CVE-2026-100136 in Content Credentials Rust SDK
Summary
by MITRE • 10/13/2026
CAI Content Credentials is affected by an Integer Overflow or Wraparound vulnerability that could result in an application denial-of-service. An attacker could exploit this vulnerability to crash the application, leading to a denial-of-service condition. Exploitation of this issue does not require user interaction.
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Analysis
by VulDB Data Team • 10/14/2026
The CAI Content Credentials library is susceptible to an integer overflow or wraparound vulnerability that poses a significant risk to application stability and availability. This specific flaw arises from improper handling of arithmetic operations involving numeric values, where the result exceeds the maximum limit for the allocated data type. In programming environments such as C or C++, when an operation produces a value larger than what can be represented by the variable's bit width, it wraps around to a negative number or a very small positive integer rather than throwing an exception. This behavior is particularly dangerous in memory allocation contexts where the calculated size determines how much heap space is reserved for subsequent operations.
The technical mechanism behind this vulnerability typically involves parsing external input that dictates buffer sizes or array lengths without adequate validation of the resulting arithmetic outcome. When an attacker supplies a crafted payload containing specific numeric values, they can trigger the overflow condition during internal calculations within the CAI Content Credentials processing logic. Because the library is designed to handle content credentials which may include metadata from various sources, it must process potentially untrusted input data. If the validation checks do not account for potential wraparound scenarios before allocating memory or iterating through arrays, the application proceeds with incorrect assumptions about resource availability and bounds.
The operational impact of exploiting this integer overflow is primarily a denial-of-service condition. When the wrapped-around value is used to allocate memory, it may request an unexpectedly small amount of space that does not accommodate the actual data being processed. Subsequent writes to this undersized buffer result in heap corruption or stack-based buffer overflows. Alternatively, if the wrapped value leads to infinite loops due to incorrect loop counter calculations, the application can become unresponsive by consuming excessive CPU resources until it is terminated by the operating system's watchdog mechanisms. In either scenario, the service provided by the CAI Content Credentials integration becomes unavailable, disrupting any downstream processes that rely on its functionality for verifying content authenticity and provenance.
This vulnerability aligns with Common Weakness Enumeration (CWE) category CWE-190, which defines integer overflow or wraparound errors. It also relates to CWE-787, out-of-bounds write vulnerabilities, as the initial arithmetic error often leads directly to memory corruption issues that can be leveraged for more severe attacks if not properly contained by system-level protections like ASLR and DEP. From a tactical perspective, this flaw supports denial-of-service objectives within the MITRE ATT&CK framework, specifically under techniques aimed at disrupting service availability without requiring authentication or user interaction, making it an attractive target for automated scanning tools seeking to destabilize infrastructure components that utilize this library.
Mitigation strategies must focus on rigorous input validation and safe arithmetic practices. Developers should implement checks to ensure that all numeric inputs fall within expected ranges before they are used in calculations involving memory allocation or loop control. Utilizing language features or libraries that provide checked arithmetic, which throw exceptions upon overflow rather than wrapping around, can prevent the initial error condition. Additionally, static analysis tools and fuzzing campaigns should be employed during the development lifecycle to identify such edge cases early. For existing deployments, applying vendor-provided patches is critical as they typically include bounds checking logic or updated parsing routines that correctly handle large numeric values without triggering overflow conditions.