CVE Vulnerabilities

CVE-2017-7901

Use of Insufficiently Random Values

Published: Jun 30, 2017 | Modified: Jul 08, 2017
CVSS 3.x
8.6
HIGH
Source:
NVD
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
CVSS 2.x
9 HIGH
AV:N/AC:L/Au:N/C:P/I:P/A:C
RedHat/V2
RedHat/V3
Ubuntu

A Predictable Value Range from Previous Values issue was discovered in Rockwell Automation Allen-Bradley MicroLogix 1100 programmable-logic controllers 1763-L16AWA, Series A and B, Version 16.00 and prior versions; 1763-L16BBB, Series A and B, Version 16.00 and prior versions; 1763-L16BWA, Series A and B, Version 16.00 and prior versions; and 1763-L16DWD, Series A and B, Version 16.00 and prior versions and Allen-Bradley MicroLogix 1400 programmable logic controllers 1766-L32AWA, Series A and B, Version 16.00 and prior versions; 1766-L32BWA, Series A and B, Version 16.00 and prior versions; 1766-L32BWAA, Series A and B, Version 16.00 and prior versions; 1766-L32BXB, Series A and B, Version 16.00 and prior versions; 1766-L32BXBA, Series A and B, Version 16.00 and prior versions; and 1766-L32AWAA, Series A and B, Version 16.00 and prior versions. Insufficiently random TCP initial sequence numbers are generated, which may allow an attacker to predict the numbers from previous values. This may allow an attacker to spoof or disrupt TCP connections, resulting in a denial of service for the target device.

Weakness

The product uses insufficiently random numbers or values in a security context that depends on unpredictable numbers.

Affected Software

Name Vendor Start Version End Version
1763-l16awa_series_a Rockwellautomation * 16.000 (including)
1763-l16awa_series_b Rockwellautomation * 16.000 (including)
1763-l16bbb_series_a Rockwellautomation * 16.000 (including)
1763-l16bbb_series_b Rockwellautomation * 16.000 (including)
1763-l16bwa_series_a Rockwellautomation * 16.000 (including)
1763-l16bwa_series_b Rockwellautomation * 16.000 (including)
1763-l16dwd_series_a Rockwellautomation * 16.000 (including)
1763-l16dwd_series_b Rockwellautomation * 16.000 (including)

Potential Mitigations

  • Use a well-vetted algorithm that is currently considered to be strong by experts in the field, and select well-tested implementations with adequate length seeds.
  • In general, if a pseudo-random number generator is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.
  • Pseudo-random number generators can produce predictable numbers if the generator is known and the seed can be guessed. A 256-bit seed is a good starting point for producing a “random enough” number.

References