ID CVE-2021-41206
Summary TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
References
Vulnerable Configurations
  • cpe:2.3:a:google:tensorflow:2.4.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc2:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc3:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc3:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc3:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc3:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc3:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc3:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc4:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc4:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.0:rc4:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.0:rc4:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.1:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.1:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.2:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.2:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.4.3:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.4.3:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.5.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.5.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.5.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.5.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.5.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.5.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.5.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.5.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.5.0:rc3:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.5.0:rc3:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.5.1:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.5.1:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.6.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.6.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.7.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.7.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.7.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.7.0:rc1:*:*:*:*:*:*
CVSS
Base: 4.6 (as of 09-11-2021 - 17:56)
Impact:
Exploitability:
CWE CWE-354
CAPEC
  • Padding Oracle Crypto Attack
    An adversary is able to efficiently decrypt data without knowing the decryption key if a target system leaks data on whether or not a padding error happened while decrypting the ciphertext. A target system that leaks this type of information becomes the padding oracle and an adversary is able to make use of that oracle to efficiently decrypt data without knowing the decryption key by issuing on average 128*b calls to the padding oracle (where b is the number of bytes in the ciphertext block). In addition to performing decryption, an adversary is also able to produce valid ciphertexts (i.e., perform encryption) by using the padding oracle, all without knowing the encryption key. Any cryptosystem can be vulnerable to padding oracle attacks if the encrypted messages are not authenticated to ensure their validity prior to decryption, and then the information about padding error is leaked to the adversary. This attack technique may be used, for instance, to break CAPTCHA systems or decrypt/modify state information stored in client side objects (e.g., hidden fields or cookies). This attack technique is a side-channel attack on the cryptosystem that uses a data leak from an improperly implemented decryption routine to completely subvert the cryptosystem. The one bit of information that tells the adversary whether a padding error during decryption has occurred, in whatever form it comes, is sufficient for the adversary to break the cryptosystem. That bit of information can come in a form of an explicit error message about a padding error, a returned blank page, or even the server taking longer to respond (a timing attack). This attack can be launched cross domain where an adversary is able to use cross-domain information leaks to get the bits of information from the padding oracle from a target system / service with which the victim is communicating. To do so an adversary sends a request containing ciphertext to the target system. Due to the browser's same origin policy, the adversary is not able to see the response directly, but can use cross-domain information leak techniques to still get the information needed (i.e., information on whether or not a padding error has occurred). For instance, this can be done using "img" tag plus the onerror()/onload() events. The adversary's JavaScript can make web browsers to load an image on the target site, and know if the image is loaded or not. This is 1-bit information needed for the padding oracle attack to work: if the image is loaded, then it is valid padding, otherwise it is not.
  • Checksum Spoofing
    An adversary spoofs a checksum message for the purpose of making a payload appear to have a valid corresponding checksum. Checksums are used to verify message integrity. They consist of some value based on the value of the message they are protecting. Hash codes are a common checksum mechanism. Both the sender and recipient are able to compute the checksum based on the contents of the message. If the message contents change between the sender and recipient, the sender and recipient will compute different checksum values. Since the sender's checksum value is transmitted with the message, the recipient would know that a modification occurred. In checksum spoofing an adversary modifies the message body and then modifies the corresponding checksum so that the recipient's checksum calculation will match the checksum (created by the adversary) in the message. This would prevent the recipient from realizing that a change occurred.
  • Manipulating Writeable Configuration Files
    Generally these are manually edited files that are not in the preview of the system administrators, any ability on the attackers' behalf to modify these files, for example in a CVS repository, gives unauthorized access directly to the application, the same as authorized users.
Access
VectorComplexityAuthentication
LOCAL LOW NONE
Impact
ConfidentialityIntegrityAvailability
PARTIAL PARTIAL PARTIAL
cvss-vector via4 AV:L/AC:L/Au:N/C:P/I:P/A:P
Last major update 09-11-2021 - 17:56
Published 05-11-2021 - 22:15
Last modified 09-11-2021 - 17:56
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