CVE-2026-20911
Heap-Based Buffer Overflow in LibRaw HuffTable::initval Function
Publication date: 2026-04-07
Last updated on: 2026-04-10
Assigner: Talos
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| libraw | libraw | 0.22.0 |
| libraw | libraw | 0.22.1 |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-131 | The product does not correctly calculate the size to be used when allocating a buffer, which could lead to a buffer overflow. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
CVE-2026-20911 is a critical heap-based buffer overflow vulnerability in the HuffTable::initval function of the LibRaw library. This function initializes Huffman decoding tables based on a bits array input derived from untrusted image files. The vulnerability occurs because the function does not validate the bits array against the mathematical constraints required for Huffman coding, specifically the Kraft inequality.
As a result, a specially crafted malicious RAW image file can specify code counts that require more entries than the allocated buffer size, causing the function to write beyond the allocated memory buffer. This leads to a heap buffer overflow.
The root cause is the failure to check the validity of the bits array, which allows attackers to trigger memory corruption by providing malicious input files.
How can this vulnerability impact me? :
This vulnerability can have severe impacts including arbitrary code execution, denial of service, and memory corruption. An attacker can exploit this by providing a malicious RAW image file to the LibRaw library, triggering the heap buffer overflow.
Because the vulnerability allows writing beyond allocated memory, it can lead to crashes or allow an attacker to execute malicious code with the privileges of the application using LibRaw.
The CVSS v3.1 base score of 9.8 reflects the high severity and potential impact of this vulnerability.
How can this vulnerability be detected on my network or system? Can you suggest some commands?
This vulnerability is triggered by processing specially crafted malicious RAW image files using the LibRaw library. Detection involves monitoring for crashes or memory corruption events related to LibRaw when handling RAW images.
One practical approach is to use AddressSanitizer or similar memory error detection tools to run applications that use LibRaw and observe if heap-buffer-overflow errors occur during the HuffTable::initval function execution.
Since the vulnerability is triggered by malicious files, scanning incoming RAW image files for suspicious or malformed Huffman tables could help, but no specific detection commands are provided.
No explicit commands for detection on network or system are provided in the available resources.
What immediate steps should I take to mitigate this vulnerability?
The immediate mitigation step is to update the LibRaw library to the patched version released by the vendor on April 6, 2026, which addresses this heap-based buffer overflow vulnerability.
Until the update can be applied, avoid processing untrusted or suspicious RAW image files with vulnerable versions of LibRaw to prevent exploitation.
Implementing input validation or sandboxing the image processing environment may reduce risk, but the primary and recommended action is to apply the official patch.
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
The provided information does not specify any direct impact of this vulnerability on compliance with common standards and regulations such as GDPR or HIPAA.