CVE-2025-0755
NVIDIA TensorRT-LLM Vulnerability — GPU memory corruption in tensor computation
Executive Summary
CVE-2025-0755 is a critical severity vulnerability affecting ai-code, binary-analysis, binary-analysis. It is classified as Out-of-bounds Write. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"At its core, this issue originates from within NVIDIA TensorRT-LLM Vulnerability —, allowing the mishandling of memory allocation boundaries. In practice, this allows unauthorized actors to compromise the entire application stack, rendering traditional defenses ineffective. The Precogs multi-engine scanning approach is specifically built to identify exploitable weaknesses before attackers do."
What is this vulnerability?
CVE-2025-0755 is categorized as a critical Buffer Overflow flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
NVIDIA TensorRT-LLM Vulnerability — GPU memory corruption in tensor computation. CVSS 9.8 — Hardware-level LLM vulnerability in NVIDIA GPU tensor operations.
This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.
Risk Assessment
| Metric | Value |
|---|---|
| CVSS Base Score | 9.8 (CRITICAL) |
| Vector String | N/A |
| Published | March 21, 2026 |
| Last Modified | March 21, 2026 |
| Related CWEs | CWE-787 |
Impact on Systems
✅ Remote Code Execution: Attackers can overwrite the instruction pointer (EIP/RIP) to redirect execution to malicious shellcode.
✅ Memory Corruption: Overwriting adjacent memory regions can corrupt critical application state, leading to unpredictable privilege escalation.
✅ Denial of Service: Triggering segmentation faults and kernel panics results in immediate disruption of critical systems.
How to fix this issue?
Implement the following strategic mitigations immediately to eliminate the attack surface.
1. Memory-Safe Languages Where possible, migrate critical parsing logic to memory-safe languages like Rust or Go.
2. Safe Standard Libraries Replace unbounded C functions (strcpy, sprintf) with boundary-checking equivalents (strncpy, snprintf).
3. Compiler Defenses Ensure software is compiled with modern defensive flags: ASLR, DEP/NX, Stack Canaries (SSP), and Position Independent Executables (PIE).
Vulnerability Signature
// Vulnerable C Function
void parse_network_packet(char *untrusted_data) \{
char local_buffer[128];
// VULNERABLE: strcpy does not verify the length of the source data
strcpy(local_buffer, untrusted_data);
printf("Packet Processed.");
\}
// EXPLOIT PAYLOAD: 128 bytes of padding + [Overwrite EIP Address]
References and Sources
- NVD — CVE-2025-0755
- MITRE — CVE-2025-0755
- CWE-787 — MITRE CWE
- CWE-787 Details
- AI Code Security Vulnerabilities
- Binary Analysis Vulnerabilities
- Binary Analysis Vulnerabilities
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | Network packet or file input |
| Vector | Data exceeds the allocated buffer bounds during a copy operation |
| Sink | strcpy(), memcpy(), or pointer arithmetic |
| Impact | Memory corruption, Remote Code Execution (RCE) |
Vulnerable Code Pattern
// ❌ VULNERABLE: Out-of-bounds write
void process_data(char *input) {
char buffer[64];
// Taint sink: copies without bounds checking
strcpy(buffer, input);
}
Secure Code Pattern
// ✅ SECURE: Bounded copy
void process_data(char *input) {
char buffer[64];
// Sanitized boundary check
strncpy(buffer, input, sizeof(buffer) - 1);
buffer[sizeof(buffer) - 1] = '\0';
}
How Precogs Detects This
Precogs Binary SAST engine explicitly uncovers memory boundary violations and unsafe memory management functions in compiled binaries.\n