Nemo Megatron Bridge
Monthly
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, data tampering, and information disclosure on the affected host. The CVSS 3.1 vector (AV:L/AC:L/PR:L/UI:N, C:H/I:H/A:H) indicates a local, low-complexity exploit path yielding full triad compromise - consistent with classic unsafe deserialization primitives that reconstruct attacker-controlled object graphs. No public exploit or CISA KEV listing has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, tamper with data, and disclose sensitive information. The vulnerability (CWE-502) exists in the Megatron Bridge component of NVIDIA's large-scale model training infrastructure, where attacker-controlled serialized input is processed without adequate validation. No public exploit code or active exploitation via CISA KEV has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-privilege access to achieve code execution, data tampering, and information disclosure on the host system. The vulnerability (CWE-502) is exploitable locally without user interaction, making it particularly relevant in multi-tenant high-performance compute environments where Megatron Bridge is used for large-scale model training pipelines. No public exploit code or active exploitation has been identified at time of analysis, but the full C/I/A impact triad elevates the urgency for affected deployments.
Local code execution in NVIDIA Megatron Bridge exploits unsafe deserialization of attacker-controlled data, allowing a low-privileged local user to achieve full process compromise with high confidentiality, integrity, and availability impact. The CVSS 7.8 (High) vector - AV:L/AC:L/PR:L/UI:N - confirms that no network exposure, user interaction, or elevated privileges are required beyond an initial local foothold. No public exploit code and no CISA KEV listing have been identified at time of analysis, but the RCE-capable impact class warrants prompt remediation in multi-user AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes affected systems to code execution, data tampering, and information disclosure by a local low-privileged attacker. The flaw (CWE-502) allows a maliciously crafted serialized object to hijack the application's deserialization routine, granting the attacker the full CIA impact of the process context without requiring elevated privileges or user interaction. No public exploit code has been identified at time of analysis, and the vulnerability is not listed in CISA KEV; however, the high CIA impact and low attack complexity make this a meaningful priority for any organization running Megatron Bridge in multi-tenant or shared compute environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a low-privileged local user to achieve arbitrary code execution, data tampering, and information disclosure on the affected host. Reported directly by NVIDIA PSIRT (psirt@nvidia.com) and classified CWE-502, the flaw requires only local system access with standard user privileges, elevating insider threat and lateral-movement risk in shared AI training environments. No public exploit code or active exploitation has been confirmed at time of analysis, but the low attack complexity and full C/I/A impact make patching a real operational priority for any deployment.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, data tampering, and information disclosure on affected systems. The CVSS 3.1 score of 7.8 (AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) reflects full CIA impact from a local, low-complexity attack requiring no user interaction, making this a meaningful privilege escalation and code execution risk in shared compute environments such as multi-tenant GPU training clusters. No public exploit code or CISA KEV listing has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local low-privileged attacker to achieve code execution, corrupt data, and exfiltrate sensitive information. The vulnerability (CWE-502) is exploitable locally with low privileges and no user interaction, yielding a CVSS 7.8 High rating with full confidentiality, integrity, and availability impact. No public exploit code has been identified at the time of analysis, and CISA has not added this to the Known Exploited Vulnerabilities catalog.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes local users to code execution, data tampering, and information disclosure. An attacker with low-privileged local access can supply crafted serialized payloads to the Bridge component, which are deserialized without adequate validation. No public exploit code or active exploitation has been identified at time of analysis, but the high C/I/A impact and low-complexity exploitation path make this a meaningful risk in multi-tenant AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes systems to local code execution, data tampering, and information disclosure from a low-privileged local user. The vulnerability (CWE-502) allows an attacker with local access to supply malicious serialized payloads that the bridge processes without sufficient validation. No public exploit or CISA KEV listing is identified at time of analysis, but the full-triad high-impact CVSS score (C:H/I:H/A:H) signals severe post-exploitation potential on any host running the component.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve code execution, data tampering, and information disclosure on the host system. The CVSS:3.1 vector (AV:L/PR:L) confirms this is a local-access vulnerability targeting NVIDIA's distributed large-model training infrastructure, where a compromised or malicious low-privileged user on the same host could supply a crafted serialized payload to the Bridge component. No public exploit or CISA KEV listing has been identified at time of analysis, but the full-triad impact (C:H/I:H/A:H) makes this a meaningful threat in multi-tenant AI training cluster environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve full system compromise, including arbitrary code execution, data tampering, and information disclosure. The CVSS 3.1 score of 7.8 (AV:L/AC:L/PR:L/UI:N) confirms that exploitation requires local access with minimal privilege but no user interaction, making it a realistic threat in multi-tenant AI training environments where Megatron Bridge is used. No public exploit code or CISA KEV listing has been identified at the time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local low-privileged attacker to achieve arbitrary code execution, tamper with data, and disclose sensitive information on the affected host. The CVSS 7.8 score with local attack vector and low-privilege requirement indicates an authenticated local user can exploit the flaw without user interaction, fully compromising confidentiality, integrity, and availability. No public exploit or active exploitation has been identified at time of analysis, though the CIA triad is fully impacted on successful exploitation, making this a meaningful risk in shared compute environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local low-privileged attacker to achieve code execution, data tampering, and information disclosure with no user interaction required. The AV:L/PR:L CVSS vector confines the attack to actors who already hold a valid local account on the affected host, limiting but not eliminating real-world risk in shared AI infrastructure. No public exploit code has been identified, and this vulnerability has not been listed in CISA's Known Exploited Vulnerabilities catalog at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected system. The CVSS vector (AV:L/PR:L) confirms exploitation requires local access with standard user privileges, making this most relevant to shared multi-user HPC or AI/ML training cluster environments where multiple users interact with the same Megatron infrastructure. No public exploit code or active exploitation (CISA KEV) has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a low-privileged local attacker to achieve arbitrary code execution, data tampering, and information disclosure on affected systems. The flaw (CWE-502) requires only an authenticated local OS session - no elevated privileges or user interaction - making it exploitable by any standard user on a host running the Bridge component. Reported directly by NVIDIA PSIRT, no public exploit has been identified at the time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-level privileges to achieve code execution, data tampering, and information disclosure on the affected system. The CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H vector indicates exploitation requires only local, low-privileged access with no user interaction, making this a meaningful threat in multi-tenant AI training environments where shared compute access is common. No public exploit code or active exploitation via CISA KEV has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to execute arbitrary code, tamper with data, and disclose sensitive information on affected systems. The vulnerability stems from CWE-502 (Deserialization of Untrusted Data), where a crafted malicious payload supplied to the Bridge component triggers unsafe deserialization, granting the attacker full control over the vulnerable process. No public exploit or CISA KEV listing has been identified at time of analysis, but the high-impact CVSS 7.8 score reflects the severity of successful exploitation.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local low-privileged attacker to achieve code execution, tamper with data, and disclose sensitive information on the affected host. The CVSS:3.1 score of 7.8 (High) with a local attack vector reflects that exploitation requires an existing foothold on the system, but the low privilege requirement and no user interaction needed make post-access exploitation straightforward. No public exploit code or CISA KEV listing has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes systems to code execution, data tampering, and information disclosure when an attacker with local user access supplies a malicious serialized payload to the Bridge process. The local attack vector (AV:L) and low-privilege requirement (PR:L) place this vulnerability in the context of shared AI/ML training infrastructure - multi-tenant GPU clusters where lateral movement between users is the realistic threat model. No public exploit code has been identified and the vulnerability is absent from the CISA KEV catalog at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The CVSS 7.8 score (AV:L/PR:L) constrains exploitation to local contexts, but the high impact across all three CIA triad components reflects the severity of a successful exploit. No public exploit code and no CISA KEV listing have been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, tamper with data, and disclose sensitive information on affected systems. Rooted in CWE-502, the flaw arises when the bridge component deserializes attacker-influenced data without adequate validation - a well-understood attack class that is particularly dangerous in distributed AI training infrastructure where serialized model state or inter-process messages transit between components. No public exploit code has been identified and the vulnerability is not listed in the CISA KEV catalog at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes AI training infrastructure to code execution, data tampering, and information disclosure by local low-privileged attackers. The vulnerability (CWE-502) resides in a bridge component of the Megatron-LM distributed training framework, used extensively in large-scale LLM training clusters. No public exploit code or CISA KEV listing has been identified at time of analysis; however, CVSS 7.8 (High) reflects the severity of a full triad (C:H/I:H/A:H) impact if exploitation succeeds.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker holding standard user privileges to achieve arbitrary code execution, data tampering, and information disclosure on the affected host. The CVSS 3.1 score of 7.8 (AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) confirms the exploitation path is local and low-privilege - no network exposure or administrator rights are required, making insider threats, shared-access HPC environments, and compromised user accounts the primary risk vectors. No public exploit code or active exploitation has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local, low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The vulnerability (CWE-502) stems from the application accepting and processing serialized data without adequate validation, enabling crafted payloads to subvert normal deserialization logic. No public exploit code or CISA KEV listing has been identified at time of analysis, but the full C:H/I:H/A:H impact triad indicates a severe outcome if exploited by a user with existing local access.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-privilege access to execute arbitrary code, tamper with data, and disclose sensitive information. The CVSS vector (AV:L/AC:L/PR:L) indicates the vulnerability is exploitable locally without elevated privileges or user interaction, making it a significant risk in multi-tenant distributed AI training environments where multiple users share infrastructure. No public exploit or KEV listing is confirmed at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local, low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The vulnerability carries a CVSS 3.1 score of 7.8 with a local attack vector, indicating that an attacker with an existing foothold on the system can escalate impact significantly. No public exploit code or CISA KEV listing has been identified at time of analysis, but the full CIA triad impact (High/High/High) makes this a high-priority remediation target for any organization running Megatron Bridge in research or production AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-privilege access to execute arbitrary code, tamper with application data, and exfiltrate sensitive information. The CVSS vector (AV:L/AC:L/PR:L/UI:N) confirms exploitation is bounded to local authenticated users or processes, but the full C:H/I:H/A:H impact triad makes successful exploitation highly damaging within that local scope. No public exploit has been identified at time of analysis, and no CISA KEV listing has been observed.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local, low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The local attack vector (AV:L) and low-privilege requirement (PR:L) limit the attack surface to users or processes with existing system access, yet the full C:H/I:H/A:H impact triad makes successful exploitation highly consequential. No public exploit code and no CISA KEV listing have been identified at time of analysis, though the NVIDIA PSIRT has published a security advisory via their product-security GitHub repository.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, data tampering, and sensitive information disclosure on the affected system. The CVSS 7.8 base score reflects a local attack vector requiring only low-privilege access with no user interaction, producing full high-impact compromise across confidentiality, integrity, and availability. No public exploit has been identified at time of analysis and the vulnerability is not listed in the CISA KEV catalog, but the severity of potential impact warrants prompt patching in AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, data tampering, and information disclosure on the affected host. The CVSS 3.1 vector (AV:L/AC:L/PR:L/UI:N, C:H/I:H/A:H) indicates a local, low-complexity exploit path yielding full triad compromise - consistent with classic unsafe deserialization primitives that reconstruct attacker-controlled object graphs. No public exploit or CISA KEV listing has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, tamper with data, and disclose sensitive information. The vulnerability (CWE-502) exists in the Megatron Bridge component of NVIDIA's large-scale model training infrastructure, where attacker-controlled serialized input is processed without adequate validation. No public exploit code or active exploitation via CISA KEV has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-privilege access to achieve code execution, data tampering, and information disclosure on the host system. The vulnerability (CWE-502) is exploitable locally without user interaction, making it particularly relevant in multi-tenant high-performance compute environments where Megatron Bridge is used for large-scale model training pipelines. No public exploit code or active exploitation has been identified at time of analysis, but the full C/I/A impact triad elevates the urgency for affected deployments.
Local code execution in NVIDIA Megatron Bridge exploits unsafe deserialization of attacker-controlled data, allowing a low-privileged local user to achieve full process compromise with high confidentiality, integrity, and availability impact. The CVSS 7.8 (High) vector - AV:L/AC:L/PR:L/UI:N - confirms that no network exposure, user interaction, or elevated privileges are required beyond an initial local foothold. No public exploit code and no CISA KEV listing have been identified at time of analysis, but the RCE-capable impact class warrants prompt remediation in multi-user AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes affected systems to code execution, data tampering, and information disclosure by a local low-privileged attacker. The flaw (CWE-502) allows a maliciously crafted serialized object to hijack the application's deserialization routine, granting the attacker the full CIA impact of the process context without requiring elevated privileges or user interaction. No public exploit code has been identified at time of analysis, and the vulnerability is not listed in CISA KEV; however, the high CIA impact and low attack complexity make this a meaningful priority for any organization running Megatron Bridge in multi-tenant or shared compute environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a low-privileged local user to achieve arbitrary code execution, data tampering, and information disclosure on the affected host. Reported directly by NVIDIA PSIRT (psirt@nvidia.com) and classified CWE-502, the flaw requires only local system access with standard user privileges, elevating insider threat and lateral-movement risk in shared AI training environments. No public exploit code or active exploitation has been confirmed at time of analysis, but the low attack complexity and full C/I/A impact make patching a real operational priority for any deployment.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, data tampering, and information disclosure on affected systems. The CVSS 3.1 score of 7.8 (AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) reflects full CIA impact from a local, low-complexity attack requiring no user interaction, making this a meaningful privilege escalation and code execution risk in shared compute environments such as multi-tenant GPU training clusters. No public exploit code or CISA KEV listing has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local low-privileged attacker to achieve code execution, corrupt data, and exfiltrate sensitive information. The vulnerability (CWE-502) is exploitable locally with low privileges and no user interaction, yielding a CVSS 7.8 High rating with full confidentiality, integrity, and availability impact. No public exploit code has been identified at the time of analysis, and CISA has not added this to the Known Exploited Vulnerabilities catalog.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes local users to code execution, data tampering, and information disclosure. An attacker with low-privileged local access can supply crafted serialized payloads to the Bridge component, which are deserialized without adequate validation. No public exploit code or active exploitation has been identified at time of analysis, but the high C/I/A impact and low-complexity exploitation path make this a meaningful risk in multi-tenant AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes systems to local code execution, data tampering, and information disclosure from a low-privileged local user. The vulnerability (CWE-502) allows an attacker with local access to supply malicious serialized payloads that the bridge processes without sufficient validation. No public exploit or CISA KEV listing is identified at time of analysis, but the full-triad high-impact CVSS score (C:H/I:H/A:H) signals severe post-exploitation potential on any host running the component.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve code execution, data tampering, and information disclosure on the host system. The CVSS:3.1 vector (AV:L/PR:L) confirms this is a local-access vulnerability targeting NVIDIA's distributed large-model training infrastructure, where a compromised or malicious low-privileged user on the same host could supply a crafted serialized payload to the Bridge component. No public exploit or CISA KEV listing has been identified at time of analysis, but the full-triad impact (C:H/I:H/A:H) makes this a meaningful threat in multi-tenant AI training cluster environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve full system compromise, including arbitrary code execution, data tampering, and information disclosure. The CVSS 3.1 score of 7.8 (AV:L/AC:L/PR:L/UI:N) confirms that exploitation requires local access with minimal privilege but no user interaction, making it a realistic threat in multi-tenant AI training environments where Megatron Bridge is used. No public exploit code or CISA KEV listing has been identified at the time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local low-privileged attacker to achieve arbitrary code execution, tamper with data, and disclose sensitive information on the affected host. The CVSS 7.8 score with local attack vector and low-privilege requirement indicates an authenticated local user can exploit the flaw without user interaction, fully compromising confidentiality, integrity, and availability. No public exploit or active exploitation has been identified at time of analysis, though the CIA triad is fully impacted on successful exploitation, making this a meaningful risk in shared compute environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local low-privileged attacker to achieve code execution, data tampering, and information disclosure with no user interaction required. The AV:L/PR:L CVSS vector confines the attack to actors who already hold a valid local account on the affected host, limiting but not eliminating real-world risk in shared AI infrastructure. No public exploit code has been identified, and this vulnerability has not been listed in CISA's Known Exploited Vulnerabilities catalog at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected system. The CVSS vector (AV:L/PR:L) confirms exploitation requires local access with standard user privileges, making this most relevant to shared multi-user HPC or AI/ML training cluster environments where multiple users interact with the same Megatron infrastructure. No public exploit code or active exploitation (CISA KEV) has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a low-privileged local attacker to achieve arbitrary code execution, data tampering, and information disclosure on affected systems. The flaw (CWE-502) requires only an authenticated local OS session - no elevated privileges or user interaction - making it exploitable by any standard user on a host running the Bridge component. Reported directly by NVIDIA PSIRT, no public exploit has been identified at the time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-level privileges to achieve code execution, data tampering, and information disclosure on the affected system. The CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H vector indicates exploitation requires only local, low-privileged access with no user interaction, making this a meaningful threat in multi-tenant AI training environments where shared compute access is common. No public exploit code or active exploitation via CISA KEV has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to execute arbitrary code, tamper with data, and disclose sensitive information on affected systems. The vulnerability stems from CWE-502 (Deserialization of Untrusted Data), where a crafted malicious payload supplied to the Bridge component triggers unsafe deserialization, granting the attacker full control over the vulnerable process. No public exploit or CISA KEV listing has been identified at time of analysis, but the high-impact CVSS 7.8 score reflects the severity of successful exploitation.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local low-privileged attacker to achieve code execution, tamper with data, and disclose sensitive information on the affected host. The CVSS:3.1 score of 7.8 (High) with a local attack vector reflects that exploitation requires an existing foothold on the system, but the low privilege requirement and no user interaction needed make post-access exploitation straightforward. No public exploit code or CISA KEV listing has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes systems to code execution, data tampering, and information disclosure when an attacker with local user access supplies a malicious serialized payload to the Bridge process. The local attack vector (AV:L) and low-privilege requirement (PR:L) place this vulnerability in the context of shared AI/ML training infrastructure - multi-tenant GPU clusters where lateral movement between users is the realistic threat model. No public exploit code has been identified and the vulnerability is absent from the CISA KEV catalog at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The CVSS 7.8 score (AV:L/PR:L) constrains exploitation to local contexts, but the high impact across all three CIA triad components reflects the severity of a successful exploit. No public exploit code and no CISA KEV listing have been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, tamper with data, and disclose sensitive information on affected systems. Rooted in CWE-502, the flaw arises when the bridge component deserializes attacker-influenced data without adequate validation - a well-understood attack class that is particularly dangerous in distributed AI training infrastructure where serialized model state or inter-process messages transit between components. No public exploit code has been identified and the vulnerability is not listed in the CISA KEV catalog at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge exposes AI training infrastructure to code execution, data tampering, and information disclosure by local low-privileged attackers. The vulnerability (CWE-502) resides in a bridge component of the Megatron-LM distributed training framework, used extensively in large-scale LLM training clusters. No public exploit code or CISA KEV listing has been identified at time of analysis; however, CVSS 7.8 (High) reflects the severity of a full triad (C:H/I:H/A:H) impact if exploitation succeeds.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker holding standard user privileges to achieve arbitrary code execution, data tampering, and information disclosure on the affected host. The CVSS 3.1 score of 7.8 (AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) confirms the exploitation path is local and low-privilege - no network exposure or administrator rights are required, making insider threats, shared-access HPC environments, and compromised user accounts the primary risk vectors. No public exploit code or active exploitation has been identified at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local, low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The vulnerability (CWE-502) stems from the application accepting and processing serialized data without adequate validation, enabling crafted payloads to subvert normal deserialization logic. No public exploit code or CISA KEV listing has been identified at time of analysis, but the full C:H/I:H/A:H impact triad indicates a severe outcome if exploited by a user with existing local access.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-privilege access to execute arbitrary code, tamper with data, and disclose sensitive information. The CVSS vector (AV:L/AC:L/PR:L) indicates the vulnerability is exploitable locally without elevated privileges or user interaction, making it a significant risk in multi-tenant distributed AI training environments where multiple users share infrastructure. No public exploit or KEV listing is confirmed at time of analysis.
Deserialization of untrusted data in NVIDIA Megatron Bridge enables a local, low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The vulnerability carries a CVSS 3.1 score of 7.8 with a local attack vector, indicating that an attacker with an existing foothold on the system can escalate impact significantly. No public exploit code or CISA KEV listing has been identified at time of analysis, but the full CIA triad impact (High/High/High) makes this a high-priority remediation target for any organization running Megatron Bridge in research or production AI training environments.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low-privilege access to execute arbitrary code, tamper with application data, and exfiltrate sensitive information. The CVSS vector (AV:L/AC:L/PR:L/UI:N) confirms exploitation is bounded to local authenticated users or processes, but the full C:H/I:H/A:H impact triad makes successful exploitation highly damaging within that local scope. No public exploit has been identified at time of analysis, and no CISA KEV listing has been observed.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local, low-privileged attacker to achieve code execution, data tampering, and information disclosure on the affected host. The local attack vector (AV:L) and low-privilege requirement (PR:L) limit the attack surface to users or processes with existing system access, yet the full C:H/I:H/A:H impact triad makes successful exploitation highly consequential. No public exploit code and no CISA KEV listing have been identified at time of analysis, though the NVIDIA PSIRT has published a security advisory via their product-security GitHub repository.
Deserialization of untrusted data in NVIDIA Megatron Bridge allows a local attacker with low privileges to achieve arbitrary code execution, data tampering, and sensitive information disclosure on the affected system. The CVSS 7.8 base score reflects a local attack vector requiring only low-privilege access with no user interaction, producing full high-impact compromise across confidentiality, integrity, and availability. No public exploit has been identified at time of analysis and the vulnerability is not listed in the CISA KEV catalog, but the severity of potential impact warrants prompt patching in AI training environments.