Litellm

United States Open Source litellm.ai ↗
B
MODERATE
14
Total CVEs
5
Crit / High
0
Medium
25%
Unpatched
0%
Patched
7.9
Avg CVSS
0
CISA KEV
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▸ CVE Trend by Year
▸ Patch Coverage
Patched
0%
Unpatched
25%
Under Review
75%
✓ 0 patched ✗ 1 unpatched ~ 3 under review
▸ Intelligence by Audience
PoC Available
3 / 20 shown
CISA KEV (Exploited)
0
Shodan Dorks
ssl:"litellm" port:443
org:"Litellm" http.status:200
Top EPSS (Exploitation Probability)
CVE-2026-47101 1.33% exploitation probability
CVE-2026-59822 0.84% exploitation probability
CVE-2026-47102 0.82% exploitation probability
CVE-2025-11203 0.10% exploitation probability
Quick Facts for Reporting
Total CVEs tracked
14
Critical severity
0
Actively exploited (CISA)
0
Unpatched ratio
25%
Avg CVSS score
7.9
Security grade
B (MODERATE)
NVD Data Attribution
Source: NIST National Vulnerability Database (NVD) + GitHub Advisory Database.
Data aggregated by Valters IT Hub · valtersit.com
Last updated: 2026-08-03
Security Risk Score (for investors)
LOW
Vuln Volume
GOOD
Patch Responsiveness
LOW
CISA Exposure
⚠ Not financial advice. Past security incidents do not guarantee future stock performance.
▸ Recent CVEs showing 20 of 4
CVE IDSeverityPatchEPSSDate
CVE-2026-59822 KEV 8.2 HIGH PATCH UNDER REVIEW 0.84% 2026-07-08
CVE-2026-47102 PoC 8.8 HIGH PATCH UNDER REVIEW 0.82% 2026-05-21
CVE-2026-47101 PoC 8.8 HIGH PATCH UNDER REVIEW 1.33% 2026-05-21
CVE-2025-11203 PoC 3.5 LOW UNKNOWN / UNPATCHED 0.10% 2025-10-29
View all 4 CVEs for Litellm →
▸Intel
CountryUnited States
LicenseOpen Source
Trust ScoreB — MODERATE
Max CVSS8.8
Last Updated2026-08-03
▸Company Profile

LiteLLM is a software company that provides an open-source proxy server and SDK for managing and routing API calls to various large language models (LLMs) from providers like OpenAI, Anthropic, and Google. Its product is significant for cybersecurity as it centralizes access control, logging, and rate limiting for LLM usage, helping organizations enforce security policies and monitor for misuse. The company's focus on API management for AI models addresses emerging security concerns in enterprise AI deployments.

▸Response Metrics
Est. MTTR ⓘ ~500 days (Critical)
Mean Time To Remediate. Estimates days from CVE disclosure to patch.
Industry avg: ~60d (good) · 100-300d (poor) · 300d+ (critical)
CVE Trend ⓘ ↗ +1200% worse
CVE count 2026 vs 2025:  1 → 13 CVEs
Patch Speed ⓘ Good (20–40% open)
25% of CVEs still unpatched.  Excellent: <20% · Good: 20-40% · Avg: 40-65% · Poor: >65%
▸ Financial Risk Estimate
Est. GDPR Low
€171K
Est. GDPR High
€1.7M

Based on 0 critical CVEs, 0 CISA KEV, 29% unpatched. Model: GDPR Art.83 · not legal advice.

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