PYSEC-2026-3754
Vulnerability from pysec - Published: 2026-08-17 11:16 - Updated: 2026-09-02 08:34
VLAI
Details
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.
Severity
Impacted products
| Name | purl | openssl-encrypt | pkg:pypi/openssl-encrypt |
|---|
Aliases
{
"affected": [
{
"ecosystem_specific": {},
"package": {
"ecosystem": "PyPI",
"name": "openssl-encrypt",
"purl": "pkg:pypi/openssl-encrypt"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.4.0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.2.2",
"0.2.3",
"0.2.4",
"0.2.5",
"0.2.6",
"0.3.0",
"0.3.1",
"0.3.2",
"0.3.3",
"0.4.0",
"0.4.1",
"0.4.2",
"0.4.3",
"0.4.4",
"0.5.0",
"0.5.1",
"0.5.3",
"0.6.0rc1",
"0.7.0rc2",
"0.7.1",
"0.7.2",
"0.8.0",
"0.8.1",
"0.8.2",
"0.9.2",
"1.0.0",
"1.0.1",
"1.0.2",
"1.0.3",
"1.1.0",
"1.2.0",
"1.2.1",
"1.3.0",
"1.3.1",
"1.3.2",
"1.3.3",
"1.3.4",
"1.3.5",
"1.4.0b3",
"1.4.0b4",
"1.4.0b5",
"1.4.0b6",
"1.4.0b7",
"1.4.0b8"
]
}
],
"aliases": [
"CVE-2026-74874",
"GHSA-vfgx-5q85-58q3"
],
"details": "openssl_encrypt versions before 1.4.0 use Python\u0027s 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.",
"id": "PYSEC-2026-3754",
"modified": "2026-09-02T08:34:39.407236Z",
"published": "2026-08-17T11:16:41.813Z",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/jahlives/openssl_encrypt/security/advisories/GHSA-vfgx-5q85-58q3"
},
{
"type": "ADVISORY",
"url": "https://www.vulncheck.com/advisories/openssl-encrypt-before-weak-prng-steganography-pixel-selection"
}
],
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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