GHSA-H45M-MGCP-Q388
Vulnerability from github – Published: 2026-03-31 23:41 – Updated: 2026-03-31 23:41
VLAI
Summary
openssl-encrypt: TOTP rate limiter is in-memory only — not shared across workers, lost on restart
Details
Severity: HIGH
Summary
The TOTP brute-force rate limiter in openssl_encrypt_server/modules/pepper/totp.py at lines 47-98 uses an in-memory defaultdict(list) as a class variable.
Affected Code
class TOTPRateLimiter:
def __init__(self, ...):
self.attempts: Dict[str, List[datetime]] = defaultdict(list)
self.lockouts: Dict[str, datetime] = {}
class TOTPService:
_rate_limiter = TOTPRateLimiter() # Class variable, in-memory only
Impact
- Rate limit state is not shared across multiple server instances/workers — an attacker can distribute attempts
- All rate limit state is lost on server restart — allows immediate retry
- In multi-worker deployments, each worker has independent rate limit state
Recommended Fix
- Use Redis or the database for rate limit state storage
- Or use a shared-memory approach for multi-worker deployments
- At minimum, persist lockout state to survive restarts
Fix
Fixed in commit 2749bc0 on branch releases/1.4.x — added abstract RateLimitBackend with InMemoryBackend and DatabaseBackend implementations; defaults to DatabaseBackend when DB available.
Severity
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "openssl-encrypt"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.4.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-03-31T23:41:26Z",
"nvd_published_at": null,
"severity": "CRITICAL"
},
"details": "## Severity: HIGH\n\n### Summary\n\nThe TOTP brute-force rate limiter in `openssl_encrypt_server/modules/pepper/totp.py` at **lines 47-98** uses an in-memory `defaultdict(list)` as a class variable.\n\n### Affected Code\n\n```python\nclass TOTPRateLimiter:\n def __init__(self, ...):\n self.attempts: Dict[str, List[datetime]] = defaultdict(list)\n self.lockouts: Dict[str, datetime] = {}\n\nclass TOTPService:\n _rate_limiter = TOTPRateLimiter() # Class variable, in-memory only\n```\n\n### Impact\n\n1. Rate limit state is **not shared** across multiple server instances/workers \u2014 an attacker can distribute attempts\n2. All rate limit state is **lost on server restart** \u2014 allows immediate retry\n3. In multi-worker deployments, each worker has independent rate limit state\n\n### Recommended Fix\n\n- Use Redis or the database for rate limit state storage\n- Or use a shared-memory approach for multi-worker deployments\n- At minimum, persist lockout state to survive restarts\n\n### Fix\n\nFixed in commit `2749bc0` on branch `releases/1.4.x` \u2014 added abstract RateLimitBackend with InMemoryBackend and DatabaseBackend implementations; defaults to DatabaseBackend when DB available.",
"id": "GHSA-h45m-mgcp-q388",
"modified": "2026-03-31T23:41:26Z",
"published": "2026-03-31T23:41:26Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/jahlives/openssl_encrypt/security/advisories/GHSA-h45m-mgcp-q388"
},
{
"type": "WEB",
"url": "https://github.com/jahlives/openssl_encrypt/commit/2749bc0949b34a5921a35fb4a3f1856fc51916de"
},
{
"type": "PACKAGE",
"url": "https://github.com/jahlives/openssl_encrypt"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "openssl-encrypt: TOTP rate limiter is in-memory only \u2014 not shared across workers, lost on restart"
}
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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