VAITP Dataset

← Back to the dataset

CVE-2016-9243

HKDF returns empty byte-string for lengths less than digest_size.

  • CVSS 7.5
  • CWE- misuse of cryptographic API
  • Cryptographic
  • Local

HKDF in cryptography before 1.5.2 returns an empty byte-string if used with a length less than algorithm.digest_size.

CVE
CVE-2016-9243
CWE
CWE- misuse of cryptographic API
CVSS base score
7.5
Published
2017-03-27
OWASP
A03 Sensitive Data Exposure
Orthogonal defect classification
Algorithm
Code defect classification
Incorrect Algorithm
Category
Cryptographic
Subcategory
Cryptographic Implementation Error
Accessibility scope
Local
Impact
Information Disclosure
Affected component
Cryptography
Fixed by upgrading
Yes

Solution

Upgrade to HKDF version 1.5.2 or later.

Vulnerable code sample

from cryptography.hazmat.primitives.kdf.hkdf import HKDF
from cryptography.hazmat.primitives import hashes

hkdf = HKDF(
    algorithm=hashes.SHA256(),
    length=20,
    salt=None,
    info=b''
)

input_key_material = b'some_key_material'
derived_key = hkdf.derive(input_key_material)

print(derived_key)

Patched code sample

import os
from cryptography.hazmat.primitives.kdf.hkdf import HKDF
from cryptography.hazmat.primitives import hashes

salt = os.urandom(16)
info = b'some_context_info'

hkdf = HKDF(
    algorithm=hashes.SHA256(),
    length=20,
    salt=salt,
    info=info
)

input_key_material = b'some_key_material'
derived_key = hkdf.derive(input_key_material)

print(derived_key)

Payload

input_key_material = b'some_key_material'
length = 20  # Length less than SHA256.digest_size (32)

Cite this entry

@misc{vaitp:cve20169243,
  title        = {{HKDF returns empty byte-string for lengths less than digest_size.}},
  author       = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
  year         = {2017},
  note         = {VAITP Python Vulnerability Dataset, entry CVE-2016-9243},
  howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2016-9243/}}
}
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.

The supreme art of war is to subdue the enemy without fighting.

Sun Tzu – “The Art of War”

:: Shaping the future through research and ingenuity ::