The ADC API requires each driver to reject a sampling sequence whose destination buffer is too small: the buffer_size field of struct adc_sequence in include/zephyr/drivers/adc.h documents that "the driver must ensure that samples are not written beyond the limit and it must return an error if the buffer turns out to be not large enough". The ADI MAX32 driver did not honour that contract. start_read() in drivers/adc/adc_max32.c compared buffer_size, a byte count, against a sample count ((1 + extra_samplings) channels), ignoring sizeof(uint16_t), so it accepted a buffer half the required size. The samples are then stored through the uint16_t data->buffer by Wrap_MXC_ADC_GetData(), which writes two bytes per sample and advances the pointer by one uint16_t: in adc_max32_start_channel() for synchronous reads, and in adc_max32_isr() for asynchronous ones. A sequence selecting two channels with a two-byte buffer, for example, passes the check and has its second sample written past the end of the buffer.
On a build with CONFIG_USERSPACE, adc_read() and adc_read_async() are system calls. The handler in drivers/adc/adc_handlers.c copies the sequence in from user memory, verifies only that [buffer, buffer + buffer_size) is writable by the calling thread, and rejects a user-supplied options->callback; it deliberately leaves the size arithmetic to the driver. A user-mode thread that has been granted access to a MAX32 ADC device object therefore fully controls channels, buffer, buffer_size and options->extra_samplings, and can make the driver write twice as many bytes as its buffer holds. Because the check scales with extra_samplings, the overrun equals the length of the buffer itself, up to channels * 65536 bytes past its end, since the sample pointer is only rewound on a repeat sampling, never on the extra samplings of a sequence.
The resulting stores are performed by the driver in kernel mode (in the system call itself, the ADC context timer, or the ADC interrupt handler for asynchronous reads), where the MPU does not restrict the thread's memory domain, so the write walks linearly out of the user partition and into adjacent memory such as other partitions, kernel data or thread stacks. The impact is kernel-memory corruption of attacker-chosen length at an attacker-chosen offset, a plausible privilege-escalation and denial-of-service primitive from an unprivileged user-mode thread. Builds without CONFIG_USERSPACE are affected only as a caller-side robustness defect, since the application itself supplies the buffer.
The fix replaces that check in start_read() with a call to the new shared helper adc_sequence_validate_buffer() in drivers/adc/adc_common.c, passing sizeof(uint16_t) as the sample size. The helper computes active_channels sizeof(uint16_t) (1 + extra_samplings) and returns -ENOMEM before any sampling is started.
| Software | Affected versions |
|---|---|
| zephyrproject / zephyr | >= 4.0.0, < 4.4.2 |
A vulnerability database tells you what is broken. Attack surface management tells you where it is running: it discovers your internet-facing assets and flags the ones affected by issues like this one.
What is attack surface management? →A security vulnerability is a weakness in software, hardware, or configuration that can be exploited to compromise confidentiality, integrity, or availability. Many vulnerabilities are tracked as CVEs (Common Vulnerabilities and Exposures), which provide a standardized identifier so teams can coordinate patching, mitigation, and risk assessment across tools and vendors.
CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.
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Recurring findings usually come from incomplete Asset Discovery, inconsistent patch management, inherited images, and configuration drift. In modern environments, you also need to watch the software supply chain: dependencies, containers, build pipelines, and third-party services can reintroduce the same weakness even after you patch a single host. Unknown or unmanaged assets (often called Shadow IT) are a common reason the same issues resurface.
Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.
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