CVE-2026-74874: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG) in jahlives openssl_encrypt
openssl_encrypt versions before 1.4.0 use Python's non-cryptographic random module for steganographic pixel selection in the generate_pseudorandom_sequence function. Attackers who know the password can recover the Mersenne Twister state from approximately 624 outputs and predict pixel locations containing hidden data for extraction.
AI Analysis
Technical Summary
The vulnerability arises because openssl_encrypt versions prior to 1.4.0 rely on Python's non-cryptographic random module for generating pseudorandom sequences used in steganographic pixel selection. The Mersenne Twister PRNG is not suitable for cryptographic purposes. Attackers with knowledge of the password can reconstruct the PRNG state from approximately 624 outputs, allowing them to predict the pixel locations where hidden data is embedded and extract it.
Potential Impact
This weakness allows attackers who know the password to bypass the intended confidentiality of steganographically hidden data by predicting pixel locations used for embedding. This compromises the confidentiality of the hidden information, potentially exposing sensitive data.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. No official fix or temporary workaround is currently documented. Users should avoid using affected versions until a fix is available.
CVE-2026-74874: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG) in jahlives openssl_encrypt
Description
openssl_encrypt versions before 1.4.0 use Python's non-cryptographic random module for steganographic pixel selection in the generate_pseudorandom_sequence function. Attackers who know the password can recover the Mersenne Twister state from approximately 624 outputs and predict pixel locations containing hidden data for extraction.
CVSS v4.0
Score 8.7high
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The vulnerability arises because openssl_encrypt versions prior to 1.4.0 rely on Python's non-cryptographic random module for generating pseudorandom sequences used in steganographic pixel selection. The Mersenne Twister PRNG is not suitable for cryptographic purposes. Attackers with knowledge of the password can reconstruct the PRNG state from approximately 624 outputs, allowing them to predict the pixel locations where hidden data is embedded and extract it.
Potential Impact
This weakness allows attackers who know the password to bypass the intended confidentiality of steganographically hidden data by predicting pixel locations used for embedding. This compromises the confidentiality of the hidden information, potentially exposing sensitive data.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. No official fix or temporary workaround is currently documented. Users should avoid using affected versions until a fix is available.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- VulnCheck
- Date Reserved
- 2026-08-17T10:31:04.593Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a82f003bf8831d539c48306
Added to database: 08/17/2026, 11:26:59 UTC
Last enriched: 08/17/2026, 11:56:05 UTC
Last updated: 08/18/2026, 01:31:35 UTC
Views: 5
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