. However, given the simplicity of the attack vector, it is highly likely that a functional exploit could be developed by threat actors with minimal effort.

Analyst Recommendation
Given the high CVSS score of 7.5 and the critical role of inference servers in modern AI-driven applications, we strongly recommend that organizations prioritize the immediate patching of CVE-2025-23320. Although there is no evidence of active exploitation at this time, the low complexity of the attack makes it a significant and easily exploitable risk for service availability. If patching must be delayed for operational reasons, the implementation of compensating controls, particularly request size limiting at the network edge, is critical to prevent service disruption.

Executive Summary:
A high-severity vulnerability exists in the NVIDIA Triton Inference Server, affecting both Windows and Linux versions. An unauthenticated attacker can send a specially crafted network request to the server's Python backend, causing an out-of-bounds write, which could lead to a system crash or allow the attacker to execute arbitrary code and take control of the affected server.

Vulnerability Details

CVE-ID: CVE-2025-23319

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability lies within the Python backend component of the NVIDIA Triton Inference Server. By sending a specifically crafted network request, a remote attacker can trigger an out-of-bounds write condition. This memory corruption flaw allows an attacker to write data outside of the allocated memory buffer, which can be leveraged to overwrite critical application data, leading to a denial-of-service (DoS) by crashing the server, or potentially achieving arbitrary code execution with the permissions of the Triton server process.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 8.1. Successful exploitation could lead to a complete compromise of the AI inference server. This could result in the theft of sensitive data or intellectual property being processed by AI models, disruption of critical AI-driven business operations leading to service outages, and significant reputational damage. A compromised server could also be used as a foothold for an attacker to move laterally within the corporate network, escalating the incident's overall impact.

Remediation Plan

Immediate Action: The primary remediation is to apply the security updates provided by NVIDIA to all affected Triton Inference Servers immediately. Following the update, administrators should monitor for any signs of post-patch exploitation attempts and review historical access logs for unusual requests targeting the Python backend that may indicate a past compromise.

Proactive Monitoring: Implement enhanced logging on Triton servers to capture detailed request information. Security teams should monitor for malformed or unusually large requests, unexpected server crashes, and anomalous outbound network traffic. System-level monitoring should be configured to alert on unauthorized processes or command execution on the server.

Compensating Controls: If patching cannot be immediately deployed, implement network-level controls to mitigate risk. Restrict access to the Triton Inference Server to only trusted, authorized IP addresses and systems. Place the server behind a Web Application Firewall (WAF) or Intrusion Prevention System (IPS) with rulesets designed to detect and block memory corruption exploits and malformed requests.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of August 6, 2025, there is no known public proof-of-concept exploit code, and no active exploitation has been observed in the wild. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, due to the high severity and the potential for remote code execution, it is anticipated that threat actors will actively work to develop exploits for this vulnerability.

Analyst Recommendation

Given the high CVSS score of 8.1 and the potential for remote code execution, this vulnerability represents a significant risk to the organization. Although it is not currently listed in the CISA KEV, the ease of exploitation (sending a network request) increases the likelihood of future attacks. We strongly recommend that all organizations prioritize the immediate application of NVIDIA's security updates to all vulnerable systems. If patching is delayed, compensating controls such as network segmentation and access control lists must be implemented as a critical temporary measure.

Executive Summary:
A high-severity vulnerability exists in the NVIDIA Triton Inference Server, a platform used for deploying AI models. An attacker can exploit a flaw in the server's Python backend to write data outside of its designated memory space, which could lead to a system crash or allow the attacker to execute arbitrary code. Successful exploitation could result in a denial of service for critical AI applications or a complete compromise of the affected server.

Vulnerability Details

CVE-ID: CVE-2025-23318

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is an out-of-bounds write within the Python backend of the NVIDIA Triton Inference Server. An unauthenticated remote attacker can send a specially crafted request to the server. When the server's Python backend processes this malicious request, it fails to properly validate the size of the input, allowing it to write data beyond the boundaries of the allocated memory buffer. This memory corruption can be leveraged by an attacker to crash the server, causing a denial of service, or potentially overwrite critical memory structures to achieve arbitrary code execution in the context of the Triton server process.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 8.1. Exploitation could have a significant business impact, particularly for organizations that rely on the Triton Inference Server for production AI/ML workloads. A successful denial-of-service attack would disrupt business-critical applications, leading to service outages and potential revenue loss. More critically, if an attacker achieves remote code execution, they could gain control of the server, leading to the theft of proprietary machine learning models, exfiltration of sensitive data being processed by the models, or using the compromised server as a foothold to move laterally within the corporate network.

Remediation Plan

Immediate Action: Apply the security updates released by NVIDIA to all affected Triton Inference Server instances immediately. After patching, it is essential to monitor for any signs of exploitation attempts that may have occurred prior to the update and to review server access logs for any anomalous or suspicious activity.

Proactive Monitoring: Implement enhanced monitoring on Triton Inference Servers. Security teams should look for unusual traffic patterns, malformed or exceptionally large requests in network logs, and unexpected crashes or restarts of the Triton server process. Enable and review verbose logging from the Python backend, specifically looking for memory allocation errors or segmentation faults that could indicate an exploitation attempt.

Compensating Controls: If patching cannot be immediately applied, implement the following controls to mitigate risk:

• Restrict network access to the Triton Inference Server, ensuring it is only reachable from trusted application front-ends and not directly exposed to the internet.
• Deploy a Web Application Firewall (WAF) or Intrusion Prevention System (IPS) with rules designed to inspect and block malformed requests targeting the server.
• Run the Triton server process with the lowest possible user privileges to limit the impact of a potential code execution exploit.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of August 6, 2025, there are no known public proof-of-concept exploits or active exploitation campaigns targeting this vulnerability. However, given the high-severity rating and the potential for remote code execution, it is highly probable that security researchers and threat actors will analyze the patch to develop an exploit. This vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog.

Analyst Recommendation

Given the high CVSS score of 8.1 and the potential for remote code execution, this vulnerability poses a significant risk to the organization. We strongly recommend that all affected NVIDIA Triton Inference Servers are patched on an emergency basis. Although there is no evidence of active exploitation at this time, vulnerabilities of this nature are attractive targets for threat actors. Prioritize the deployment of vendor-supplied security updates and implement the recommended compensating controls on any systems where patching may be delayed.

Executive Summary:
A critical vulnerability has been discovered in the NVIDIA Triton Inference Server, identified as CVE-2025-23317 with a CVSS score of 9.1. An unauthenticated attacker can send a specially crafted web request to a vulnerable server to gain full control via a reverse shell. A successful exploit could lead to complete system compromise, allowing for data theft, service disruption, and further attacks on the internal network.

Vulnerability Details

CVE-ID: CVE-2025-23317

Affected Software: NVIDIA Triton Inference Server

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists within the HTTP server component of the NVIDIA Triton Inference Server. An attacker can exploit this flaw by sending a specially crafted HTTP request to the server's listening port. This request triggers a condition that allows for remote code execution (RCE), enabling the attacker to force the compromised server to initiate an outbound connection (a "reverse shell") back to an attacker-controlled machine, effectively bypassing perimeter firewalls.

Business Impact

This vulnerability is rated as critical severity with a CVSS score of 9.1. Successful exploitation grants an attacker remote control over the Triton Inference Server, leading to severe business consequences. These risks include the theft of proprietary machine learning models and sensitive data being processed, manipulation of AI model outputs to cause incorrect results, and complete denial of service. Furthermore, a compromised server can be used as a pivot point to launch further attacks against other critical systems within the organization's network, escalating the incident's impact.

Remediation Plan

Immediate Action: The primary remediation is to update the NVIDIA Triton Inference Server to the latest patched version as recommended by the vendor. After patching, administrators should closely monitor for any signs of exploitation attempts by reviewing server and network access logs for suspicious activity.

Proactive Monitoring: Organizations should monitor for unusual outbound network connections from Triton servers, especially to unknown IP addresses or ports, which could indicate a reverse shell. Review HTTP access logs for malformed or anomalous requests that do not align with standard API traffic. Monitor system processes for unexpected child processes spawned by the Triton server process.

Compensating Controls: If immediate patching is not feasible, implement the following controls to reduce risk:

• Restrict network access to the Triton server's HTTP port using a firewall or network access control lists (ACLs), allowing connections only from trusted IP ranges.
• Deploy a Web Application Firewall (WAF) in front of the server to inspect and block malicious HTTP requests.
• Run the Triton Inference Server process with the lowest possible user privileges to limit an attacker's capabilities if the system is compromised.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of the publication date, August 6, 2025, there are no known public proof-of-concept exploits or reports of this vulnerability being actively exploited in the wild. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, due to the critical severity and potential for remote code execution, it is highly likely that threat actors will develop exploits.

Analyst Recommendation

Given the critical severity (CVSS 9.1) and the risk of complete system compromise, it is imperative that organizations identify all vulnerable instances of NVIDIA Triton Inference Server and apply the vendor-supplied patches immediately. This vulnerability represents a significant threat to confidentiality, integrity, and availability. While it is not yet on the CISA KEV list, its high impact makes it a prime target for future exploitation. If patching cannot be performed immediately, the compensating controls listed above must be implemented as a matter of urgency.

Executive Summary:
A critical vulnerability has been identified in the NVIDIA Triton Inference Server for both Windows and Linux, specifically within its Python backend. This flaw allows a remote, unauthenticated attacker to execute arbitrary code on the server by sending a specially crafted request, potentially leading to a complete system compromise and theft of sensitive data or AI models.

Vulnerability Details

CVE-ID: CVE-2025-23316

Affected Software: NVIDIA Triton Inference Server for Windows and Linux (Python Backend)

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists within the Python backend component of the NVIDIA Triton Inference Server. The server fails to properly sanitize the model name parameter in incoming requests. A remote, unauthenticated attacker can exploit this by crafting a request with a malicious model name string that includes arbitrary commands. When the server processes this request, the unsanitized input is executed on the underlying operating system with the privileges of the Triton server process, resulting in remote code execution (RCE).

Business Impact

This vulnerability is rated as critical with a CVSS score of 9.8, posing a severe risk to the organization. A successful exploit could lead to a complete compromise of the affected inference server, allowing an attacker to execute arbitrary code. This could result in the theft of proprietary machine learning models and sensitive training data, disruption of critical AI-powered services, and the potential for the attacker to pivot and move laterally within the corporate network. The business could face significant financial losses, reputational damage, and loss of intellectual property.

Remediation Plan

Immediate Action: Update NVIDIA Triton Inference Server for Windows and Linux to the latest version. Monitor for exploitation attempts and review access logs.

Proactive Monitoring:

• Log Analysis: Review Triton Inference Server access logs for unusual or excessively long model name parameters, especially those containing special characters, shell commands, or script syntax.
• Process Monitoring: Monitor for unexpected child processes being spawned by the Triton server process (e.g., sh, bash, powershell.exe, cmd.exe).
• Network Traffic: Monitor for anomalous outbound network connections from the Triton server to unknown or untrusted IP addresses, which could indicate a successful compromise and command-and-control communication.

Compensating Controls:

• Network Segmentation: Restrict network access to the Triton Inference Server. Use a firewall or network access control lists (ACLs) to ensure it is only accessible from trusted application servers and internal IP ranges.
• Web Application Firewall (WAF): If the server is exposed, deploy a WAF with rules designed to inspect and block malicious patterns or command injection attempts within the model name parameter of API requests.
• Principle of Least Privilege: Ensure the Triton server process runs as a low-privilege service account with minimal necessary permissions on the host system to limit the impact of a potential compromise.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of September 17, 2025, there are no known public exploits or reports of this vulnerability being actively exploited in the wild. However, due to the critical severity (CVSS 9.8) and the relative simplicity of the attack vector (parameter manipulation), it is highly likely that proof-of-concept exploits will be developed by security researchers and threat actors. This vulnerability is not currently listed in the CISA Known Exploited Vulnerabilities (KEV) catalog.

Analyst Recommendation

Given the critical severity (CVSS 9.8) of this remote code execution vulnerability, immediate action is required. Organizations using the affected NVIDIA Triton Inference Server versions should prioritize applying the vendor-supplied patches to all vulnerable systems without delay. Although this vulnerability is not currently listed on the CISA KEV catalog, its high potential for impact makes it an attractive target for threat actors. If immediate patching is not feasible, implement the recommended compensating controls and proactive monitoring to reduce the risk of compromise.

Executive Summary:
A critical vulnerability has been identified in the NVIDIA Triton Inference Server, a platform used for deploying artificial intelligence models. An unauthenticated attacker can send a specially crafted network request to cause a stack overflow, which could allow them to execute arbitrary code and take full control of the affected server. This vulnerability poses a severe risk of data breach, system compromise, and disruption of critical AI-powered services.

Vulnerability Details

CVE-ID: CVE-2025-23311

Affected Software: NVIDIA Triton Inference Server (Note: This component may be bundled within other NVIDIA software suites and products).

Affected Versions: See vendor advisory for specific affected versions.

Vulnerability: The vulnerability is a stack-based buffer overflow within the HTTP request handling component of the NVIDIA Triton Inference Server. An unauthenticated remote attacker can exploit this by sending a crafted HTTP request containing an overly long value in a specific field (e.g., a header or parameter). This action overwrites the program's call stack, potentially allowing the attacker to hijack the execution flow and run arbitrary code with the permissions of the Triton server process, or at minimum, crash the server causing a denial of service.

Business Impact

This vulnerability is rated as critical severity with a CVSS score of 9.8. A successful exploit could lead to complete system compromise, allowing an attacker to execute remote code on the server hosting the Triton Inference Server. This poses a significant business risk, including the theft of proprietary AI/ML models and sensitive training data, unauthorized access to internal networks, and the potential for deploying ransomware. A denial-of-service attack would disrupt critical AI-driven applications, leading to operational downtime, reputational damage, and financial loss.

Remediation Plan

Immediate Action: Organizations must immediately apply the security updates provided by NVIDIA. Prioritize patching internet-facing Triton Inference Servers and then internal instances to mitigate the risk of exploitation.

Proactive Monitoring: Security teams should actively monitor for signs of exploitation. Review web server and application logs for unusually long or malformed HTTP requests directed at the Triton server. Monitor system behavior for unexpected crashes or restarts of the Triton server process and look for anomalous outbound network connections from the server, which could indicate a successful compromise.

Compensating Controls: If immediate patching is not feasible, implement a Web Application Firewall (WAF) with rules to inspect and block malformed HTTP requests or those with excessively long headers/parameters. Additionally, restrict network access to the Triton Inference Server's HTTP port, allowing connections only from trusted, authorized IP addresses to reduce the attack surface.

Exploitation Status

Public Exploit Available: False

Analyst Notes: As of August 6, 2025, there are no known public proof-of-concept exploits or observed in-the-wild attacks leveraging this vulnerability. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, due to the critical CVSS score and the relative simplicity of stack overflow attacks, it is highly probable that threat actors will develop an exploit in the near future.

Analyst Recommendation

Given the critical severity (CVSS 9.8) and the high potential for remote code execution, this vulnerability requires immediate attention. We strongly recommend that all organizations using the NVIDIA Triton Inference Server apply the vendor-supplied patches without delay, prioritizing internet-exposed systems. Although not yet listed in the CISA KEV, its severity makes it a prime target for exploitation. If patching is delayed, the compensating controls outlined above should be implemented as an urgent temporary measure.

Executive Summary:
A critical vulnerability has been discovered in NVIDIA's Triton Inference Server for both Windows and Linux. This flaw, identified as a stack buffer overflow, can be exploited by a remote attacker sending specially crafted inputs to the server. A successful exploit could allow the attacker to execute arbitrary code, leading to a complete system compromise, data theft, or a denial-of-service condition that would disrupt critical AI/ML operations.

Vulnerability Details

CVE-ID: CVE-2025-23310

Affected Software: NVIDIA Triton Inference Server for Windows and Linux

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is a stack-based buffer overflow within the NVIDIA Triton Inference Server. An unauthenticated, remote attacker can exploit this by sending a specially crafted request with an overly large input to a vulnerable endpoint. This action overwrites the memory buffer on the stack, allowing the attacker to corrupt adjacent memory, including the function's return pointer. By overwriting the return pointer with an address of their choosing, an attacker can redirect the program's execution flow to malicious code (shellcode) they have injected, resulting in arbitrary code execution with the same privileges as the Triton server process.

Business Impact

This vulnerability is rated as critical severity with a CVSS score of 9.8. A successful exploit poses a significant risk to the organization, potentially leading to a complete compromise of the affected server. An attacker could gain control of the system to steal sensitive data being processed, such as proprietary AI models, intellectual property, or confidential business information. Furthermore, the compromised server could be used as a pivot point to attack other systems within the corporate network, or be leveraged for malicious activities like hosting malware or participating in a botnet. The vulnerability could also be exploited to cause a denial-of-service (DoS) by crashing the server, which would disrupt business-critical applications and services that rely on the AI/ML infrastructure.

Remediation Plan

Immediate Action: Prioritize updating all affected NVIDIA Triton Inference Server instances to the latest patched version as recommended by the vendor. After patching, verify that the service is operating correctly.

Proactive Monitoring: Implement enhanced monitoring on affected systems. Review Triton server access logs for requests that are unusually large, malformed, or result in server errors or crashes. Monitor network traffic for anomalous outbound connections from the Triton server, which could indicate a successful compromise and communication with a command-and-control server. Utilize Intrusion Detection/Prevention Systems (IDS/IPS) with updated signatures to detect and block potential exploitation attempts.

Compensating Controls: If immediate patching is not feasible, implement compensating controls to reduce the risk. Place the Triton Inference Server behind a Web Application Firewall (WAF) or a reverse proxy capable of inspecting and sanitizing input traffic to block malicious requests. Enforce strict network segmentation to isolate the server, limiting its ability to communicate with critical internal network segments and thus containing the potential impact of a compromise. Ensure the server process is running with the lowest possible user privileges.

Exploitation Status

Public Exploit Available: False

Analyst Notes: As of the publication date, August 6, 2025, there are no known public proof-of-concept exploits or active exploitation campaigns targeting this vulnerability. However, given the critical CVSS score of 9.8 and the widespread use of the Triton Inference Server, it is highly probable that threat actors will prioritize developing an exploit. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog.

Analyst Recommendation

Given the critical severity (CVSS 9.8) and the potential for remote code execution, this vulnerability represents a direct and severe threat to the organization. We strongly recommend that all system owners identify and patch affected NVIDIA Triton Inference Server instances with the highest priority. Although this CVE is not yet on the CISA KEV list, its high impact score makes it a prime target for future exploitation. Organizations should treat this vulnerability with the utmost urgency and apply remediation actions immediately to prevent potential system compromise and data breaches.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA Installer for NvAPP on Windows systems. This flaw allows a local attacker with standard user permissions to modify files during the installation of the Frameview SDK, which could lead to them gaining full administrative control over the affected computer. Successful exploitation could result in data theft, malware installation, or complete system compromise.

Vulnerability Details

CVE-ID: CVE-2025-23297

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists within the installation process of the Frameview SDK, which is part of the NVIDIA Installer for NvAPP. During installation, the process may set insecure permissions on the Frameview SDK directory or be susceptible to a race condition. An attacker with local, unprivileged user access on the Windows system can exploit this window of opportunity to replace or modify legitimate files, such as dynamic-link libraries (DLLs) or executables, with malicious code. When a legitimate, higher-privileged process later executes these modified files, the attacker's code runs with elevated privileges, leading to a local privilege escalation (LPE).

Business Impact

This vulnerability is rated as high severity with a CVSS score of 7.8. Successful exploitation allows an attacker to escalate their privileges from a standard user to a full administrator on the compromised system. This level of access would enable an attacker to bypass security controls, install persistent malware like ransomware or keyloggers, exfiltrate sensitive corporate data, and potentially pivot to other systems on the network. The impact on business operations includes risks to data confidentiality, system integrity, and availability, potentially leading to significant financial or reputational damage.

Remediation Plan

Immediate Action: Apply the security updates provided by NVIDIA to all affected systems immediately. Prioritize patching on workstations and multi-user systems where unprivileged accounts exist. After patching, monitor for any signs of exploitation attempts by reviewing system and application logs for unusual activity related to NVIDIA services.

Proactive Monitoring: Security teams should configure Endpoint Detection and Response (EDR) and Security Information and Event Management (SIEM) systems to monitor for and alert on suspicious file modifications within the NVIDIA Frameview SDK installation directory (e.g., C:\Program Files\NVIDIA Corporation\FrameviewSDK\). Monitor Windows Security Event Logs for anomalous process creation events originating from NVIDIA services, particularly those running with SYSTEM privileges.

Compensating Controls: If immediate patching is not feasible, implement compensating controls such as application whitelisting to prevent unauthorized executables from running from the Frameview SDK directory. Harden endpoint security configurations to restrict file modification in sensitive program directories. Ensure that EDR solutions are deployed and configured to detect common privilege escalation techniques.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of October 1, 2025, there are no known public exploits or active attacks targeting this vulnerability. The vulnerability requires an attacker to have already gained local access to a target system, making it a second-stage attack vector used for privilege escalation. The vulnerability is not currently listed in the CISA Known Exploited Vulnerabilities (KEV) catalog.

Analyst Recommendation

Immediate patching of all affected NVIDIA installations is strongly recommended. Although this vulnerability requires prior local access and is not yet actively exploited in the wild, its high severity score of 7.8 underscores a significant risk. An attacker who has gained an initial foothold via phishing or another method could use this vulnerability to achieve full system control, rendering other security defenses ineffective. Organizations should prioritize the deployment of vendor-supplied security updates to mitigate the threat of local privilege escalation.

Executive Summary:
A high-severity vulnerability exists in NVIDIA's vGPU software that could allow a malicious user in a guest virtual machine to crash or potentially execute code on the underlying host system. Successful exploitation could lead to a widespread denial of service affecting all virtual machines on a host or a complete system compromise, posing a significant risk to virtualized infrastructure.

Vulnerability Details

CVE-ID: CVE-2025-23284

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is a stack-based buffer overflow within the Virtual GPU Manager (vGPU Manager) component, which runs on the host hypervisor. An attacker with sufficient privileges within a guest operating system can send specially crafted, malicious data to the vGPU Manager. This input is not properly validated, leading to a buffer overflow on the stack, which can corrupt adjacent memory, overwrite the function's return address, and ultimately lead to a crash (Denial of Service) or arbitrary code execution on the host system with the privileges of the vGPU Manager process.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.8. Exploitation presents a critical risk to business operations that rely on virtualized environments. A successful denial-of-service attack would crash the vGPU Manager, disrupting GPU-accelerated workloads for all virtual machines on the physical host, leading to significant service outages. More critically, a successful code execution exploit constitutes a "guest-to-host" or "VM escape" scenario, allowing an attacker to break out of the isolated guest environment and gain control of the underlying host, potentially accessing data from all other VMs, moving laterally across the network, and causing a complete compromise of the infrastructure.

Remediation Plan

Immediate Action: The primary remediation is to apply the security updates released by NVIDIA to all affected systems immediately. Prioritize patching of internet-facing or multi-tenant systems to prevent exploitation. Concurrently, security teams should begin monitoring for signs of exploitation attempts and closely review access and system logs for any anomalous behavior related to the vGPU Manager.

Proactive Monitoring: Monitor host system logs for any unexpected crashes or restarts of the vGPU Manager process. Implement enhanced logging on hypervisors to capture inter-VM and guest-to-host communication. Utilize Endpoint Detection and Response (EDR) tools on host systems to detect memory corruption attacks and unauthorized process execution originating from the vGPU service.

Compensating Controls: If patching cannot be performed immediately, consider isolating untrusted guest VMs to dedicated physical hosts that are either patched or do not utilize the vGPU feature. Strengthen network segmentation to limit communication from guest VMs to the host management interface and prevent lateral movement in the event of a compromise. Restrict administrative or root-level access within guest VMs to trusted users only.

Exploitation Status

Public Exploit Available: False

Analyst Notes: As of August 3, 2025, there are no known public proof-of-concept exploits or active attacks targeting this vulnerability. However, stack buffer overflows are a well-understood vulnerability class, and the technical details provided in advisories may be sufficient for skilled threat actors to develop an exploit. The vulnerability is not currently listed in the CISA Known Exploited Vulnerabilities (KEV) catalog.

Analyst Recommendation

Given the High severity rating (CVSS 7.8) and the potential for a full hypervisor escape, this vulnerability represents a critical risk to the security and stability of the virtualization environment. Although there is no evidence of active exploitation, the impact of a successful attack is severe. We strongly recommend that organizations using NVIDIA vGPU software treat this as a high-priority issue and deploy the vendor-provided security patches on an emergency basis to mitigate the risk of service disruption and host system compromise.

Executive Summary:
A high-severity vulnerability has been discovered in NVIDIA's virtual GPU (vGPU) software for Linux-based systems. An attacker with control over a guest virtual machine could exploit this flaw to crash the underlying host system, leading to a denial-of-service condition for all other virtual machines running on that host and disrupting critical services.

Vulnerability Details

CVE-ID: CVE-2025-23283

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability exists within the Virtual GPU Manager (vGPU Manager) component, which runs on the host hypervisor. An attacker with low-level privileges within a guest virtual machine can send specially crafted data to the vGPU Manager, triggering a stack-based buffer overflow. Successful exploitation could lead to the termination of the vGPU Manager process, causing a denial-of-service (DoS) that crashes the host hypervisor and impacts all guest virtual machines running on it. Depending on the memory layout, this flaw could potentially be leveraged for arbitrary code execution on the host system, allowing an attacker to escape the guest VM environment.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.8. Exploitation poses a significant risk to business operations, particularly in environments relying on virtualization for critical services like Virtual Desktop Infrastructure (VDI) or high-performance computing. A successful attack would result in a denial-of-service condition, crashing the host server and causing an outage for all virtual machines it supports. This could lead to significant downtime, loss of productivity, and potential data loss. If an attacker achieves code execution on the hypervisor, they could gain complete control of the host, compromising the confidentiality and integrity of all guest data and using the compromised host as a pivot point for further attacks within the network.

Remediation Plan

Immediate Action: Organizations must prioritize the deployment of security patches provided by NVIDIA across all affected systems. Due to the high severity and potential for a host-level denial-of-service, these updates should be applied immediately in accordance with established patch management policies, starting with the most critical systems.

Proactive Monitoring: Security teams should actively monitor for signs of exploitation. This includes monitoring hypervisor logs for any crashes or unexpected restarts of the vGPU Manager service. System performance monitoring should be configured to alert on abnormal CPU or memory usage on the host that could indicate an attempted overflow attack. Review guest VM logs for any anomalous behavior or processes attempting to interact directly with the vGPU in an unusual manner.

Compensating Controls: If immediate patching is not feasible, implement compensating controls to reduce the attack surface. Restrict the creation and control of guest virtual machines to only trusted administrators. Isolate virtual machines that require vGPU functionality onto dedicated, segmented host clusters to limit the blast radius of a successful exploit. Consider temporarily disabling vGPU profiles on non-essential guest VMs until patches can be applied.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of the publication date, August 3, 2025, there are no known public exploits for CVE-2025-23283. The vulnerability is not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, given the nature of the vulnerability (guest-to-host DoS/escape), it is highly likely that security researchers and threat actors will begin developing exploit code. Organizations should operate under the assumption that an exploit will become available.

Analyst Recommendation

Given the High severity (CVSS 7.8) of this vulnerability and its potential to cause a complete host system failure or facilitate a virtual machine escape, we strongly recommend immediate action. The primary risk is a denial-of-service that could disrupt critical business functions. Organizations must prioritize applying the NVIDIA security updates to all affected hypervisors. While there is no evidence of active exploitation at this time, the severity of the flaw makes it an attractive target for attackers. Treat this vulnerability with high urgency and expedite patching and monitoring efforts.

Executive Summary:
A high-severity vulnerability has been identified in the NVIDIA GPU Display Driver for Windows. An unprivileged local attacker could potentially exploit this flaw to escalate their privileges, leading to a full system compromise. Successful exploitation could allow an attacker to gain administrative control over the affected machine, enabling them to steal sensitive data, install malicious software, or disrupt operations.

Vulnerability Details

CVE-ID: CVE-2025-23281

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability is a use-after-free condition within the NVIDIA GPU Display Driver for Windows. To exploit this, an attacker with local, non-administrative access to a system must win a race condition. This involves precisely timing a sequence of operations to manipulate the driver's memory management, causing it to use a memory pointer after the memory it points to has been freed. Successful exploitation can lead to memory corruption, which can be leveraged to execute arbitrary code with kernel-level privileges, resulting in a complete system takeover.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7. The primary business impact is the risk of privilege escalation on company assets, including employee workstations, virtual desktop infrastructure (VDI), and servers equipped with affected NVIDIA GPUs. A compromised standard user account could be elevated to full system administrator, bypassing security controls and gaining access to sensitive corporate data, intellectual property, or critical infrastructure. This could facilitate lateral movement within the network, deployment of ransomware, or persistent, undetected access to the corporate environment.

Remediation Plan

Immediate Action: The primary remediation is to apply the security updates provided by NVIDIA to all affected systems immediately. Prioritize patching for critical systems, multi-user workstations, and servers. In parallel, security teams should actively monitor for any signs of exploitation attempts and review system and security logs for anomalous activity related to the display driver.

Proactive Monitoring: Monitor for unexpected system crashes or Blue Screen of Death (BSOD) events, as these can be indicators of failed exploitation attempts. Utilize Endpoint Detection and Response (EDR) tools to monitor for suspicious process behavior, such as processes spawning with elevated (SYSTEM) privileges from a user-level context. Review Windows Event Logs for errors or warnings related to the nvlddmkm.sys driver or other NVIDIA components.

Compensating Controls: If immediate patching is not feasible, implement compensating controls to reduce risk. Enforce the principle of least privilege by restricting user permissions and limiting software installation capabilities. Utilize application whitelisting or control solutions to prevent the execution of unauthorized code that could be used to trigger the vulnerability. Ensure EDR solutions are configured to detect and block memory corruption exploitation techniques.

Exploitation Status

Public Exploit Available: False

Analyst Notes: As of August 3, 2025, there is no known public proof-of-concept exploit code, and the vulnerability is not reported to be actively exploited in the wild. The vulnerability is not listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. However, given the nature of the flaw, dedicated threat actors may attempt to develop private exploits for targeted attacks.

Analyst Recommendation

It is strongly recommended that the organization treat this vulnerability as a high priority for remediation. Although exploitation requires local access and winning a race condition, the potential impact of a successful privilege escalation is severe. Organizations should adhere to their patching policies for high-severity vulnerabilities and deploy the vendor-supplied security updates as soon as possible to mitigate the risk of a system compromise.

Executive Summary:
A high-severity vulnerability has been identified in NVIDIA display drivers for Windows and Linux systems. An attacker with local access to a vulnerable machine could exploit this flaw by sending specially crafted data to the driver, potentially causing the system to crash or allowing the attacker to execute malicious code with elevated privileges. This could lead to system downtime, unauthorized access, or a full compromise of the affected device.

Vulnerability Details

CVE-ID: CVE-2025-23278

Affected Software: NVIDIA Multiple Products

Affected Versions: See vendor advisory for specific affected versions

Vulnerability: The vulnerability resides within the NVIDIA Display Driver for both Windows and Linux operating systems and is caused by an improper index validation flaw. A local attacker who can issue calls to the driver's API can send a specially crafted request with malicious parameters. This action can trigger an out-of-bounds memory access, leading to a denial-of-service (DoS) condition by crashing the system or, in a more severe scenario, enabling arbitrary code execution with kernel-level privileges.

Business Impact

This vulnerability is rated as High severity with a CVSS score of 7.1. Successful exploitation poses a significant risk to business operations. The most probable outcome is a denial-of-service attack, resulting in system crashes (e.g., Blue Screen of Death on Windows) that disrupt user productivity and critical services. A successful privilege escalation attack would be more damaging, allowing an attacker to gain complete control over the system. This could lead to sensitive data theft, the deployment of ransomware or other malware, and lateral movement throughout the corporate network.

Remediation Plan

Immediate Action: Identify all Windows and Linux systems with vulnerable NVIDIA display drivers. Prioritize and apply the security updates provided by NVIDIA immediately, starting with critical assets such as servers, developer workstations, and executive machines. Follow standard patch management procedures to ensure a comprehensive rollout across the environment.

Proactive Monitoring: Monitor system logs (Windows Event Logs, Linux syslog/journalctl) for unexpected driver crashes, kernel panics, or system reboots that could indicate exploitation attempts. Utilize an Endpoint Detection and Response (EDR) solution to detect anomalous process behavior interacting with the NVIDIA driver stack. Review access logs for suspicious user activity that might precede an attack.

Compensating Controls: If patching cannot be performed immediately, enforce the principle of least privilege to limit an attacker's ability to run the code necessary to exploit the flaw. Implement application whitelisting to prevent unauthorized executables from running. Segment networks to isolate critical systems and limit the potential impact of a compromise.

Exploitation Status

Public Exploit Available: false

Analyst Notes: As of August 3, 2025, there is no known public proof-of-concept exploit code, and this vulnerability is not reported to be actively exploited in the wild. However, vulnerabilities in widely deployed software like NVIDIA drivers are attractive targets for threat actors. It is highly probable that security researchers and malicious actors will analyze the patch to develop exploit code. The requirement for local access makes it a likely candidate for a privilege escalation tool within a larger attack chain.

Analyst Recommendation

This vulnerability represents a high risk to the organization due to its potential for causing system instability or enabling a full system compromise. Although CVE-2025-23278 is not currently on the CISA Known Exploited Vulnerabilities (KEV) catalog, its high CVSS score necessitates urgent action. We strongly recommend that all system administrators prioritize the immediate testing and deployment of the vendor-supplied security updates to mitigate this risk and prevent potential operational disruption or data breaches.