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OpenEXR Heap-Based Buffer Overflow in Deep Scanline Parsing via Forged Unpacked Size

High severity GitHub Reviewed Published Jul 31, 2025 in AcademySoftwareFoundation/openexr • Updated Aug 1, 2025

Package

pip OpenEXR (pip)

Affected versions

>= 3.3.0, < 3.3.3

Patched versions

3.3.3

Description

Summary

The OpenEXRCore code is vulnerable to a heap-based buffer overflow during a write operation when decompressing ZIPS-packed deep scan-line EXR files with a maliciously forged chunk header.

Details

When parsing STORAGE_DEEP_SCANLINE chunks from an EXR file, the following code (from src/lib/OpenEXRCore/chunk.c) is used to extract the chunk information:

if (part->storage_mode == EXR_STORAGE_DEEP_SCANLINE)
// SNIP...
        cinfo->sample_count_data_offset = dataoff;
        cinfo->sample_count_table_size  = (uint64_t) ddata[0];
        cinfo->data_offset              = dataoff + (uint64_t) ddata[0];
        cinfo->packed_size              = (uint64_t) ddata[1];
        cinfo->unpacked_size            = (uint64_t) ddata[2];
// SNIP...

By storing this information, the code that will later decompress and reconstruct the chunk bytes, will know how much space the uncompressed data will occupy.

This size is carried along in the chain of decoding/decompression until the undo_zip_impl function in src/lib/OpenEXRCore/internal_zip.c:

static exr_result_t
undo_zip_impl (
    exr_decode_pipeline_t* decode,
    const void*            compressed_data,
    uint64_t               comp_buf_size,
    void*                  uncompressed_data,
    uint64_t               uncompressed_size,
    void*                  scratch_data,
    uint64_t               scratch_size)
{
    size_t       actual_out_bytes;
    exr_result_t res;

    if (scratch_size < uncompressed_size) return EXR_ERR_INVALID_ARGUMENT;

    res = exr_uncompress_buffer (
        decode->context,
        compressed_data,
        comp_buf_size,
        scratch_data,
        scratch_size,
        &actual_out_bytes);

    if (res == EXR_ERR_SUCCESS)
    {
        decode->bytes_decompressed = actual_out_bytes;
        if (comp_buf_size > actual_out_bytes)
            res = EXR_ERR_CORRUPT_CHUNK;
        else
            internal_zip_reconstruct_bytes (
                uncompressed_data, scratch_data, actual_out_bytes);
    }

    return res;
}

The uncompressed_size comes from the unpacked_size extracted earlier, and the uncompressed_data is a buffer allocated by making space for the size "advertised" in the chunk information.

However, scratch_data and actual_out_bytes will contain, after decompression, the uncompressed data and its size, respectively.

The vulnerability lies in the fact that the undo_zip_impl function lacks code to check whether actual_out_bytes is greater than uncompressed_size.

The effect is that, by setting the unpacked_size in the chunk header smaller than the actual chunk decompressed data, it is possible - in the internal_zip_reconstruct_bytes function - to overflow past the boundaries of a heap chunk.

PoC

NOTE: you can download the heap_overflow.exr file from this link:

https://github.com/ShielderSec/poc/tree/main/CVE-2025-48071

  1. Compile the exrcheck binary in a macOS or GNU/Linux machine with ASAN.
  2. Open the heap_overflow.exr file with the following command:
exrcheck heap_overflow.exr
  1. Notice that exrcheck crashes with an ASAN stack-trace.
    image

Impact

An attacker might exploit this vulnerability by feeding a maliciously crafted file to a program that uses the OpenEXR libraries, thus gaining the capability to write an arbitrary amount of bytes in the heap. This could potentially result in code execution in the process.

References

@cary-ilm cary-ilm published to AcademySoftwareFoundation/openexr Jul 31, 2025
Published to the GitHub Advisory Database Jul 31, 2025
Reviewed Jul 31, 2025
Published by the National Vulnerability Database Jul 31, 2025
Last updated Aug 1, 2025

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Local
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction Active
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(2nd percentile)

Weaknesses

Heap-based Buffer Overflow

A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc(). Learn more on MITRE.

CVE ID

CVE-2025-48071

GHSA ID

GHSA-h45x-qhg2-q375

Source code

Credits

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