CVE-2026-51263 in ESP32-audioI2S
Summary
by MITRE • 07/28/2026
schreibfaul1 ESP32-audioI2S 3.4.5 is vulnerable to Buffer Overflow. The Audio::openai_speech function in the Audio library manually constructs JSON request bodies and HTTP request headers by directly concatenating externally controllable input and instructions strings without effective length restriction and boundary validation. An unauthenticated remote attacker can send oversized malicious string data to trigger a heap buffer overflow during string splicing, resulting in memory corruption.
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Analysis
by VulDB Data Team • 07/28/2026
The vulnerability in schreibfaul1 ESP32-audioI2S version 3.4.5 represents a critical buffer overflow flaw that stems from improper input validation within the Audio::openai_speech function. This function demonstrates poor defensive programming practices by directly concatenating externally controlled data with hardcoded strings and instructions without implementing adequate length restrictions or boundary checks. The specific implementation constructs JSON request bodies and HTTP headers through string manipulation techniques that fail to account for potential input size limitations, creating an exploitable condition where malicious data can exceed allocated buffer boundaries.
The technical exploitation of this vulnerability occurs through unauthenticated remote attack vectors where an attacker can craft oversized malicious strings and inject them into the function parameters. When these oversized inputs are processed through the manual string concatenation logic, the heap-based buffer overflow manifests during the dynamic memory allocation phase of string splicing operations. The corrupted memory can lead to arbitrary code execution, system instability, or complete device compromise depending on the attacker's control over the memory layout and execution flow.
This vulnerability aligns with CWE-121, which addresses stack buffer overflow conditions, and CWE-122, covering heap buffer overflow scenarios in software applications. The attack surface extends beyond simple memory corruption to include potential privilege escalation and persistent system compromise through the exploitation of the heap-based memory corruption patterns typical in embedded IoT devices. The ATT&CK framework categorizes this as a remote code execution technique under T1059 where adversaries leverage application vulnerabilities to execute malicious code on target systems.
The operational impact of this vulnerability extends significantly within IoT environments where ESP32-based audio devices may serve as part of larger networked systems or be deployed in sensitive locations. Attackers could potentially gain unauthorized access to audio processing systems, manipulate voice data transmission, or use the compromised device as a foothold for further network penetration. The lack of authentication requirements makes this vulnerability particularly dangerous as it enables immediate exploitation without prior access credentials, potentially affecting multiple devices within the same network segment.
Mitigation strategies should focus on implementing strict input validation mechanisms within the Audio::openai_speech function including maximum string length enforcement, proper buffer boundary checks, and sanitization of all externally controlled inputs. Developers must replace manual string concatenation operations with safer alternatives such as bounded string functions or dedicated JSON parsing libraries that inherently handle memory management and input validation. Additionally, implementing proper error handling and memory safety checks in the embedded environment can prevent exploitation attempts and provide early detection mechanisms for potential attacks against the audio processing framework.