CVE-2025-29913

March 17, 2025, 11:15 p.m.

None
No Score

Description

CryptoLib provides a software-only solution using the CCSDS Space Data Link Security Protocol - Extended Procedures (SDLS-EP) to secure communications between a spacecraft running the core Flight System (cFS) and a ground station. A critical heap buffer overflow vulnerability was identified in the `Crypto_TC_Prep_AAD` function of CryptoLib versions 1.3.3 and prior. This vulnerability allows an attacker to trigger a Denial of Service (DoS) or potentially execute arbitrary code (RCE) by providing a maliciously crafted telecommand (TC) frame that causes an unsigned integer underflow. The vulnerability lies in the function `Crypto_TC_Prep_AAD`, specifically during the computation of `tc_mac_start_index`. The affected code incorrectly calculates the MAC start index without ensuring it remains within the bounds of the `ingest` buffer. When `tc_mac_start_index` underflows due to an incorrect length calculation, the function attempts to access an out-of-bounds memory location, leading to a segmentation fault. The vulnerability is still present in the repository as of commit `d3cc420ace96d02a5b7e83d88cbd2e48010d5723`.

Product(s) Impacted

Vendor Product Versions
Cryptolib
  • Cryptolib
  • 1.3.3, *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-125
Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a cryptolib cryptolib 1.3.3 / / / / / / /
a cryptolib cryptolib / / / / / / / /

Date

  • Published: March 17, 2025, 11:15 p.m.
  • Last Modified: March 17, 2025, 11:15 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.