CVE Vulnerabilities

CVE-2023-34454

Integer Overflow or Wraparound

Published: Jun 15, 2023 | Modified: Jun 27, 2023
CVSS 3.x
7.5
HIGH
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CVSS 2.x
RedHat/V2
RedHat/V3
Ubuntu

snappy-java is a fast compressor/decompressor for Java. Due to unchecked multiplications, an integer overflow may occur in versions prior to 1.1.10.1, causing an unrecoverable fatal error.

The function compress(char[] input) in the file Snappy.java receives an array of characters and compresses it. It does so by multiplying the length by 2 and passing it to the rawCompress` function.

Since the length is not tested, the multiplication by two can cause an integer overflow and become negative. The rawCompress function then uses the received length and passes it to the natively compiled maxCompressedLength function, using the returned value to allocate a byte array.

Since the maxCompressedLength function treats the length as an unsigned integer, it doesn’t care that it is negative, and it returns a valid value, which is casted to a signed integer by the Java engine. If the result is negative, a java.lang.NegativeArraySizeException exception will be raised while trying to allocate the array buf. On the other side, if the result is positive, the buf array will successfully be allocated, but its size might be too small to use for the compression, causing a fatal Access Violation error.

The same issue exists also when using the compress functions that receive double, float, int, long and short, each using a different multiplier that may cause the same issue. The issue most likely won’t occur when using a byte array, since creating a byte array of size 0x80000000 (or any other negative value) is impossible in the first place.

Version 1.1.10.1 contains a patch for this issue.

Weakness

The product performs a calculation that can produce an integer overflow or wraparound, when the logic assumes that the resulting value will always be larger than the original value. This can introduce other weaknesses when the calculation is used for resource management or execution control.

Affected Software

Name Vendor Start Version End Version
Snappy-java Xerial * 1.1.10.1 (excluding)

Potential Mitigations

  • Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
  • If possible, choose a language or compiler that performs automatic bounds checking.
  • Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
  • Use libraries or frameworks that make it easier to handle numbers without unexpected consequences.
  • Examples include safe integer handling packages such as SafeInt (C++) or IntegerLib (C or C++). [REF-106]
  • Perform input validation on any numeric input by ensuring that it is within the expected range. Enforce that the input meets both the minimum and maximum requirements for the expected range.
  • Use unsigned integers where possible. This makes it easier to perform validation for integer overflows. When signed integers are required, ensure that the range check includes minimum values as well as maximum values.
  • Understand the programming language’s underlying representation and how it interacts with numeric calculation (CWE-681). Pay close attention to byte size discrepancies, precision, signed/unsigned distinctions, truncation, conversion and casting between types, “not-a-number” calculations, and how the language handles numbers that are too large or too small for its underlying representation. [REF-7]
  • Also be careful to account for 32-bit, 64-bit, and other potential differences that may affect the numeric representation.

References