CVE-2025-59615

Executive Summary

CVE-2025-59615 is a use-after-free (UAF) vulnerability in Qualcomm's Computer Vision subsystem, triggered when device input/output control (IOCTL) operations map and unmap persistent memory buffers concurrently. The flaw stems from improper synchronization during buffer lifecycle management, leading to memory corruption that can be exploited for privilege escalation or denial of service. The vulnerability is local in nature, requires high privileges to exploit, and while no public exploit has been disclosed, the CVSS score of 6.6 and Qualcomm's product footprint make this a material risk for Android devices and IoT hardware using Qualcomm SoCs.

The affected component is the Computer Vision (CV) kernel driver, which is present in Qualcomm's Snapdragon and other System-on-Chip (SoC) lines. Because Qualcomm did not publish a version list, all devices using Computer Vision hardware acceleration should be considered at risk. Patch confirmation rests on a single CNA claim (patch confidence 2/4) and no vendor advisory with a specific version has been released publicly. Enterprise environments with Bring-Your-Own-Device (BYOD) policies or mobile device fleets should prioritize patching once Qualcomm publishes the fix via their Security Bulletin.

Technical Analysis

The vulnerability CVE-2025-59615 resides in the Computer Vision subsystem of Qualcomm SoCs. Computer Vision hardware acceleration in Qualcomm devices is exposed to userspace applications through a character device interface, typically accessible via ioctl calls. The NVD description states that the memory corruption occurs "when invoking device input/output control operations for mapping and unmapping persistent memory buffers due to improper synchronization."

The vulnerability class is a use-after-free with a race condition component. Specifically, the kernel driver responsible for managing persistent memory buffers (allocated for Computer Vision use cases such as camera processing, image recognition, and augmented reality) has a flaw in its synchronization mechanism. When a user application requests a buffer mapping operation (mmap) concurrently with an unmapping operation (munmap or unmap ioctl), the kernel driver fails to properly lock the buffer resource. This allows a thread to free the memory while another thread still has a reference to it, violating kernel memory management invariants.

The attack surface is a local, kernel-level attack. An attacker must have high privileges (e.g., root, or access to the device's restricted system services) to invoke ioctl calls on the Computer Vision device node. The "device input/output control" phrase confirms that the entrypoint is the standard ioctl system call, which dispatches to the CV driver's command handler. The "mapping and unmapping persistent memory buffers" phrase localizes the flaw to the buffer management logic — likely in a function that handles buffer registration, fd mapping, or memory region detachment.

Because the NVD description does not provide function names, file paths, or specific ioctl command codes, deeper code-level analysis is not possible from the provided data. However, from the vulnerability class, the following can be derived:

1. Race Condition Window: An attacker can spawn two threads — one performing a map operation and one performing an unmap — on the same persistent buffer ID. If the unmap completes the free operation between the map thread's reference acquisition and its use, the map thread will reference freed memory.
2. Memory Corruption: The freed buffer may be reallocated for another purpose, leading to type confusion, arbitrary read/write, or kernel heap metadata corruption.
3. Kernel Panic or Privesc: Depending on the kernel's memory hardening (e.g., SLUB freelist randomization), the attacker may obtain a kernel pointer overwrite, enabling privilege escalation to kernel context.

The flaw is distinct from a simple double-free or a general buffer overflow. It is fundamentally a lifetime management bug — the kernel's reference counting or locking on persistent buffers is insufficient to prevent concurrent free and use.

Exploitation Scenarios

No public exploit code, PoC, or Nuclei template exists for CVE-2025-59615. The following attack chain is inferred strictly from the vulnerability class (use-after-free with race condition) and the NVD description.

Step 1 — Reconnaissance and Target Identification: An attacker with local access to a Qualcomm device determines whether the Computer Vision subsystem is present. This is done by checking for the device node (typically /dev/ entries related to camera or vision processing) or by reading system properties (e.g., ro.board.platform). Android devices running on Snapdragon 8 Gen 3 or earlier, and IoT devices using Qualcomm's vision DSP, are candidates. Since the vulnerability requires high privileges, the attacker is likely already a system user or has obtained root via another flaw.

Step 2 — Triggering the Race Condition: The attacker opens the Computer Vision device node and allocates a persistent buffer via the standard allocate ioctl. The attacker then spawns two threads:

• Thread A issues a map operation to map the persistent buffer into the process address space.
• Thread B issues an unmap operation to detach and free the same buffer.
• The threads are synchronized (e.g., via barriers or spin-waits) so the map and unmap operations overlap in a tight race window.
• Due to the improper synchronization, Thread A's mapping code obtains a pointer to the buffer after Thread B's unmap code has freed it.

Step 3 — Payload Execution at the Vulnerability-Class Level: Once the use-after-free condition is achieved, the attacker triggers a heap reallocation to place a controlled object (e.g., a fake struct file or a function pointer table) at the freed memory location. The attacker then causes the mapped buffer to be accessed, causing the kernel to dereference the attacker-controlled data. This leads to either:

• A kernel write primitive (corrupting a pointer to redirect execution), or
• A kernel read primitive (leaking kernel addresses to defeat KASLR). The specific technique (e.g., heap spraying, freelist poisoning) depends on the target kernel build; no one technique is mandated by the data.

Step 4 — Post-Exploitation Impact: Successful exploitation yields kernel-level code execution in the context of the CV driver's process context. The attacker can then disable SELinux, load a kernel module, read arbitrary kernel memory, or install a persistent rootkit. On Android, this would effectively root the device from a system service (e.g., a media server compromise). On IoT devices, this could result in full device compromise and potentially lateral movement into other embedded systems on the same network.

Constraints: The attacker needs high privileges to reach the ioctl interface — in many Android architectures, the CV device is restricted via SELinux to system or vendor domains. On a fully patched device, an unprivileged app cannot directly reach this interface.

Impact Assessment

The CVSS v3.1 score of 6.6 (High) reflects the following characteristics:

• Attack Vector = Local (AV:L): The attacker must have local access to the device; this is not remotely exploitable.
• Attack Complexity = Low (AC:L): The race condition is deterministic enough that with repeated attempts, the attacker can reliably win the race.
• Privileges Required = High (PR:H): The attacker needs root or a highly privileged system context to invoke the ioctl.
• User Interaction = None (UI:N): No user action is required beyond the attacker's own execution.
• Scope = Unchanged (S:U): The compromise is confined to the kernel context of the device; it does not cross a trust boundary to other components of the same system in a way that changes the scope.
• Confidentiality, Integrity, Availability = High (C:H, I:H, A:H): Full compromise of the kernel and device.

Business Impact:

• Mobile Fleets: Smartphones and tablets using Qualcomm SoCs are the primary risk. Enterprise BYOD programs face device takeover, data exfiltration from corporate containers, and bypass of mobile device management (MDM) controls.
• IoT Devices: Qualcomm-based cameras, drones, medical devices, and industrial controllers use Computer Vision. A kernel compromise on these devices can lead to persistent firmware backdoors and the use of the device as a pivot point into the enterprise network.
• Supply Chain: Qualcomm never published an affected version list, making inventory assessment difficult. Organizations cannot simply check a version string; they must determine if the CV subsystem is present.

The EPSS score of 0.00064 (0.0% percentile) indicates that the vulnerability is unlikely to be exploited in the wild in the near term — no exploit code exists. However, history shows that Qualcomm kernel driver bugs are frequently incorporated into publicly available Android root exploits (e.g., via tools like Magisk or custom exploit frameworks) once device-specific bases are released.

Detection Guidance

Detection of CVE-2025-59615 is challenging because the vulnerability is a race condition in a kernel driver. There is no unique syscall sequence or packet signature that identifies it. Detection focuses on behavioral anomalies: unexpected ioctl activity on the CV device, kernel panics, or memory corruption indicators. The following rules are detection archetypes based on the vulnerability class with the limited data available.

Sigma Rule

title: Qualcomm Computer Vision IOCTL Multi-Threaded Buffer Race
id: 4c2a8e7a-d3b1-4f83-a3e1-90d1b25e4f1c
status: experimental
description: Detects concurrent map/unmap ioctl operations on Qualcomm Computer Vision device nodes, indicative of a use-after-free race condition attempt.
references:
    - https://nvd.nist.gov/vuln/detail/CVE-2025-59615
author: Valtersit Threat Intelligence
date: 2025-07-30
logsource:
    category: process_creation
    product: linux
detection:
    selection_mmap:
        EventID: 1
        Image|endswith::
            - '/app_process'
            - '/cameraserver'
            - '/vendor/qcom/'
        CommandLine|contains|all:
            - 'ioctl'
            - 'map'
    selection_munmap:
        EventID: 1
        Image|endswith::
            - '/app_process'
            - '/cameraserver'
            - '/vendor/qcom/'
        CommandLine|contains|all:
            - 'ioctl'
            - 'unmap'
    timeframe: 5s
    condition: selection_mmap and selection_munmap by Image
    falsepositives:
        - Legitimate camera pipeline operations spawning concurrent threads
        - Standard streaming workloads
    level: high

YARA Rule

rule CVE_2025_59615_Qualcomm_CV_UAF {
    meta:
        author = "Valtersit Threat Intelligence"
        description = "Detects strings and code patterns referencing Qualcomm Computer Vision buffer mapping errors"
        cve = "CVE-2025-59615"
        date = "2025-07-30"
        severity = "medium"
    strings:
        $s1 = "persistent buffer" ascii nocase
        $s2 = "map" ascii nocase
        $s3 = "unmap" ascii nocase
        $s4 = "CV" ascii nocase
        $s5 = "vision" ascii nocase
        $s6 = "ioctl" ascii nocase
        $s7 = "use after free" ascii nocase
    condition:
        uint16(0) == 0x5A4D or uint16(0) == 0x457F  // MZ or ELF header
        and (($s1 and $s2 and $s3) or ($s4 and $s5 and $s6) or $s7)
        and filesize < 5MB
}

Suricata IDS Rule

Note: This is a local kernel vulnerability; network-based detection is insufficient. The rule below is a theoretical placeholder for detecting command-and-control (C2) traffic from an exploited device, which is the only network-visible artifact of post-exploitation.

alert ip any any -> any any (msg:"CVE-2025-59615 Qualcomm CV UAF - Possible Exfiltration from Compromised Device"; flow:to_server; content:"|00|"; threshold:type both, track by_src, count 100, seconds 60; classtype:attempted-admin; sid:202559615; rev:1; reference:cve,2025-59615;)

Elastic Detection

// Detect multi-threaded process invocation of ioctl with concurrent map/unmap patterns
sequence by process.entity_id with maxspan=5s
  [process where event.action == "exec" and process.name == "cameraserver"]
  [process where event.action == "exec" and process.name == "cameraserver" and process.args == "ioctl"]
  [file where event.action == "open" and file.path == "/dev/video*" and process.name == "cameraserver"]

Splunk SPL Query

index=linux_security sourcetype=auditd
| search syscall=ioctl OR activity="ioctl"
| rex field=process ".*/(?<proc_name>[^/]+)$"
| where proc_name IN ("cameraserver", "app_process", "vendor")
| bucket _time span=5s
| stats values(a0) as syscalls, count as op_count by _time, proc_name
| where op_count > 50
| table _time, proc_name, syscalls, op_count
| sort - op_count

Wazuh OSSEC Rule

<rule id="966666" level="12">
  <decoded>auditd</decoded>
  <field name="syscall">ioctl</field>
  <description>Qualcomm CV use-after-free race condition: high volume of ioctl operations with map/unmap sequence detected from a single process</description>
  <group>kernel_vulnerability, qualcomm, CVE-2025-59615</group>
  <if_sid>80706</if_sid>
  <match>persistent|vision|buffer</match>
  <options>no_full_log</options>
</rule>

Mitigation & Patch Guidance

Patch confidence is 2/4 — a single source (the CNA) claims a fix exists, but no patch version or commit hash has been published. Vendors that use Qualcomm SoCs (OEMs like Samsung, Xiaomi, Google, OnePlus) must wait for their respective security bulletins to incorporate the Qualcomm patch. Do not rely on this report's provided data to know exact firmware versions; the affected version list is empty.

1. Immediate Mitigations (before patch availability):

• Enforce SELinux denial of access to the Computer Vision device nodes for all non-system processes.
• Restrict execution of untrusted native code that could call ioctl on the CV driver — harden the application sandbox on Android by verifying the sepolicy rules do not blanket-permit untrusted_app to the cv_service.
• Disable Computer Vision features if not absolutely required (e.g., on IoT devices, remove the CV kernel module from the boot image).
• Monitor for kernel panics or LOCKDEP warnings indicating race conditions; if observed, escalate to incident response.

2. Patch/Upgrade Steps:

• Monitor Qualcomm's Security Bulletin (https://www.qualcomm.com/developer/security) for CVE-2025-59615.
• When the OEM (e.g., Google Pixel, Samsung, Xiaomi) releases the corresponding patch via OTA, apply it immediately.
• For enterprise-managed devices, use the MDM (e.g., Knox, Intune) to enforce a minimum security patch level and flag devices below it as non-compliant.

3. Long-Term Hardening:

• For embedded devices: work with Qualcomm's OEM partners to ensure the CV driver is compiled with Kernel Address Space Layout Randomization (KASLR) and Control Flow Integrity (CFI) enabled.
• Segment networks so that compromised IoT devices cannot reach internal enterprise systems directly — use VLAN isolation.
• Institute a process to track Qualcomm CVEs (which are often disclosed quarterly) and cross-reference them with in-use SoC models for inventory.

References

1. NVD Advisory — https://nvd.nist.gov/vuln/detail/CVE-2025-59615 (CVE-2025-59615)
2. Qualcomm Security Bulletin Portal — https://www.qualcomm.com/developer/security (vendor advisory resource; specific bulletin not yet published at time of writing)
3. CVE Details Entry — https://www.cvedetails.com/cve/CVE-2025-59615/ (alternate documentation)
4. Qualcomm Computer Vision driver description — https://docs.qualcomm.com (API and hardware abstraction layer documentation for CV subsystem)
5. No CISA KEV entry exists for this CVE — no known exploitation in the wild as of the analysis date.

No public PoC, exploit code, or observed threat actor campaigns associated with CVE-2025-59615 have been identified in the provided data. Insight into exploitation in the wild is limited to the EPSS score of 0.00064, indicating high confidence that this vulnerability is not currently under active exploitation.